{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Инфраструктура Python. Источники данных" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Архивы" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "todo Python поддерживает чтение некоторых типов архивов (https://docs.python.org/2/library/archiving.html)\n", "\n", "todo Нужен отчет по ФС (особенно по либе), какие встречаются архивы\n", "\n", " zlib.decompress(s)\n", " \n", " with zipfile.ZipFile(fn) as z:\n", " for info in z.infolist:\n", " print info.filename, info.file_size, z.read(info.filename)[:100]\n", " \n", " zlib\n", " gzip\n", " bz2\n", " zipfile\n", " tarfile\n", "\n", " `backports.lzma` для .xz и .lzma | pylzma\n", " libarchive -- Windows?\n", " rarfile\n", " https://github.com/harvimt/pylib7zip\n", " bz2file\n", " lz4\n", " python-lzo\n", " Brotli | brotlipy\n", " zopfli | zopflipy | pyzopfli\n", " mpyq is a Python library for reading MPQ (MoPaQ) archives used in many of Blizzard's games" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Документы: pdf djvu doc rtf chm docx xls xlsx odt\n", "\n", "Архивы либгена по популярности: rar zip gz exe/SFX ha iso 7z bz2 nrg ace arj isz tar msi daa mdf" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "todo Как читать контейнеры виртуальных машин, образы дисков, iso?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Форматы обмена данными" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### JSON" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "В веб повсеместно используется JSON, похожий на литералы в JavaScript." ] }, { "cell_type": "code", "execution_count": 115, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{u'u': [1, 2, 3]}\n", "[1, 3, 5, \"abc\", {\"o\": true}]\n" ] } ], "source": [ "import json\n", "print json.loads('{\"u\":[1,2,3]}')\n", "print json.dumps([1,3,5,'abc',{'o':True}])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### XML" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Устарел, но еще встречается (например, в формате fb2) XML. Для работы с ним подходит встроенная библиотека `lxml`. Одним из удобных способов искать что-нибудь в XML (как во всем документе, так и в отдельном узле) являются селекторы XPath." ] }, { "cell_type": "code", "execution_count": 103, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " description {'id': '125'} [('id', '125')] ['id'] ['125'] 125\n", "['child_sf']\n", "first-name Сергей\n", "last-name Другаль\n", "\n", " Сергей\n", " Другаль\n", " \n", " \n" ] } ], "source": [ "from lxml import etree\n", "xml = '''\\\n", "\n", " \n", " child_sf\n", " \n", " Сергей\n", " Другаль\n", " \n", " Тигр проводит вас до гаража\n", " \n", "\n", "'''\n", "doc = etree.XML(xml)\n", "print doc, doc.tag, doc.attrib, doc.items(), doc.keys(), doc.values(), doc.get('id')\n", "print doc.xpath('/description/title-info/genre/text()')\n", "for c in doc.xpath('//author')[0].getchildren():\n", " print c.tag, c.text\n", "print etree.tostring(doc.xpath('//author')[0])" ] }, { "cell_type": "code", "execution_count": 476, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "child_sf\n" ] } ], "source": [ "for info in doc.findall('title-info'):\n", " for genre in info.findall('genre'):\n", " print genre.text" ] }, { "cell_type": "code", "execution_count": 492, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ ":1:29:FATAL:PARSER:ERR_TAG_NAME_MISMATCH: Opening and ending tag mismatch: root line 1 and rot" ] }, "execution_count": 492, "metadata": {}, "output_type": "execute_result" } ], "source": [ "parser = etree.XMLParser(recover=True)\n", "tree = etree.fromstring('', parser)\n", "parser.error_log" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Библиотека `lxml` содержит и менее требовательный к памяти на больших XML SAX-парсер, генерирующий эвенты в процессе разбора." ] }, { "cell_type": "code", "execution_count": 108, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[('end', ),\n", " ('end', ),\n", " ('end', ),\n", " ('end', ),\n", " ('end', ),\n", " ('end', ),\n", " ('end', )]" ] }, "execution_count": 108, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import lxml\n", "list(lxml.etree.iterparse(BytesIO(xml)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "С небольшим XML может быть удобнее работать в стиле библиотеки `json`, для этого есть библиотека `xmltodict`" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```\n", "pip install xmltodict\n", "```" ] }, { "cell_type": "code", "execution_count": 54, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "OrderedDict([(u'description', OrderedDict([(u'@id', u'125'), (u'title-info', OrderedDict([(u'genre', u'child_sf'), (u'author', OrderedDict([(u'first-name', u'\\u0421\\u0435\\u0440\\u0433\\u0435\\u0439'), (u'last-name', u'\\u0414\\u0440\\u0443\\u0433\\u0430\\u043b\\u044c')])), (u'book-title', u'\\u0422\\u0438\\u0433\\u0440 \\u043f\\u0440\\u043e\\u0432\\u043e\\u0434\\u0438\\u0442 \\u0432\\u0430\\u0441 \\u0434\\u043e \\u0433\\u0430\\u0440\\u0430\\u0436\\u0430')]))]))])\n", "Другаль\n" ] } ], "source": [ "import xmltodict\n", "dic = xmltodict.parse(xml)\n", "print dic\n", "print dic['description']['title-info']['author']['last-name']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Впрочем, использовать ее следует с осторожностью" ] }, { "cell_type": "code", "execution_count": 59, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "OrderedDict([(u'a', OrderedDict([(u'b', [u'1', u'3']), ('#text', u'2')]))])\n", "\n", "\n", "132\n" ] } ], "source": [ "parsed = xmltodict.parse('123')\n", "print parsed\n", "print\n", "print xmltodict.unparse(parsed)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### HTML" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "HTML похож на XML, с которым они имеют общего предшественника, так что для парсинга HTML можно использовать ту же библиотеку `lxml`. Оттуда же пришли селекторы CSS, иногда позволяющие записать выборку короче." ] }, { "cell_type": "code", "execution_count": 65, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n", "Hello, HTML of evil, you are rocks\n", "\n", "\n", " Hello, HTML of evil, you are rocks\n", "\n", "\n", "[] ' of evil'\n", "'Hello, ' ', you are rocks'\n" ] } ], "source": [ "html = 'Hello, HTML of evil, you are rocks'\n", "doc = etree.HTML(html)\n", "print doc\n", "print\n", "print etree.tostring(doc)\n", "print\n", "etree.dump(doc)\n", "print\n", "print doc.cssselect('.red'), repr(doc.cssselect('.red')[0].tail)\n", "a = doc.cssselect('a')[0]\n", "print repr(a.text), repr(a.tail)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Pickle" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Почти все Python-объекты могут быть сериализованы в формат `pickle`. Но он плохо подходит для передачи данных, потому что зависит от версии Python и позволяет исполнять код при загрузке." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "todo Интероп pickle (2<->3, x32-x64, или лучше dill? pickleshare?), bson? cPickle? objloader?\n", "\n", "The pickle library often fails for complex functions including lambdas, closures, and class methods. When this occurs we recommend the alternative serialization library dill.\n", "\n", "альтернативы pickle: marshmallow, dill, и pyro" ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import pickle\n", "from collections import OrderedDict\n", "from numpy import nan" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "\"ccollections\\nOrderedDict\\np0\\n((lp1\\n(lp2\\n(I1\\nI2\\nI3\\ntp3\\na(dp4\\nS'a'\\np5\\nc__builtin__\\nset\\np6\\n((lp7\\nI1\\naI2\\naI3\\natp8\\nRp9\\nsS'c'\\np10\\n(lp11\\nsS'b'\\np12\\nFnan\\nsaatp13\\nRp14\\n.\"" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data = OrderedDict([((1,2,3), {'a': {1, 2, 3}, 'b': nan, 'c': []})])\n", "serialized = pickle.dumps(data)\n", "serialized" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "OrderedDict([((1, 2, 3), {'a': {1, 2, 3}, 'b': nan, 'c': []})])" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pickle.loads(serialized)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "С просмотром и анализом файла, сгенерированного `pickle`, может помочь встроенная библиотека `pickletools`" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import pickletools" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "158 108\n" ] } ], "source": [ "print len(serialized), len(pickletools.optimize(serialized))" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 0: c GLOBAL 'collections OrderedDict'\n", " 25: ( MARK\n", " 26: ( MARK\n", " 27: l LIST (MARK at 26)\n", " 28: ( MARK\n", " 29: l LIST (MARK at 28)\n", " 30: ( MARK\n", " 31: I INT 1\n", " 34: I INT 2\n", " 37: I INT 3\n", " 40: t TUPLE (MARK at 30)\n", " 41: a APPEND\n", " 42: ( MARK\n", " 43: d DICT (MARK at 42)\n", " 44: S STRING 'a'\n", " 49: c GLOBAL '__builtin__ set'\n", " 66: ( MARK\n", " 67: ( MARK\n", " 68: l LIST (MARK at 67)\n", " 69: I INT 1\n", " 72: a APPEND\n", " 73: I INT 2\n", " 76: a APPEND\n", " 77: I INT 3\n", " 80: a APPEND\n", " 81: t TUPLE (MARK at 66)\n", " 82: R REDUCE\n", " 83: s SETITEM\n", " 84: S STRING 'c'\n", " 89: ( MARK\n", " 90: l LIST (MARK at 89)\n", " 91: s SETITEM\n", " 92: S STRING 'b'\n", " 97: F FLOAT nan\n", " 102: s SETITEM\n", " 103: a APPEND\n", " 104: a APPEND\n", " 105: t TUPLE (MARK at 25)\n", " 106: R REDUCE\n", " 107: . STOP\n", "highest protocol among opcodes = 0\n" ] } ], "source": [ "pickletools.dis(pickletools.optimize(serialized))" ] }, { "cell_type": "code", "execution_count": 48, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 0: c GLOBAL '__builtin__ eval'\n", " 18: ( MARK\n", " 19: c GLOBAL '__builtin__ compile'\n", " 40: ( MARK\n", " 41: V UNICODE u'print \"BOOM!\"'\n", " 56: V UNICODE u'-'\n", " 59: V UNICODE u'exec'\n", " 65: t TUPLE (MARK at 40)\n", " 66: R REDUCE\n", " 67: t TUPLE (MARK at 18)\n", " 68: R REDUCE\n", " 69: . STOP\n", "highest protocol among opcodes = 0\n" ] } ], "source": [ "pickle_bomb = '''\\\n", "c__builtin__\n", "eval\n", "(c__builtin__\n", "compile\n", "(Vprint \"BOOM!\"\n", "V-\n", "Vexec\n", "tRtR.'''\n", "pickletools.dis(pickle_bomb)" ] }, { "cell_type": "code", "execution_count": 49, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "BOOM!\n" ] } ], "source": [ "pickle.loads(pickle_bomb)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Несколько более читабельной альтернативой может послужить библиотека `jsonpickle`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```\n", "pip install jsonpickle\n", "```" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import jsonpickle" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "'{\"py/set\": [1267650600228229401496703205376, 1, 2.0, null]}'" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dumped = jsonpickle.dumps({1, 2.0, 2**100, None})\n", "dumped" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "{None, 1, 2.0, 1267650600228229401496703205376L}" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "jsonpickle.loads(dumped)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Bencode" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Очень похож на JSON, но удобнее для хранения бинарных данных формат Bencode, используемый, например, в файлах `*.torrent`. Для его парсинга используется одноименная библиотека `bencode`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```\n", "pip install bencode\n", "```" ] }, { "cell_type": "code", "execution_count": 87, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "d8:announce20:udp://shubt.net:271013:announce-listll20:udp://shubt.net:2710el33:http://bt.dugtor.ru:2710/announceel70:http://bt.nnm-club.info:2710/00c1495fbcc09403e464f01d58faee25/announceel188:http://retracker.local/announce.php?size=3479044224&comment=http%3A%2F%2Fnnm-club.me%2Fforum%2Fviewtopic.php%3Fp%3D8331459&name=Linux+Mint+18+Sarah+%28Mate%2C+Cinnamon%29+%5B64bit%5D+2xDVDel31:http://retracker.local/announceel43:http://tracker.filetracker.pl:8089/announceel44:http://tracker2.wasabii.com.tw:6969/announceel40:http://tracker.grepler.com:6969/announceel35:http://125.227.35.196:6969/announceel41:http://tracker.tiny-vps.com:6969/announceel35:http://87.248.186.252:8080/announceel34:http://210.244.71.25:6969/announceel33:http://46.4.109.148:6969/announceel37:http://tracker.dler.org:6969/announceel37:udp://[2001:67c:28f8:92::1111:1]:2710el37:udp://ipv6.leechers-paradise.org:6969el24:udp://46.148.18.250:2710ee7:comment30:http://rutor.is/torrent/51182610:created by21:Friend721 (DugTor.ru)13:creation datei1467152079e4:infod5:filesld6:lengthi128e4:pathl12:checksum.md5eed6:lengthi1697906688e4:pathl31:linuxmint-18-cinnamon-64bit.isoeed6:lengthi1781137408e4:pathl27:linuxmint-18-mate-64bit.isoeee4:name18:LinuxMint-18-64bit12:piece lengthi52\n", "\n", "{\n", " \"announce\": \"udp://shubt.net:2710\", \n", " \"announce-list\": [\n", " [\n", " \"udp://shubt.net:2710\"\n", " ], \n", " \"...\"\n", " ], \n", " \"comment\": \"http://rutor.is/torrent/511826\", \n", " \"created by\": \"Friend721 (DugTor.ru)\", \n", " \"creation date\": 1467152079, \n", " \"info\": {\n", " \"files\": [\n", " {\n", " \"length\": 128, \n", " \"path\": [\n", " \"checksum.md5\"\n", " ]\n", " }, \n", " {\n", " \"length\": 1697906688, \n", " \"path\": [\n", " \"linuxmint-18-cinnamon-64bit.iso\"\n", " ]\n", " }, \n", " {\n", " \"length\": 1781137408, \n", " \"path\": [\n", " \"linuxmint-18-mate-64bit.iso\"\n", " ]\n", " }\n", " ], \n", " \"name\": \"LinuxMint-18-64bit\", \n", " \"piece length\": 524288, \n", " \"pieces\": \"(less noise)\"\n", " }, \n", " \"publisher\": \"rutor.is\", \n", " \"publisher-url\": \"http://rutor.is/torrent/511826\"\n", "}\n" ] } ], "source": [ "import bencode, requests, json\n", "\n", "torrent = requests.get('http://d.rutor.info/download/511826').content\n", "print torrent[:1250]\n", "print\n", "decoded = bencode.bdecode(torrent)\n", "decoded['info']['pieces'] = '(less noise)'\n", "decoded['announce-list'] = [['udp://shubt.net:2710'], '...']\n", "print json.dumps(decoded, indent=4, sort_keys=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### TOML" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Если структурированные данные хочется задавать ручками в текстовом редакторе или диффать, ни JSON, ни XML не лучший выбор. Удобнее всего для этих целей TOML, язык разметки, похожий на формат `*.ini` файлов." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```\n", "pip install toml\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "todo или лучше pytoml?" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "y = \"e\"\n", "abc = [ 1, 2,]\n", "\n", "[def]\n", "u = \"i\"\n", "\n", "[def.\"Привет\"]\n", "o2 = 2\n", "o = 1\n", "\n" ] } ], "source": [ "import toml\n", "print toml.dumps({\n", " \"abc\": [1,2],\n", " \"def\": {\n", " u\"Привет\": {\"o\": 1, \"o2\": 2},\n", " \"u\": \"i\"\n", " },\n", " \"y\": \"e\"\n", "})" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "{u'section': {u'value': [{u'a': u'A', u'b': u'B'},\n", " {u'a': u'AA', u'b': u'BB'}]}}" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "toml.loads('''\n", "[section]\n", "[[section.value]]\n", "a = \"A\"\n", "b = \"B\"\n", "[[section.value]]\n", "a = \"AA\"\n", "b = \"BB\"\n", "''')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Табличные данные" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Встроенная библиотека `csv` позволяет построчно читать в списки (и писать из) строки CSV-файла." ] }, { "cell_type": "code", "execution_count": 79, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from io import BytesIO\n", "import csv" ] }, { "cell_type": "code", "execution_count": 96, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['headerA', ' headerB', ' headerC']\n", "['1', '2', '3']\n", "['4', '5', '6 \\xd0\\xbf\\xd1\\x8b\\xd1\\x89']\n" ] } ], "source": [ "csvfile = BytesIO('''\\\n", "headerA, headerB, headerC\n", "1,2,3\n", "4,5,6 пыщ\n", "''')\n", "for line in csv.reader(csvfile):\n", " print line" ] }, { "cell_type": "code", "execution_count": 102, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "a;b\r\n", "c;\"d\"\"d\"\r\n", "e;f пыщ\r\n", "g;h\r\n", "\n" ] } ], "source": [ "io = BytesIO()\n", "writer = csv.writer(io, delimiter=';')\n", "data = [\n", " ['a', 'b'],\n", " ['c', 'd\"d'],\n", " ['e', 'f пыщ'],\n", "]\n", "writer.writerows(data)\n", "writer.writerow(['g', 'h'])\n", "print io.getvalue()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Для более высокоуровневой работы с табличными данными (обычно исходно в формате `csv`) в Python имеется библиотека `pandas`, предоставляющая доступ через не самый интуитивный API к различным выборкам и группировкам. http://pandas.pydata.org/pandas-docs/stable/index.html" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Основные классы `pandas`:\n", "\n", "* `Series`, похожий на 1D `numpy.array`, в котором можно именовать индексы\n", "* `DataFrame`, 2D таблица, похожая на словарь из колонок-`Series`" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "todo\n", "\n", "\timport pandas.tseries.offsets\n", "\t\n", "\tdf['column']\n", "\tdf.index, df.columns, df.values\n", "\n", "\tdf.set_index([\"State\", \"City\"]).sortlevel(0)\n", "\tdf.set_index(\"City\").sort([\"State\", \"NumericPopulation\"], ascending=[False, True])\n", "\n", "\tdf.groupby(df.columns[0]).aggregate(average)\n", "\tdf[df.columns[0]].apply(log10)\n", "\n", "\tdf.name.str.split(\" \", expand=True)\n", "\tdf.groupby('name')['activity'].value_counts()\n", "\tdf.groupby('name')['activity'].value_counts().unstack().fillna(0)\n", "\ton which row this column is changing by doing this: df.name!=df.name.shift()\n", "\tdf.sort_values(by=['name','timestamp'])\n", "\n", "\tpandas.qcut(data.weight, 10, labels=False) ввод новой фичи, дециля?\n", " \n", " df.pivot(index='date', columns='variable', values='value') EAV->relation\n", " df.melt(id_vars=['first', 'last'])\n", " \n", " pandas.crosstab\n", " pivot_table\n", "\n", " labels, uniques = pd.factorize(x)\n", " Out[111]: array([ 0, 0, -1, 1, 2, 3])\n", " Out[112]: Index(['A', 'B', 3.14, inf], dtype='object')\n", " \n", " scatter_matrix\n", " \n", " df.corr()\n", " \n", " data = data.fillna(data.median(axis=0), axis=0)\n", " pandas.get_dummies\n", " \n", " concat, join" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import pandas" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(3, 2)\n", "Index([u'a', u'b'], dtype='object')\n", "Index([u'first', u'second', u'third'], dtype='object')\n" ] }, { "data": { "text/html": [ "
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\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
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" ], "text/plain": [ " a b\n", "first 1.0 1.0\n", "second 3.0 2.0\n", "third 2.0 3.0" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.rank()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2\n", "2\n" ] } ], "source": [ "print df.iloc[0,1]\n", "print df.loc['first','b']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Объект `pandas.DataFrame` похож по API на словарь строка → `numpy.array`" ] }, { "cell_type": "code", "execution_count": 71, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "0 a\n", "1 a\n", "2 a\n", "3 a\n", "4 a\n", "Name: PID, dtype: object" ] }, "execution_count": 71, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import math\n", "(df['PID'] * 2).apply(math.sqrt).astype(int)[:5].map({69: 'a'})" ] }, { "cell_type": "code", "execution_count": 72, "metadata": { "collapsed": true }, "outputs": [], "source": [ "df['New Column'] = df['Operation'].apply(lambda s:s[:-1])" ] }, { "cell_type": "code", "execution_count": 73, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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SequenceTime of DayProcess NamePIDOperationPathResultDurationDetailNew Column
0NaN20:35:12,0034072Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VIDEOSUCCESS5.900000e-06Desired Access: Read, Maximum AllowedRegOpenKe
1NaN20:35:12,0034247Dwm.exe2432RegQueryValueHKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\MaxObjectNumberSUCCESS2.200000e-06Type: REG_DWORD, Length: 4, Data: 10RegQueryValu
2NaN20:35:12,0034379Dwm.exe2432RegCloseKeyHKLM\\HARDWARE\\DEVICEMAP\\VIDEOSUCCESS7.000000e-07NaNRegCloseKe
3NaN20:35:12,0034510Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VideoSUCCESS1.800000e-06Desired Access: ReadRegOpenKe
4NaN20:35:12,0034597Dwm.exe2432RegQueryValueHKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video4SUCCESS1.900000e-06Type: REG_SZ, Length: 202, Data: \\Registry\\Mac...RegQueryValu
5NaN20:35:12,0034721Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\CONTROL\\VIDEO\\{7...REPARSE4.800000e-06Desired Access: ReadRegOpenKe
6NaN20:35:12,0034835Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\CONTROL\\VIDEO\\{7...SUCCESS3.600000e-06Desired Access: ReadRegOpenKe
7NaN20:35:12,0034955Dwm.exe2432RegCloseKeyHKLM\\HARDWARE\\DEVICEMAP\\VIDEOSUCCESS7.000000e-07NaNRegCloseKe
8NaN20:35:12,0035031Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...NAME NOT FOUND7.700000e-06Length: 52RegQueryValu
9NaN20:35:12,0035181Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...SUCCESS7.000000e-07NaNRegCloseKe
10NaN20:35:12,0035287Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS2.200000e-06Desired Access: ReadRegOpenKe
11NaN20:35:12,0035381Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.500000e-06Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN...RegQueryValu
12NaN20:35:12,0035476Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS8.000000e-07NaNRegCloseKe
13NaN20:35:12,0035560Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.500000e-06Desired Access: ReadRegOpenKe
14NaN20:35:12,0035633Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.100000e-06Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN...RegQueryValu
15NaN20:35:12,0035721Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS7.000000e-07NaNRegCloseKe
16NaN20:35:12,0035801Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VideoSUCCESS1.800000e-06Desired Access: ReadRegOpenKe
17NaN20:35:12,0035877Dwm.exe2432RegQueryValueHKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video4SUCCESS1.100000e-06Type: REG_SZ, Length: 202, Data: \\Registry\\Mac...RegQueryValu
18NaN20:35:12,0035961Dwm.exe2432RegCloseKeyHKLM\\HARDWARE\\DEVICEMAP\\VIDEOSUCCESS8.000000e-07NaNRegCloseKe
19NaN20:35:12,0036917Dwm.exe2432RegQueryKeyHKLMSUCCESS1.100000e-06Query: HandleTags, HandleTags: 0x0RegQueryKe
20NaN20:35:12,0037011Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Control\\Video\\{7...REPARSE3.700000e-06Desired Access: Query ValueRegOpenKe
21NaN20:35:12,0037106Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Control\\Video\\{7...SUCCESS3.300000e-06Desired Access: Query ValueRegOpenKe
22NaN20:35:12,0037216Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...SUCCESS6.200000e-06Type: REG_BINARY, Length: 4, Data: 00 00 00 40RegQueryValu
23NaN20:35:12,0037336Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...BUFFER OVERFLOW1.500000e-06Length: 144RegQueryValu
24NaN20:35:12,0037420Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...SUCCESS1.400000e-06Type: REG_MULTI_SZ, Length: 142, Data: igdumdi...RegQueryValu
25NaN20:35:12,0037504Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...SUCCESS7.000000e-07NaNRegCloseKe
26NaN20:35:12,0037606Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VIDEOSUCCESS1.800000e-06Desired Access: Read, Maximum AllowedRegOpenKe
27NaN20:35:12,0037686Dwm.exe2432RegQueryValueHKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\MaxObjectNumberSUCCESS1.100000e-06Type: REG_DWORD, Length: 4, Data: 10RegQueryValu
28NaN20:35:12,0037770Dwm.exe2432RegCloseKeyHKLM\\HARDWARE\\DEVICEMAP\\VIDEOSUCCESS7.000000e-07NaNRegCloseKe
29NaN20:35:12,0037861Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VideoSUCCESS1.500000e-06Desired Access: ReadRegOpenKe
.................................
75083NaN20:35:18,4282281Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.100000e-06NaNRegCloseKe
75084NaN20:35:18,4282412Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS2.200000e-06Desired Access: ReadRegOpenKe
75085NaN20:35:18,4282536Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.500000e-06Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN...RegQueryValu
75086NaN20:35:18,4282675Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.000000e-06NaNRegCloseKe
75087NaN20:35:18,4282802Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VideoSUCCESS2.900000e-06Desired Access: ReadRegOpenKe
75088NaN20:35:18,4282926Dwm.exe2432RegQueryValueHKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video4SUCCESS1.800000e-06Type: REG_SZ, Length: 202, Data: \\Registry\\Mac...RegQueryValu
75089NaN20:35:18,4283068Dwm.exe2432RegCloseKeyHKLM\\HARDWARE\\DEVICEMAP\\VIDEOSUCCESS8.000000e-07NaNRegCloseKe
75090NaN20:35:18,4283830Dwm.exe2432RegQueryKeyHKLMSUCCESS1.500000e-06Query: HandleTags, HandleTags: 0x0RegQueryKe
75091NaN20:35:18,4283969Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Control\\Video\\{7...REPARSE5.500000e-06Desired Access: Query ValueRegOpenKe
75092NaN20:35:18,4284119Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Control\\Video\\{7...SUCCESS4.700000e-06Desired Access: Query ValueRegOpenKe
75093NaN20:35:18,4284283Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...SUCCESS9.400000e-06Type: REG_BINARY, Length: 4, Data: 00 00 00 40RegQueryValu
75094NaN20:35:18,4284472Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...BUFFER OVERFLOW2.200000e-06Length: 144RegQueryValu
75095NaN20:35:18,4284585Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...SUCCESS2.200000e-06Type: REG_MULTI_SZ, Length: 142, Data: igdumdi...RegQueryValu
75096NaN20:35:18,4284713Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...SUCCESS1.400000e-06NaNRegCloseKe
75097NaN20:35:18,4284884Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VIDEOSUCCESS3.300000e-06Desired Access: Read, Maximum AllowedRegOpenKe
75098NaN20:35:18,4285019Dwm.exe2432RegQueryValueHKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\MaxObjectNumberSUCCESS1.500000e-06Type: REG_DWORD, Length: 4, Data: 10RegQueryValu
75099NaN20:35:18,4285161Dwm.exe2432RegCloseKeyHKLM\\HARDWARE\\DEVICEMAP\\VIDEOSUCCESS1.100000e-06NaNRegCloseKe
75100NaN20:35:18,4285304Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VideoSUCCESS2.500000e-06Desired Access: ReadRegOpenKe
75101NaN20:35:18,4285428Dwm.exe2432RegQueryValueHKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video5SUCCESS1.800000e-06Type: REG_SZ, Length: 202, Data: \\Registry\\Mac...RegQueryValu
75102NaN20:35:18,4285595Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\CONTROL\\VIDEO\\{7...REPARSE4.000000e-06Desired Access: ReadRegOpenKe
75103NaN20:35:18,4285734Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\CONTROL\\VIDEO\\{7...SUCCESS4.000000e-06Desired Access: ReadRegOpenKe
75104NaN20:35:18,4285902Dwm.exe2432RegCloseKeyHKLM\\HARDWARE\\DEVICEMAP\\VIDEOSUCCESS1.100000e-06NaNRegCloseKe
75105NaN20:35:18,4286007Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...NAME NOT FOUND9.900000e-06Length: 52RegQueryValu
75106NaN20:35:18,4286223Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...SUCCESS1.000000e-06NaNRegCloseKe
75107NaN20:35:18,4286354Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS2.200000e-06Desired Access: ReadRegOpenKe
75108NaN20:35:18,4286481Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.900000e-06Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN...RegQueryValu
75109NaN20:35:18,4286624Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.100000e-06NaNRegCloseKe
75110NaN20:35:18,4286748Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS2.200000e-06Desired Access: ReadRegOpenKe
75111NaN20:35:18,4286879Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.400000e-06Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN...RegQueryValu
75112NaN20:35:18,4287014Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.100000e-06NaNRegCloseKe
\n", "

75113 rows × 10 columns

\n", "
" ], "text/plain": [ " Sequence Time of Day Process Name PID Operation \\\n", "0 NaN 20:35:12,0034072 Dwm.exe 2432 RegOpenKey \n", "1 NaN 20:35:12,0034247 Dwm.exe 2432 RegQueryValue \n", "2 NaN 20:35:12,0034379 Dwm.exe 2432 RegCloseKey \n", "3 NaN 20:35:12,0034510 Dwm.exe 2432 RegOpenKey \n", "4 NaN 20:35:12,0034597 Dwm.exe 2432 RegQueryValue \n", "5 NaN 20:35:12,0034721 Dwm.exe 2432 RegOpenKey \n", "6 NaN 20:35:12,0034835 Dwm.exe 2432 RegOpenKey \n", "7 NaN 20:35:12,0034955 Dwm.exe 2432 RegCloseKey \n", "8 NaN 20:35:12,0035031 Dwm.exe 2432 RegQueryValue \n", "9 NaN 20:35:12,0035181 Dwm.exe 2432 RegCloseKey \n", "10 NaN 20:35:12,0035287 Dwm.exe 2432 RegOpenKey \n", "11 NaN 20:35:12,0035381 Dwm.exe 2432 RegQueryValue \n", "12 NaN 20:35:12,0035476 Dwm.exe 2432 RegCloseKey \n", "13 NaN 20:35:12,0035560 Dwm.exe 2432 RegOpenKey \n", "14 NaN 20:35:12,0035633 Dwm.exe 2432 RegQueryValue \n", "15 NaN 20:35:12,0035721 Dwm.exe 2432 RegCloseKey \n", "16 NaN 20:35:12,0035801 Dwm.exe 2432 RegOpenKey \n", "17 NaN 20:35:12,0035877 Dwm.exe 2432 RegQueryValue \n", "18 NaN 20:35:12,0035961 Dwm.exe 2432 RegCloseKey \n", "19 NaN 20:35:12,0036917 Dwm.exe 2432 RegQueryKey \n", "20 NaN 20:35:12,0037011 Dwm.exe 2432 RegOpenKey \n", "21 NaN 20:35:12,0037106 Dwm.exe 2432 RegOpenKey \n", "22 NaN 20:35:12,0037216 Dwm.exe 2432 RegQueryValue \n", "23 NaN 20:35:12,0037336 Dwm.exe 2432 RegQueryValue \n", "24 NaN 20:35:12,0037420 Dwm.exe 2432 RegQueryValue \n", "25 NaN 20:35:12,0037504 Dwm.exe 2432 RegCloseKey \n", "26 NaN 20:35:12,0037606 Dwm.exe 2432 RegOpenKey \n", "27 NaN 20:35:12,0037686 Dwm.exe 2432 RegQueryValue \n", "28 NaN 20:35:12,0037770 Dwm.exe 2432 RegCloseKey \n", "29 NaN 20:35:12,0037861 Dwm.exe 2432 RegOpenKey \n", "... ... ... ... ... ... \n", "75083 NaN 20:35:18,4282281 Dwm.exe 2432 RegCloseKey \n", "75084 NaN 20:35:18,4282412 Dwm.exe 2432 RegOpenKey \n", "75085 NaN 20:35:18,4282536 Dwm.exe 2432 RegQueryValue \n", "75086 NaN 20:35:18,4282675 Dwm.exe 2432 RegCloseKey \n", "75087 NaN 20:35:18,4282802 Dwm.exe 2432 RegOpenKey \n", "75088 NaN 20:35:18,4282926 Dwm.exe 2432 RegQueryValue \n", "75089 NaN 20:35:18,4283068 Dwm.exe 2432 RegCloseKey \n", "75090 NaN 20:35:18,4283830 Dwm.exe 2432 RegQueryKey \n", "75091 NaN 20:35:18,4283969 Dwm.exe 2432 RegOpenKey \n", "75092 NaN 20:35:18,4284119 Dwm.exe 2432 RegOpenKey \n", "75093 NaN 20:35:18,4284283 Dwm.exe 2432 RegQueryValue \n", "75094 NaN 20:35:18,4284472 Dwm.exe 2432 RegQueryValue \n", "75095 NaN 20:35:18,4284585 Dwm.exe 2432 RegQueryValue \n", "75096 NaN 20:35:18,4284713 Dwm.exe 2432 RegCloseKey \n", "75097 NaN 20:35:18,4284884 Dwm.exe 2432 RegOpenKey \n", "75098 NaN 20:35:18,4285019 Dwm.exe 2432 RegQueryValue \n", "75099 NaN 20:35:18,4285161 Dwm.exe 2432 RegCloseKey \n", "75100 NaN 20:35:18,4285304 Dwm.exe 2432 RegOpenKey \n", "75101 NaN 20:35:18,4285428 Dwm.exe 2432 RegQueryValue \n", "75102 NaN 20:35:18,4285595 Dwm.exe 2432 RegOpenKey \n", "75103 NaN 20:35:18,4285734 Dwm.exe 2432 RegOpenKey \n", "75104 NaN 20:35:18,4285902 Dwm.exe 2432 RegCloseKey \n", "75105 NaN 20:35:18,4286007 Dwm.exe 2432 RegQueryValue \n", "75106 NaN 20:35:18,4286223 Dwm.exe 2432 RegCloseKey \n", "75107 NaN 20:35:18,4286354 Dwm.exe 2432 RegOpenKey \n", "75108 NaN 20:35:18,4286481 Dwm.exe 2432 RegQueryValue \n", "75109 NaN 20:35:18,4286624 Dwm.exe 2432 RegCloseKey \n", "75110 NaN 20:35:18,4286748 Dwm.exe 2432 RegOpenKey \n", "75111 NaN 20:35:18,4286879 Dwm.exe 2432 RegQueryValue \n", "75112 NaN 20:35:18,4287014 Dwm.exe 2432 RegCloseKey \n", "\n", " Path Result \\\n", "0 HKLM\\Hardware\\DeviceMap\\VIDEO SUCCESS \n", "1 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\MaxObjectNumber SUCCESS \n", "2 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO SUCCESS \n", "3 HKLM\\Hardware\\DeviceMap\\Video SUCCESS \n", "4 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video4 SUCCESS \n", "5 HKLM\\System\\CurrentControlSet\\CONTROL\\VIDEO\\{7... REPARSE \n", "6 HKLM\\System\\CurrentControlSet\\CONTROL\\VIDEO\\{7... SUCCESS \n", "7 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO SUCCESS \n", "8 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... NAME NOT FOUND \n", "9 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... SUCCESS \n", "10 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "11 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "12 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "13 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "14 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "15 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "16 HKLM\\Hardware\\DeviceMap\\Video SUCCESS \n", "17 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video4 SUCCESS \n", "18 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO SUCCESS \n", "19 HKLM SUCCESS \n", "20 HKLM\\System\\CurrentControlSet\\Control\\Video\\{7... REPARSE \n", "21 HKLM\\System\\CurrentControlSet\\Control\\Video\\{7... SUCCESS \n", "22 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... SUCCESS \n", "23 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... BUFFER OVERFLOW \n", "24 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... SUCCESS \n", "25 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... SUCCESS \n", "26 HKLM\\Hardware\\DeviceMap\\VIDEO SUCCESS \n", "27 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\MaxObjectNumber SUCCESS \n", "28 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO SUCCESS \n", "29 HKLM\\Hardware\\DeviceMap\\Video SUCCESS \n", "... ... ... \n", "75083 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75084 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75085 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75086 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75087 HKLM\\Hardware\\DeviceMap\\Video SUCCESS \n", "75088 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video4 SUCCESS \n", "75089 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO SUCCESS \n", "75090 HKLM SUCCESS \n", "75091 HKLM\\System\\CurrentControlSet\\Control\\Video\\{7... REPARSE \n", "75092 HKLM\\System\\CurrentControlSet\\Control\\Video\\{7... SUCCESS \n", "75093 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... SUCCESS \n", "75094 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... BUFFER OVERFLOW \n", "75095 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... SUCCESS \n", "75096 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... SUCCESS \n", "75097 HKLM\\Hardware\\DeviceMap\\VIDEO SUCCESS \n", "75098 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\MaxObjectNumber SUCCESS \n", "75099 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO SUCCESS \n", "75100 HKLM\\Hardware\\DeviceMap\\Video SUCCESS \n", "75101 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video5 SUCCESS \n", "75102 HKLM\\System\\CurrentControlSet\\CONTROL\\VIDEO\\{7... REPARSE \n", "75103 HKLM\\System\\CurrentControlSet\\CONTROL\\VIDEO\\{7... SUCCESS \n", "75104 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO SUCCESS \n", "75105 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... NAME NOT FOUND \n", "75106 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... SUCCESS \n", "75107 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75108 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75109 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75110 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75111 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75112 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "\n", " Duration Detail \\\n", "0 5.900000e-06 Desired Access: Read, Maximum Allowed \n", "1 2.200000e-06 Type: REG_DWORD, Length: 4, Data: 10 \n", "2 7.000000e-07 NaN \n", "3 1.800000e-06 Desired Access: Read \n", "4 1.900000e-06 Type: REG_SZ, Length: 202, Data: \\Registry\\Mac... \n", "5 4.800000e-06 Desired Access: Read \n", "6 3.600000e-06 Desired Access: Read \n", "7 7.000000e-07 NaN \n", "8 7.700000e-06 Length: 52 \n", "9 7.000000e-07 NaN \n", "10 2.200000e-06 Desired Access: Read \n", "11 1.500000e-06 Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN... \n", "12 8.000000e-07 NaN \n", "13 1.500000e-06 Desired Access: Read \n", "14 1.100000e-06 Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN... \n", "15 7.000000e-07 NaN \n", "16 1.800000e-06 Desired Access: Read \n", "17 1.100000e-06 Type: REG_SZ, Length: 202, Data: \\Registry\\Mac... \n", "18 8.000000e-07 NaN \n", "19 1.100000e-06 Query: HandleTags, HandleTags: 0x0 \n", "20 3.700000e-06 Desired Access: Query Value \n", "21 3.300000e-06 Desired Access: Query Value \n", "22 6.200000e-06 Type: REG_BINARY, Length: 4, Data: 00 00 00 40 \n", "23 1.500000e-06 Length: 144 \n", "24 1.400000e-06 Type: REG_MULTI_SZ, Length: 142, Data: igdumdi... \n", "25 7.000000e-07 NaN \n", "26 1.800000e-06 Desired Access: Read, Maximum Allowed \n", "27 1.100000e-06 Type: REG_DWORD, Length: 4, Data: 10 \n", "28 7.000000e-07 NaN \n", "29 1.500000e-06 Desired Access: Read \n", "... ... ... \n", "75083 1.100000e-06 NaN \n", "75084 2.200000e-06 Desired Access: Read \n", "75085 1.500000e-06 Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN... \n", "75086 1.000000e-06 NaN \n", "75087 2.900000e-06 Desired Access: Read \n", "75088 1.800000e-06 Type: REG_SZ, Length: 202, Data: \\Registry\\Mac... \n", "75089 8.000000e-07 NaN \n", "75090 1.500000e-06 Query: HandleTags, HandleTags: 0x0 \n", "75091 5.500000e-06 Desired Access: Query Value \n", "75092 4.700000e-06 Desired Access: Query Value \n", "75093 9.400000e-06 Type: REG_BINARY, Length: 4, Data: 00 00 00 40 \n", "75094 2.200000e-06 Length: 144 \n", "75095 2.200000e-06 Type: REG_MULTI_SZ, Length: 142, Data: igdumdi... \n", "75096 1.400000e-06 NaN \n", "75097 3.300000e-06 Desired Access: Read, Maximum Allowed \n", "75098 1.500000e-06 Type: REG_DWORD, Length: 4, Data: 10 \n", "75099 1.100000e-06 NaN \n", "75100 2.500000e-06 Desired Access: Read \n", "75101 1.800000e-06 Type: REG_SZ, Length: 202, Data: \\Registry\\Mac... \n", "75102 4.000000e-06 Desired Access: Read \n", "75103 4.000000e-06 Desired Access: Read \n", "75104 1.100000e-06 NaN \n", "75105 9.900000e-06 Length: 52 \n", "75106 1.000000e-06 NaN \n", "75107 2.200000e-06 Desired Access: Read \n", "75108 1.900000e-06 Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN... \n", "75109 1.100000e-06 NaN \n", "75110 2.200000e-06 Desired Access: Read \n", "75111 1.400000e-06 Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN... \n", "75112 1.100000e-06 NaN \n", "\n", " New Column \n", "0 RegOpenKe \n", "1 RegQueryValu \n", "2 RegCloseKe \n", "3 RegOpenKe \n", "4 RegQueryValu \n", "5 RegOpenKe \n", "6 RegOpenKe \n", "7 RegCloseKe \n", "8 RegQueryValu \n", "9 RegCloseKe \n", "10 RegOpenKe \n", "11 RegQueryValu \n", "12 RegCloseKe \n", "13 RegOpenKe \n", "14 RegQueryValu \n", "15 RegCloseKe \n", "16 RegOpenKe \n", "17 RegQueryValu \n", "18 RegCloseKe \n", "19 RegQueryKe \n", "20 RegOpenKe \n", "21 RegOpenKe \n", "22 RegQueryValu \n", "23 RegQueryValu \n", "24 RegQueryValu \n", "25 RegCloseKe \n", "26 RegOpenKe \n", "27 RegQueryValu \n", "28 RegCloseKe \n", "29 RegOpenKe \n", "... ... \n", "75083 RegCloseKe \n", "75084 RegOpenKe \n", "75085 RegQueryValu \n", "75086 RegCloseKe \n", "75087 RegOpenKe \n", "75088 RegQueryValu \n", "75089 RegCloseKe \n", "75090 RegQueryKe \n", "75091 RegOpenKe \n", "75092 RegOpenKe \n", "75093 RegQueryValu \n", "75094 RegQueryValu \n", "75095 RegQueryValu \n", "75096 RegCloseKe \n", "75097 RegOpenKe \n", "75098 RegQueryValu \n", "75099 RegCloseKe \n", "75100 RegOpenKe \n", "75101 RegQueryValu \n", "75102 RegOpenKe \n", "75103 RegOpenKe \n", "75104 RegCloseKe \n", "75105 RegQueryValu \n", "75106 RegCloseKe \n", "75107 RegOpenKe \n", "75108 RegQueryValu \n", "75109 RegCloseKe \n", "75110 RegOpenKe \n", "75111 RegQueryValu \n", "75112 RegCloseKe \n", "\n", "[75113 rows x 10 columns]" ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "code", "execution_count": 74, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "Index([u'Sequence', u'Time of Day', u'Process Name', u'PID', u'Operation',\n", " u'Path', u'Result', u'Duration', u'Detail', u'New Column'],\n", " dtype='object')" ] }, "execution_count": 74, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.columns" ] }, { "cell_type": "code", "execution_count": 75, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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SequenceTime of DayProcess NamePIDOperationPathResultDurationDetail
0NaN20:35:12,0034072Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VIDEOSUCCESS5.900000e-06Desired Access: Read, Maximum Allowed
1NaN20:35:12,0034247Dwm.exe2432RegQueryValueHKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\MaxObjectNumberSUCCESS2.200000e-06Type: REG_DWORD, Length: 4, Data: 10
2NaN20:35:12,0034379Dwm.exe2432RegCloseKeyHKLM\\HARDWARE\\DEVICEMAP\\VIDEOSUCCESS7.000000e-07NaN
3NaN20:35:12,0034510Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VideoSUCCESS1.800000e-06Desired Access: Read
4NaN20:35:12,0034597Dwm.exe2432RegQueryValueHKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video4SUCCESS1.900000e-06Type: REG_SZ, Length: 202, Data: \\Registry\\Mac...
5NaN20:35:12,0034721Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\CONTROL\\VIDEO\\{7...REPARSE4.800000e-06Desired Access: Read
6NaN20:35:12,0034835Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\CONTROL\\VIDEO\\{7...SUCCESS3.600000e-06Desired Access: Read
7NaN20:35:12,0034955Dwm.exe2432RegCloseKeyHKLM\\HARDWARE\\DEVICEMAP\\VIDEOSUCCESS7.000000e-07NaN
8NaN20:35:12,0035031Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...NAME NOT FOUND7.700000e-06Length: 52
9NaN20:35:12,0035181Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...SUCCESS7.000000e-07NaN
10NaN20:35:12,0035287Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS2.200000e-06Desired Access: Read
11NaN20:35:12,0035381Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.500000e-06Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN...
12NaN20:35:12,0035476Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS8.000000e-07NaN
13NaN20:35:12,0035560Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.500000e-06Desired Access: Read
14NaN20:35:12,0035633Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.100000e-06Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN...
15NaN20:35:12,0035721Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS7.000000e-07NaN
16NaN20:35:12,0035801Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VideoSUCCESS1.800000e-06Desired Access: Read
17NaN20:35:12,0035877Dwm.exe2432RegQueryValueHKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video4SUCCESS1.100000e-06Type: REG_SZ, Length: 202, Data: \\Registry\\Mac...
18NaN20:35:12,0035961Dwm.exe2432RegCloseKeyHKLM\\HARDWARE\\DEVICEMAP\\VIDEOSUCCESS8.000000e-07NaN
19NaN20:35:12,0036917Dwm.exe2432RegQueryKeyHKLMSUCCESS1.100000e-06Query: HandleTags, HandleTags: 0x0
20NaN20:35:12,0037011Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Control\\Video\\{7...REPARSE3.700000e-06Desired Access: Query Value
21NaN20:35:12,0037106Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Control\\Video\\{7...SUCCESS3.300000e-06Desired Access: Query Value
22NaN20:35:12,0037216Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...SUCCESS6.200000e-06Type: REG_BINARY, Length: 4, Data: 00 00 00 40
23NaN20:35:12,0037336Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...BUFFER OVERFLOW1.500000e-06Length: 144
24NaN20:35:12,0037420Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...SUCCESS1.400000e-06Type: REG_MULTI_SZ, Length: 142, Data: igdumdi...
25NaN20:35:12,0037504Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...SUCCESS7.000000e-07NaN
26NaN20:35:12,0037606Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VIDEOSUCCESS1.800000e-06Desired Access: Read, Maximum Allowed
27NaN20:35:12,0037686Dwm.exe2432RegQueryValueHKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\MaxObjectNumberSUCCESS1.100000e-06Type: REG_DWORD, Length: 4, Data: 10
28NaN20:35:12,0037770Dwm.exe2432RegCloseKeyHKLM\\HARDWARE\\DEVICEMAP\\VIDEOSUCCESS7.000000e-07NaN
29NaN20:35:12,0037861Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VideoSUCCESS1.500000e-06Desired Access: Read
..............................
75083NaN20:35:18,4282281Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.100000e-06NaN
75084NaN20:35:18,4282412Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS2.200000e-06Desired Access: Read
75085NaN20:35:18,4282536Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.500000e-06Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN...
75086NaN20:35:18,4282675Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.000000e-06NaN
75087NaN20:35:18,4282802Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VideoSUCCESS2.900000e-06Desired Access: Read
75088NaN20:35:18,4282926Dwm.exe2432RegQueryValueHKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video4SUCCESS1.800000e-06Type: REG_SZ, Length: 202, Data: \\Registry\\Mac...
75089NaN20:35:18,4283068Dwm.exe2432RegCloseKeyHKLM\\HARDWARE\\DEVICEMAP\\VIDEOSUCCESS8.000000e-07NaN
75090NaN20:35:18,4283830Dwm.exe2432RegQueryKeyHKLMSUCCESS1.500000e-06Query: HandleTags, HandleTags: 0x0
75091NaN20:35:18,4283969Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Control\\Video\\{7...REPARSE5.500000e-06Desired Access: Query Value
75092NaN20:35:18,4284119Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Control\\Video\\{7...SUCCESS4.700000e-06Desired Access: Query Value
75093NaN20:35:18,4284283Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...SUCCESS9.400000e-06Type: REG_BINARY, Length: 4, Data: 00 00 00 40
75094NaN20:35:18,4284472Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...BUFFER OVERFLOW2.200000e-06Length: 144
75095NaN20:35:18,4284585Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...SUCCESS2.200000e-06Type: REG_MULTI_SZ, Length: 142, Data: igdumdi...
75096NaN20:35:18,4284713Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...SUCCESS1.400000e-06NaN
75097NaN20:35:18,4284884Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VIDEOSUCCESS3.300000e-06Desired Access: Read, Maximum Allowed
75098NaN20:35:18,4285019Dwm.exe2432RegQueryValueHKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\MaxObjectNumberSUCCESS1.500000e-06Type: REG_DWORD, Length: 4, Data: 10
75099NaN20:35:18,4285161Dwm.exe2432RegCloseKeyHKLM\\HARDWARE\\DEVICEMAP\\VIDEOSUCCESS1.100000e-06NaN
75100NaN20:35:18,4285304Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VideoSUCCESS2.500000e-06Desired Access: Read
75101NaN20:35:18,4285428Dwm.exe2432RegQueryValueHKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video5SUCCESS1.800000e-06Type: REG_SZ, Length: 202, Data: \\Registry\\Mac...
75102NaN20:35:18,4285595Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\CONTROL\\VIDEO\\{7...REPARSE4.000000e-06Desired Access: Read
75103NaN20:35:18,4285734Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\CONTROL\\VIDEO\\{7...SUCCESS4.000000e-06Desired Access: Read
75104NaN20:35:18,4285902Dwm.exe2432RegCloseKeyHKLM\\HARDWARE\\DEVICEMAP\\VIDEOSUCCESS1.100000e-06NaN
75105NaN20:35:18,4286007Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...NAME NOT FOUND9.900000e-06Length: 52
75106NaN20:35:18,4286223Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4...SUCCESS1.000000e-06NaN
75107NaN20:35:18,4286354Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS2.200000e-06Desired Access: Read
75108NaN20:35:18,4286481Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.900000e-06Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN...
75109NaN20:35:18,4286624Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.100000e-06NaN
75110NaN20:35:18,4286748Dwm.exe2432RegOpenKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS2.200000e-06Desired Access: Read
75111NaN20:35:18,4286879Dwm.exe2432RegQueryValueHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.400000e-06Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN...
75112NaN20:35:18,4287014Dwm.exe2432RegCloseKeyHKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808...SUCCESS1.100000e-06NaN
\n", "

75113 rows × 9 columns

\n", "
" ], "text/plain": [ " Sequence Time of Day Process Name PID Operation \\\n", "0 NaN 20:35:12,0034072 Dwm.exe 2432 RegOpenKey \n", "1 NaN 20:35:12,0034247 Dwm.exe 2432 RegQueryValue \n", "2 NaN 20:35:12,0034379 Dwm.exe 2432 RegCloseKey \n", "3 NaN 20:35:12,0034510 Dwm.exe 2432 RegOpenKey \n", "4 NaN 20:35:12,0034597 Dwm.exe 2432 RegQueryValue \n", "5 NaN 20:35:12,0034721 Dwm.exe 2432 RegOpenKey \n", "6 NaN 20:35:12,0034835 Dwm.exe 2432 RegOpenKey \n", "7 NaN 20:35:12,0034955 Dwm.exe 2432 RegCloseKey \n", "8 NaN 20:35:12,0035031 Dwm.exe 2432 RegQueryValue \n", "9 NaN 20:35:12,0035181 Dwm.exe 2432 RegCloseKey \n", "10 NaN 20:35:12,0035287 Dwm.exe 2432 RegOpenKey \n", "11 NaN 20:35:12,0035381 Dwm.exe 2432 RegQueryValue \n", "12 NaN 20:35:12,0035476 Dwm.exe 2432 RegCloseKey \n", "13 NaN 20:35:12,0035560 Dwm.exe 2432 RegOpenKey \n", "14 NaN 20:35:12,0035633 Dwm.exe 2432 RegQueryValue \n", "15 NaN 20:35:12,0035721 Dwm.exe 2432 RegCloseKey \n", "16 NaN 20:35:12,0035801 Dwm.exe 2432 RegOpenKey \n", "17 NaN 20:35:12,0035877 Dwm.exe 2432 RegQueryValue \n", "18 NaN 20:35:12,0035961 Dwm.exe 2432 RegCloseKey \n", "19 NaN 20:35:12,0036917 Dwm.exe 2432 RegQueryKey \n", "20 NaN 20:35:12,0037011 Dwm.exe 2432 RegOpenKey \n", "21 NaN 20:35:12,0037106 Dwm.exe 2432 RegOpenKey \n", "22 NaN 20:35:12,0037216 Dwm.exe 2432 RegQueryValue \n", "23 NaN 20:35:12,0037336 Dwm.exe 2432 RegQueryValue \n", "24 NaN 20:35:12,0037420 Dwm.exe 2432 RegQueryValue \n", "25 NaN 20:35:12,0037504 Dwm.exe 2432 RegCloseKey \n", "26 NaN 20:35:12,0037606 Dwm.exe 2432 RegOpenKey \n", "27 NaN 20:35:12,0037686 Dwm.exe 2432 RegQueryValue \n", "28 NaN 20:35:12,0037770 Dwm.exe 2432 RegCloseKey \n", "29 NaN 20:35:12,0037861 Dwm.exe 2432 RegOpenKey \n", "... ... ... ... ... ... \n", "75083 NaN 20:35:18,4282281 Dwm.exe 2432 RegCloseKey \n", "75084 NaN 20:35:18,4282412 Dwm.exe 2432 RegOpenKey \n", "75085 NaN 20:35:18,4282536 Dwm.exe 2432 RegQueryValue \n", "75086 NaN 20:35:18,4282675 Dwm.exe 2432 RegCloseKey \n", "75087 NaN 20:35:18,4282802 Dwm.exe 2432 RegOpenKey \n", "75088 NaN 20:35:18,4282926 Dwm.exe 2432 RegQueryValue \n", "75089 NaN 20:35:18,4283068 Dwm.exe 2432 RegCloseKey \n", "75090 NaN 20:35:18,4283830 Dwm.exe 2432 RegQueryKey \n", "75091 NaN 20:35:18,4283969 Dwm.exe 2432 RegOpenKey \n", "75092 NaN 20:35:18,4284119 Dwm.exe 2432 RegOpenKey \n", "75093 NaN 20:35:18,4284283 Dwm.exe 2432 RegQueryValue \n", "75094 NaN 20:35:18,4284472 Dwm.exe 2432 RegQueryValue \n", "75095 NaN 20:35:18,4284585 Dwm.exe 2432 RegQueryValue \n", "75096 NaN 20:35:18,4284713 Dwm.exe 2432 RegCloseKey \n", "75097 NaN 20:35:18,4284884 Dwm.exe 2432 RegOpenKey \n", "75098 NaN 20:35:18,4285019 Dwm.exe 2432 RegQueryValue \n", "75099 NaN 20:35:18,4285161 Dwm.exe 2432 RegCloseKey \n", "75100 NaN 20:35:18,4285304 Dwm.exe 2432 RegOpenKey \n", "75101 NaN 20:35:18,4285428 Dwm.exe 2432 RegQueryValue \n", "75102 NaN 20:35:18,4285595 Dwm.exe 2432 RegOpenKey \n", "75103 NaN 20:35:18,4285734 Dwm.exe 2432 RegOpenKey \n", "75104 NaN 20:35:18,4285902 Dwm.exe 2432 RegCloseKey \n", "75105 NaN 20:35:18,4286007 Dwm.exe 2432 RegQueryValue \n", "75106 NaN 20:35:18,4286223 Dwm.exe 2432 RegCloseKey \n", "75107 NaN 20:35:18,4286354 Dwm.exe 2432 RegOpenKey \n", "75108 NaN 20:35:18,4286481 Dwm.exe 2432 RegQueryValue \n", "75109 NaN 20:35:18,4286624 Dwm.exe 2432 RegCloseKey \n", "75110 NaN 20:35:18,4286748 Dwm.exe 2432 RegOpenKey \n", "75111 NaN 20:35:18,4286879 Dwm.exe 2432 RegQueryValue \n", "75112 NaN 20:35:18,4287014 Dwm.exe 2432 RegCloseKey \n", "\n", " Path Result \\\n", "0 HKLM\\Hardware\\DeviceMap\\VIDEO SUCCESS \n", "1 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\MaxObjectNumber SUCCESS \n", "2 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO SUCCESS \n", "3 HKLM\\Hardware\\DeviceMap\\Video SUCCESS \n", "4 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video4 SUCCESS \n", "5 HKLM\\System\\CurrentControlSet\\CONTROL\\VIDEO\\{7... REPARSE \n", "6 HKLM\\System\\CurrentControlSet\\CONTROL\\VIDEO\\{7... SUCCESS \n", "7 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO SUCCESS \n", "8 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... NAME NOT FOUND \n", "9 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... SUCCESS \n", "10 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "11 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "12 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "13 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "14 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "15 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "16 HKLM\\Hardware\\DeviceMap\\Video SUCCESS \n", "17 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video4 SUCCESS \n", "18 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO SUCCESS \n", "19 HKLM SUCCESS \n", "20 HKLM\\System\\CurrentControlSet\\Control\\Video\\{7... REPARSE \n", "21 HKLM\\System\\CurrentControlSet\\Control\\Video\\{7... SUCCESS \n", "22 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... SUCCESS \n", "23 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... BUFFER OVERFLOW \n", "24 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... SUCCESS \n", "25 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... SUCCESS \n", "26 HKLM\\Hardware\\DeviceMap\\VIDEO SUCCESS \n", "27 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\MaxObjectNumber SUCCESS \n", "28 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO SUCCESS \n", "29 HKLM\\Hardware\\DeviceMap\\Video SUCCESS \n", "... ... ... \n", "75083 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75084 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75085 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75086 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75087 HKLM\\Hardware\\DeviceMap\\Video SUCCESS \n", "75088 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video4 SUCCESS \n", "75089 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO SUCCESS \n", "75090 HKLM SUCCESS \n", "75091 HKLM\\System\\CurrentControlSet\\Control\\Video\\{7... REPARSE \n", "75092 HKLM\\System\\CurrentControlSet\\Control\\Video\\{7... SUCCESS \n", "75093 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... SUCCESS \n", "75094 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... BUFFER OVERFLOW \n", "75095 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... SUCCESS \n", "75096 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... SUCCESS \n", "75097 HKLM\\Hardware\\DeviceMap\\VIDEO SUCCESS \n", "75098 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\MaxObjectNumber SUCCESS \n", "75099 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO SUCCESS \n", "75100 HKLM\\Hardware\\DeviceMap\\Video SUCCESS \n", "75101 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video5 SUCCESS \n", "75102 HKLM\\System\\CurrentControlSet\\CONTROL\\VIDEO\\{7... REPARSE \n", "75103 HKLM\\System\\CurrentControlSet\\CONTROL\\VIDEO\\{7... SUCCESS \n", "75104 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO SUCCESS \n", "75105 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... NAME NOT FOUND \n", "75106 HKLM\\System\\CurrentControlSet\\Control\\CLASS\\{4... SUCCESS \n", "75107 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75108 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75109 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75110 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75111 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "75112 HKLM\\System\\CurrentControlSet\\Enum\\PCI\\VEN_808... SUCCESS \n", "\n", " Duration Detail \n", "0 5.900000e-06 Desired Access: Read, Maximum Allowed \n", "1 2.200000e-06 Type: REG_DWORD, Length: 4, Data: 10 \n", "2 7.000000e-07 NaN \n", "3 1.800000e-06 Desired Access: Read \n", "4 1.900000e-06 Type: REG_SZ, Length: 202, Data: \\Registry\\Mac... \n", "5 4.800000e-06 Desired Access: Read \n", "6 3.600000e-06 Desired Access: Read \n", "7 7.000000e-07 NaN \n", "8 7.700000e-06 Length: 52 \n", "9 7.000000e-07 NaN \n", "10 2.200000e-06 Desired Access: Read \n", "11 1.500000e-06 Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN... \n", "12 8.000000e-07 NaN \n", "13 1.500000e-06 Desired Access: Read \n", "14 1.100000e-06 Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN... \n", "15 7.000000e-07 NaN \n", "16 1.800000e-06 Desired Access: Read \n", "17 1.100000e-06 Type: REG_SZ, Length: 202, Data: \\Registry\\Mac... \n", "18 8.000000e-07 NaN \n", "19 1.100000e-06 Query: HandleTags, HandleTags: 0x0 \n", "20 3.700000e-06 Desired Access: Query Value \n", "21 3.300000e-06 Desired Access: Query Value \n", "22 6.200000e-06 Type: REG_BINARY, Length: 4, Data: 00 00 00 40 \n", "23 1.500000e-06 Length: 144 \n", "24 1.400000e-06 Type: REG_MULTI_SZ, Length: 142, Data: igdumdi... \n", "25 7.000000e-07 NaN \n", "26 1.800000e-06 Desired Access: Read, Maximum Allowed \n", "27 1.100000e-06 Type: REG_DWORD, Length: 4, Data: 10 \n", "28 7.000000e-07 NaN \n", "29 1.500000e-06 Desired Access: Read \n", "... ... ... \n", "75083 1.100000e-06 NaN \n", "75084 2.200000e-06 Desired Access: Read \n", "75085 1.500000e-06 Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN... \n", "75086 1.000000e-06 NaN \n", "75087 2.900000e-06 Desired Access: Read \n", "75088 1.800000e-06 Type: REG_SZ, Length: 202, Data: \\Registry\\Mac... \n", "75089 8.000000e-07 NaN \n", "75090 1.500000e-06 Query: HandleTags, HandleTags: 0x0 \n", "75091 5.500000e-06 Desired Access: Query Value \n", "75092 4.700000e-06 Desired Access: Query Value \n", "75093 9.400000e-06 Type: REG_BINARY, Length: 4, Data: 00 00 00 40 \n", "75094 2.200000e-06 Length: 144 \n", "75095 2.200000e-06 Type: REG_MULTI_SZ, Length: 142, Data: igdumdi... \n", "75096 1.400000e-06 NaN \n", "75097 3.300000e-06 Desired Access: Read, Maximum Allowed \n", "75098 1.500000e-06 Type: REG_DWORD, Length: 4, Data: 10 \n", "75099 1.100000e-06 NaN \n", "75100 2.500000e-06 Desired Access: Read \n", "75101 1.800000e-06 Type: REG_SZ, Length: 202, Data: \\Registry\\Mac... \n", "75102 4.000000e-06 Desired Access: Read \n", "75103 4.000000e-06 Desired Access: Read \n", "75104 1.100000e-06 NaN \n", "75105 9.900000e-06 Length: 52 \n", "75106 1.000000e-06 NaN \n", "75107 2.200000e-06 Desired Access: Read \n", "75108 1.900000e-06 Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN... \n", "75109 1.100000e-06 NaN \n", "75110 2.200000e-06 Desired Access: Read \n", "75111 1.400000e-06 Type: REG_MULTI_SZ, Length: 292, Data: PCI\\VEN... \n", "75112 1.100000e-06 NaN \n", "\n", "[75113 rows x 9 columns]" ] }, "execution_count": 75, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.drop('New Column', 1).head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Продемонстрируем работу с `pandas` на примере файла лога Sysinternals Process Monitor, записанного при попытке исполнить `import magic` без правильных телодвижений.\n", "\n", "Фильтр по колонке `df.ColName` или `df['ColName']`, `df[['ColName1', 'ColName2']]`, если их несколько.\n", "\n", "Фильтр по строкам `df[mask]`, где `mask` какое-то условие над столбцами, например, `df[~(df.ColName1 == 5) & (df.ColName2 < 5)]`.\n", "\n", "Уникальная выборка `df[condition][columns].unique()` — возвращает `array`.\n", "\n", "Сортировка по столбцу `df.sort_values('ColName', ascending=False)` (по умолчанию `ascending=False`); имена колонок и параметр ascending могут быть списками.\n", "\n", "Проверка на вхождение значения столбца в список `df.ColName.isin([values, ...])`.\n", "\n", "Группировка `df.groupby(column_or_columns)` возвращает `pandas.core.groupby.DataFrameGroupBy object`, для получения из него `DataFrame` надо использовать какую-нибудь агрегирующую функцию (по оставшимся несгруппированными столбцам), например\n", "\n", "* `.sum()`, `min()`, `max()`, `idxmin()`, `idxmax()`, `mean()`, `median()`\n", "* `.size()` (возвращает `pandas.core.series.Series`, преобразовать в `DataFrame` вызовом `to_frame('SizeColumnName')`)\n", "* `.count()` (число не NULL/nan записей)\n", "* `.agg({'ColumnName': ['min', 'max', 'mean', 'median', ...]})`\n", "\n", "Вызов `groupby` делает значения колонок группировки индексами строк. Их можно вернуть обратно в значения строк вызовом `.reset_index()`.\n", "\n", "Группы можно отфильтровать вызовом `df.groupby(columns).filter(callback)`, где `callback` принимает `DataFrame` для каждой группы и возвращает, включать ли ее в состав результирующего (несгруппированного!) `DataFrame`.\n", "\n", "Топы можно получать `df.nlargest(count, column)` или `.nsmallest`.\n", "\n", "Поменять местами строки и столбцы можно `.T`.\n", "\n", "Удалить строку `df.drop([index, ...])`\n", "\n", "Удалить столбец `df.drop([column, ...], axis=1)`" ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " a b\n", "0 1 2\n", "1 3 4" ] }, "execution_count": 180, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pandas.DataFrame({'a': [1, 3], 'b': [2, 4]})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "из базы данных SQL, из файла CSV." ] }, { "cell_type": "code", "execution_count": 157, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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IDTitleVolumeInfoSeriesPeriodicalAuthorYearEditionPublisherCity...MD5GenericVisibleLocatorLocalTimeAddedTimeLastModifiedCoverurlTagsIdentifierWODash
0106315Seismic Amplitude Interpretation DVDHilterman Fred J....4ECC43085AD2470DDE139CDA19515576ban02009-07-21 03:29:142013-12-30 19:27:10
1106316IOn SystemFour Reference Data...6D09557157049A450249789B67A21813ban02009-07-21 03:29:142013-12-30 19:27:10
2283888Библия Скорина...9E5D962AA7AAD600677843992580D4BEG:\\!upload\\!ADD\\Лингвистика\\Компаративистика\\И...02010-07-14 14:48:422014-09-04 03:01:57283000/9E5D962AA7AAD600677843992580D4BE-g.jpg
3198220Путь к реальности, или законы, управляющие Все...Роджер Пенроуз2007Институт компьютерных исследований, Регулярная......6D2A90A441094163C2F2DC00F287EE323B69975814637A6DF44EC9626B369589no1456630-Путь к реальности, или законы, управля...02010-02-18 15:16:042016-03-20 09:50:50198000/6d2a90a441094163c2f2dc00f287ee32.jpg9785939726184
4232910Новый ЗаветУдовский1892Университетская типогр....487313B08708B466D62A7AD2F4A15AF31534612-Чудовский Новый Завет=+chudovskij-NZ.pdf02010-02-18 15:16:042016-03-14 16:48:04232000/487313b08708b466d62a7ad2f4a15af3.jpg
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5 rows × 47 columns

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" ], "text/plain": [ " ID Title VolumeInfo \\\n", "0 106315 Seismic Amplitude Interpretation DVD \n", "1 106316 IOn SystemFour Reference Data \n", "2 283888 Библия Скорина \n", "3 198220 Путь к реальности, или законы, управляющие Все... \n", "4 232910 Новый Завет \n", "\n", " Series Periodical Author Year Edition \\\n", "0 Hilterman Fred J. \n", "1 \n", "2 \n", "3 Роджер Пенроуз 2007 \n", "4 Удовский 1892 \n", "\n", " Publisher City ... \\\n", "0 ... \n", "1 ... \n", "2 ... \n", "3 Институт компьютерных исследований, Регулярная... ... \n", "4 Университетская типогр. ... \n", "\n", " MD5 Generic Visible \\\n", "0 4ECC43085AD2470DDE139CDA19515576 ban \n", "1 6D09557157049A450249789B67A21813 ban \n", "2 9E5D962AA7AAD600677843992580D4BE \n", "3 6D2A90A441094163C2F2DC00F287EE32 3B69975814637A6DF44EC9626B369589 no \n", "4 487313B08708B466D62A7AD2F4A15AF3 \n", "\n", " Locator Local \\\n", "0 0 \n", "1 0 \n", "2 G:\\!upload\\!ADD\\Лингвистика\\Компаративистика\\И... 0 \n", "3 1456630-Путь к реальности, или законы, управля... 0 \n", "4 1534612-Чудовский Новый Завет=+chudovskij-NZ.pdf 0 \n", "\n", " TimeAdded TimeLastModified \\\n", "0 2009-07-21 03:29:14 2013-12-30 19:27:10 \n", "1 2009-07-21 03:29:14 2013-12-30 19:27:10 \n", "2 2010-07-14 14:48:42 2014-09-04 03:01:57 \n", "3 2010-02-18 15:16:04 2016-03-20 09:50:50 \n", "4 2010-02-18 15:16:04 2016-03-14 16:48:04 \n", "\n", " Coverurl Tags IdentifierWODash \n", "0 \n", "1 \n", "2 283000/9E5D962AA7AAD600677843992580D4BE-g.jpg \n", "3 198000/6d2a90a441094163c2f2dc00f287ee32.jpg 9785939726184 \n", "4 232000/487313b08708b466d62a7ad2f4a15af3.jpg \n", "\n", "[5 rows x 47 columns]" ] }, "execution_count": 157, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pymysql\n", "conn = pymysql.connect(\n", " host='localhost', user='root', password='toor', db='bookwarrior',\n", " charset='utf8mb4', cursorclass=pymysql.cursors.DictCursor)\n", "df = pandas.read_sql('SELECT * FROM updated WHERE Filesize > 1000000000', conn)\n", "df.head()" ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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SequenceTime of DayProcess NamePIDOperationPathResultDurationDetail
0NaN20:35:12,0034072Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VIDEOSUCCESS5.900000e-06Desired Access: Read, Maximum Allowed
1NaN20:35:12,0034247Dwm.exe2432RegQueryValueHKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\MaxObjectNumberSUCCESS2.200000e-06Type: REG_DWORD, Length: 4, Data: 10
2NaN20:35:12,0034379Dwm.exe2432RegCloseKeyHKLM\\HARDWARE\\DEVICEMAP\\VIDEOSUCCESS7.000000e-07NaN
3NaN20:35:12,0034510Dwm.exe2432RegOpenKeyHKLM\\Hardware\\DeviceMap\\VideoSUCCESS1.800000e-06Desired Access: Read
4NaN20:35:12,0034597Dwm.exe2432RegQueryValueHKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video4SUCCESS1.900000e-06Type: REG_SZ, Length: 202, Data: \\Registry\\Mac...
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" ], "text/plain": [ " Sequence Time of Day Process Name PID Operation \\\n", "0 NaN 20:35:12,0034072 Dwm.exe 2432 RegOpenKey \n", "1 NaN 20:35:12,0034247 Dwm.exe 2432 RegQueryValue \n", "2 NaN 20:35:12,0034379 Dwm.exe 2432 RegCloseKey \n", "3 NaN 20:35:12,0034510 Dwm.exe 2432 RegOpenKey \n", "4 NaN 20:35:12,0034597 Dwm.exe 2432 RegQueryValue \n", "\n", " Path Result Duration \\\n", "0 HKLM\\Hardware\\DeviceMap\\VIDEO SUCCESS 5.900000e-06 \n", "1 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\MaxObjectNumber SUCCESS 2.200000e-06 \n", "2 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO SUCCESS 7.000000e-07 \n", "3 HKLM\\Hardware\\DeviceMap\\Video SUCCESS 1.800000e-06 \n", "4 HKLM\\HARDWARE\\DEVICEMAP\\VIDEO\\\\Device\\Video4 SUCCESS 1.900000e-06 \n", "\n", " Detail \n", "0 Desired Access: Read, Maximum Allowed \n", "1 Type: REG_DWORD, Length: 4, Data: 10 \n", "2 NaN \n", "3 Desired Access: Read \n", "4 Type: REG_SZ, Length: 202, Data: \\Registry\\Mac... " ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df = pandas.read_csv('C:\\\\Users\\\\User\\\\Desktop\\\\Logfile.CSV')\n", "df.head()" ] }, { "cell_type": "code", "execution_count": 115, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array(['Dwm.exe', 'svchost.exe', 'System', 'AIMP3.exe', 'Explorer.EXE',\n", " 'csrss.exe', 'DllHost.exe', 'taskhost.exe', 'services.exe',\n", " 'Miranda64.exe', 'VeraCrypt.exe', 'chrome.exe', 'python.exe',\n", " 'lsass.exe', 'wmiprvse.exe', 'taskmgr.exe'], dtype=object)" ] }, "execution_count": 115, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['Process Name'].unique()" ] }, { "cell_type": "code", "execution_count": 113, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "Dwm.exe 62750\n", "svchost.exe 5028\n", "chrome.exe 2357\n", "wmiprvse.exe 1961\n", "python.exe 1336\n", "csrss.exe 742\n", "VeraCrypt.exe 415\n", "Explorer.EXE 144\n", "System 103\n", "AIMP3.exe 86\n", "DllHost.exe 85\n", "taskmgr.exe 49\n", "taskhost.exe 19\n", "lsass.exe 16\n", "services.exe 16\n", "Miranda64.exe 6\n", "Name: Process Name, dtype: int64" ] }, "execution_count": 113, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['Process Name'].value_counts()" ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "collapsed": true }, "outputs": [], "source": [ "system = [\n", " 'Dwm.exe', 'svchost.exe', 'System', 'csrss.exe', 'DllHost.exe',\n", " 'taskhost.exe', 'services.exe', 'VeraCrypt.exe', 'lsass.exe', 'wmiprvse.exe',\n", " 'taskmgr.exe'\n", "]\n", "mask = ~df['Process Name'].isin(system)" ] }, { "cell_type": "code", "execution_count": 48, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 48, "metadata": {}, "output_type": "execute_result" } ], "source": [ "group = df[mask][['PID', 'Process Name', 'Operation', 'Duration']].groupby(['Process Name', 'PID'])\n", "group" ] }, { "cell_type": "code", "execution_count": 57, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "MultiIndex(levels=[[u'AIMP3.exe', u'Explorer.EXE', u'Miranda64.exe', u'chrome.exe', u'python.exe'], [2012, 2508, 3912, 4184, 4988, 7120]],\n", " labels=[[0, 1, 2, 3, 4, 4], [0, 1, 2, 3, 4, 5]],\n", " names=[u'Process Name', u'PID'])" ] }, "execution_count": 57, "metadata": {}, "output_type": "execute_result" } ], "source": [ "group.count().index" ] }, { "cell_type": "code", "execution_count": 54, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[86L, 144L, 6L, 2357L, 66L, 1270L]" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "group.size().tolist()" ] }, { "cell_type": "code", "execution_count": 140, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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Process NamePIDSize
0AIMP3.exe201286
1Explorer.EXE2508144
2Miranda64.exe39126
3chrome.exe41842357
4python.exe498866
5python.exe71201270
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" ], "text/plain": [ " Process Name PID Size\n", "0 AIMP3.exe 2012 86\n", "1 Explorer.EXE 2508 144\n", "2 Miranda64.exe 3912 6\n", "3 chrome.exe 4184 2357\n", "4 python.exe 4988 66\n", "5 python.exe 7120 1270" ] }, "execution_count": 140, "metadata": {}, "output_type": "execute_result" } ], "source": [ "group.size().to_frame('Size').reset_index()" ] }, { "cell_type": "code", "execution_count": 141, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Process NamePIDSize
3chrome.exe41842357
5python.exe71201270
1Explorer.EXE2508144
\n", "
" ], "text/plain": [ " Process Name PID Size\n", "3 chrome.exe 4184 2357\n", "5 python.exe 7120 1270\n", "1 Explorer.EXE 2508 144" ] }, "execution_count": 141, "metadata": {}, "output_type": "execute_result" } ], "source": [ "group.size().to_frame('Size').reset_index().nlargest(3, 'Size')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Аналогично `.nsmallest`" ] }, { "cell_type": "code", "execution_count": 142, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def fi(g):\n", " return len(g) < 100" ] }, { "cell_type": "code", "execution_count": 145, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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Process NameAIMP3.exeExplorer.EXEMiranda64.exechrome.exepython.exe
PID201225083912418449887120
Durationmin4.000000e-070.0000000.00.0000000.0000000.000000
mean2.125919e-040.0000200.00.0000020.0001900.000022
max1.662280e-020.0010620.00.0000350.0019880.003486
\n", "
" ], "text/plain": [ "Process Name AIMP3.exe Explorer.EXE Miranda64.exe chrome.exe python.exe \\\n", "PID 2012 2508 3912 4184 4988 \n", "Duration min 4.000000e-07 0.000000 0.0 0.000000 0.000000 \n", " mean 2.125919e-04 0.000020 0.0 0.000002 0.000190 \n", " max 1.662280e-02 0.001062 0.0 0.000035 0.001988 \n", "\n", "Process Name \n", "PID 7120 \n", "Duration min 0.000000 \n", " mean 0.000022 \n", " max 0.003486 " ] }, "execution_count": 145, "metadata": {}, "output_type": "execute_result" } ], "source": [ "group.agg({'Duration': ['min', 'mean', 'max']}).T" ] }, { "cell_type": "code", "execution_count": 150, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
OperationDuration
Process NamePID
chrome.exe418423572357
python.exe712012701270
Explorer.EXE2508144144
AIMP3.exe20128686
python.exe49886666
Miranda64.exe391266
\n", "
" ], "text/plain": [ " Operation Duration\n", "Process Name PID \n", "chrome.exe 4184 2357 2357\n", "python.exe 7120 1270 1270\n", "Explorer.EXE 2508 144 144\n", "AIMP3.exe 2012 86 86\n", "python.exe 4988 66 66\n", "Miranda64.exe 3912 6 6" ] }, "execution_count": 150, "metadata": {}, "output_type": "execute_result" } ], "source": [ "group.count().sort_values('Operation', ascending=False)" ] }, { "cell_type": "code", "execution_count": 151, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Duration
Process NamePID
AIMP3.exe20120.018283
Explorer.EXE25080.002945
Miranda64.exe39120.000000
chrome.exe41840.004051
python.exe49880.012529
71200.028555
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" ], "text/plain": [ " Duration\n", "Process Name PID \n", "AIMP3.exe 2012 0.018283\n", "Explorer.EXE 2508 0.002945\n", "Miranda64.exe 3912 0.000000\n", "chrome.exe 4184 0.004051\n", "python.exe 4988 0.012529\n", " 7120 0.028555" ] }, "execution_count": 151, "metadata": {}, "output_type": "execute_result" } ], "source": [ "group.sum()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "todo Уникальные строки сразу с несколькими колонками?" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "magic1.dll 105\n", "cygmagic-1.dll 105\n", "magic 60\n", "magic1 50\n", "magic.dll 50\n", "cygmagic-1 50\n", "magic.py 13\n", "magic.pyd 10\n", "magic.pyc 10\n", "magic.pyw 9\n", "history.sqlite-journal 5\n", "interactiveshell.py 3\n", " 3\n", "site-packages 1\n", "history.sqlite-wal 1\n", " 1\n", "Name: Result, dtype: int64" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "def extract_filename(rec):\n", " path = df.iloc[rec].Path\n", " return os.path.split(path)[1].lower()\n", "\n", "filtr = (df['Process Name'] == 'python.exe') & (df.Operation == 'IRP_MJ_CREATE') #& (df.Result == 'NAME NOT FOUND')\n", "gr = df[filtr].groupby(extract_filename)\n", "gr['Result'].agg(len).sort_values(ascending=False)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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ResultNAME INVALIDNAME NOT FOUNDPATH NOT FOUNDREPARSESUCCESS
cygmagic-1.dll0792420
magic1.dll0792420
magic0471210
cygmagic-10371210
magic.dll0371210
magic10371210
magic.pyd010000
magic.pyw09000
history.sqlite-wal01000
00100
<ipython-input-2-27b85091660b>30000
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" ], "text/plain": [ "Result NAME INVALID NAME NOT FOUND PATH NOT FOUND \\\n", "cygmagic-1.dll 0 79 24 \n", "magic1.dll 0 79 24 \n", "magic 0 47 12 \n", "cygmagic-1 0 37 12 \n", "magic.dll 0 37 12 \n", "magic1 0 37 12 \n", "magic.pyd 0 10 0 \n", "magic.pyw 0 9 0 \n", "history.sqlite-wal 0 1 0 \n", " 0 0 1 \n", " 3 0 0 \n", "\n", "Result REPARSE SUCCESS \n", "cygmagic-1.dll 2 0 \n", "magic1.dll 2 0 \n", "magic 1 0 \n", "cygmagic-1 1 0 \n", "magic.dll 1 0 \n", "magic1 1 0 \n", "magic.pyd 0 0 \n", "magic.pyw 0 0 \n", "history.sqlite-wal 0 0 \n", " 0 0 \n", " 0 0 " ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "report = df[filtr].groupby([extract_filename, 'Result']).size().unstack(fill_value=0)\n", "report[report['SUCCESS'] == 0].sort_values('NAME NOT FOUND', ascending=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Из этого отчета видно, что отчаяннее всего Python пытался найти файлы magic.dll, magic1.dll или cymagic-1.dll." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "todo\n", "\n", "JOIN\n", "Use .merge() to join Pandas dataframes. You need to provide which columns to join on (left_on and right_on), and join type: inner (default), left (corresponds to LEFT OUTER in SQL), right (RIGHT OUTER), or outer (FULL OUTER).\n", "\n", "UNION ALL and UNION\n", "Use pd.concat() to UNION ALL two dataframes:\n", "\n", "To deduplicate things (equivalent of UNION), you’d also have to add .drop_duplicates().\n", "\n", " df[mask].Column = new_value\n", " df.drop(df[mask].index)\n", " df.NewColumn = fn(df.OldColumn)" ] }, { "cell_type": "code", "execution_count": 192, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[(75113,)]\n" ] } ], "source": [ "import sqlite3\n", "\n", "con = sqlite3.connect(':memory:')\n", "con.text_factory = str\n", "df.to_sql('df', con)\n", "\n", "cur = con.cursor()\n", "print cur.execute('select count(*) from df').fetchall()\n", "con.close()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "todo" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [ { "ename": "NameError", "evalue": "name 'df' is not defined", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mto_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[1;31mNameError\u001b[0m: name 'df' is not defined" ] } ], "source": [ "df.to_csv() # (filename)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "pandas.read_excel('file.xlsx')\n", "pandas.read_excel(pandas.ExcelFile('file.xlsx'), 'Sheet1')\n", "df.to_excel('file.xlsx', sheet_name='Sheet 1')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "One-hot кодирование данных" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Populating the interactive namespace from numpy and matplotlib\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING: pylab import has clobbered these variables: ['isnan', 'random', 'datetime', 'save']\n", "`%matplotlib` prevents importing * from pylab and numpy\n" ] } ], "source": [ "import numpy" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " cls_0 cls_1 cls_3 cls_4 cls_5\n", "0 0 0 0 1 0\n", "1 0 0 0 0 1\n", "2 1 0 0 0 0\n", "3 0 0 1 0 0\n", "4 0 0 1 0 0\n", "5 0 0 1 0 0\n", "6 0 1 0 0 0\n", "7 0 0 1 0 0" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pandas.get_dummies(df['cls'], prefix='cls')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "При выводе `pandas` может обрезать слишком длинные строки в ячейке таблицы. Изменить это поведение:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "pandas.set_option('display.max_colwidth', -1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "todo Пример" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Иногда выборку данных над таблицей pandas быстрее записать в SQL, чем в вызовах методов `pandas`. На этот случай есть библиотека `pandasql` (входит в Anaconda)." ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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idlocalized_namenamerolesattacktype
01Anti-MageantimageCarry Escape Nukermeleeagility
12AxeaxeInitiator Durable Disabler Junglermeleestrength
23BanebaneSupport Disabler Nuker Durablerangeintelligence
34BloodseekerbloodseekerCarry Disabler Jungler Nuker Initiatormeleeagility
45Crystal Maidencrystal_maidenSupport Disabler Nuker Junglerrangeintelligence
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" ], "text/plain": [ " id localized_name name roles \\\n", "0 1 Anti-Mage antimage Carry Escape Nuker \n", "1 2 Axe axe Initiator Durable Disabler Jungler \n", "2 3 Bane bane Support Disabler Nuker Durable \n", "3 4 Bloodseeker bloodseeker Carry Disabler Jungler Nuker Initiator \n", "4 5 Crystal Maiden crystal_maiden Support Disabler Nuker Jungler \n", "\n", " attack type \n", "0 melee agility \n", "1 melee strength \n", "2 range intelligence \n", "3 melee agility \n", "4 range intelligence " ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from pandasql import sqldf\n", "\n", "df = pandas.read_csv(\"files/heroes++.csv\")\n", "df.head()" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
localized_nametype
53Dark Seerintelligence
82Ogre Magiintelligence
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" ], "text/plain": [ " localized_name type\n", "53 Dark Seer intelligence\n", "82 Ogre Magi intelligence" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[df.roles.map(lambda x: 'Disabler' in x) & (df.attack == 'melee') & (df.type == 'intelligence')][['localized_name', 'type']]" ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
localized_nametype
0Dark Seerintelligence
1Ogre Magiintelligence
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" ], "text/plain": [ " localized_name type\n", "0 Dark Seer intelligence\n", "1 Ogre Magi intelligence" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sqldf(\"SELECT localized_name, type FROM df WHERE attack='melee' AND roles LIKE '%Disabler%' AND type='intelligence'\", globals())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Базы данных" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Простейшей базой данных, поддерживающей SQL, является встраиваемая БД SQLite, использующая один файл для хранения реляционных таблиц. Ее можно использовать посредством встроенной библиотеки `sqlite3`. При этом никакого дополнительного ПО ставить не надо." ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "meta table\n", "CREATE TABLE meta(key LONGVARCHAR NOT NULL UNIQUE PRIMARY KEY,value LONGVARCHAR)\n", "\n", "sqlite_autoindex_meta_1 index\n", "None\n", "\n", "icon_mapping table\n", "CREATE TABLE icon_mapping(id INTEGER PRIMARY KEY,page_url LONGVARCHAR NOT NULL,icon_id INTEGER)\n", "\n", "icon_mapping_page_url_idx index\n", "CREATE INDEX icon_mapping_page_url_idx ON icon_mapping(page_url)\n", "\n", "icon_mapping_icon_id_idx index\n", "CREATE INDEX icon_mapping_icon_id_idx ON icon_mapping(icon_id)\n", "\n", "favicon_bitmaps table\n", "CREATE TABLE favicon_bitmaps(id INTEGER PRIMARY KEY,icon_id INTEGER NOT NULL,last_updated INTEGER DEFAULT 0,image_data BLOB,width INTEGER DEFAULT 0,height INTEGER DEFAULT 0, last_requested INTEGER DEFAULT 0)\n", "\n", "favicon_bitmaps_icon_id index\n", "CREATE INDEX favicon_bitmaps_icon_id ON favicon_bitmaps(icon_id)\n", "\n", "favicons table\n", "CREATE TABLE \"favicons\" (id INTEGER PRIMARY KEY,url LONGVARCHAR NOT NULL,icon_type INTEGER DEFAULT 1)\n", "\n", "favicons_url index\n", "CREATE INDEX favicons_url ON favicons(url)\n", "\n", "(('image_data', None, None, None, None, None, None),)\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAACIklEQVQ4jYWSS0iUURTHf/fe8RvH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\nE9P+UUTuqurmufl/AKTzsFGmvUNUAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import sqlite3, os, IPython\n", "\n", "db_filename = os.path.join(os.getenv('LOCALAPPDATA'), 'Google\\\\Chrome\\\\User Data\\\\Default\\\\Favicons - Copy')\n", "conn = sqlite3.connect(db_filename)\n", "cur = conn.cursor()\n", "for item in cur.execute('SELECT name, type, sql FROM sqlite_master').fetchall():\n", " print item[0], item[1]\n", " print item[2]\n", " print\n", " \n", "sql = 'SELECT image_data FROM favicon_bitmaps WHERE icon_id IN (SELECT id FROM favicons WHERE url LIKE ?)'\n", "png = str(cur.execute(sql, ['%google%']).fetchone()[0])\n", "print cur.description\n", "conn.close()\n", "IPython.display.display(IPython.display.Image(png))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Обратите внимание на то, как следует осуществлять подстановку аргументов в SQL-запрос во избежание SQL injection." ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(1, u'abc', 3.14)\n", "(2, u'def', 2.72)\n", "(3, u'ghi', 1.62)\n" ] } ], "source": [ "conn = sqlite3.connect(':memory:')\n", "cur = conn.cursor()\n", "cur.execute('''\n", "CREATE TABLE IF NOT EXISTS sample(\n", " id INTEGER PRIMARY KEY,\n", " s TEXT,\n", " z REAL\n", ")''')\n", "cur.executemany('INSERT INTO sample VALUES(?, ?, ?)', [(1, 'abc', 3.14), (2, 'def', 2.72), (3, 'ghi', 1.62)])\n", "conn.commit()\n", "\n", "for record in cur.execute('SELECT * FROM sample'):\n", " print record\n", "\n", "conn.close()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Запись в БД производится только при вызове `conn.commit()`" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "todo\n", "\n", " sqlite3.register_adapter(np.ndarray, adapt_array) # return return sqlite3.Binary(...)\n", " sqlite3.register_converter(\"array\", convert_array)\n", " create table test (idx integer primary key, X array, y integer );" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Для более серьезных нагрузок лучше подходит промышленная СУБД MySQL (https://dev.mysql.com/downloads/mysql/), клиент к которой на чистом Python реализован в библиотеке `pymysql`. Работа с ней, за исключением коннекта, идет аналогично SQLite. Отладку запросов и просмотр данных удобно вести в GUI-клиенте HeidiSQL (https://www.heidisql.com/download.php). Для запуска службы установленного MySQL под Windows можно использовать командную строку (администратор) `net start mysql`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```\n", "pip install pymysql\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "todo По слухам mysqlclient быстрее в 10 раз" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[{u'Bookmarked': u'', u'City': u'', u'Paginated': u'', u'Author': u'Kenneth W. Ford, John Archibald Wheeler', u'Generic': u'', u'Filesize': 3075899, u'Title': u'Geons, Black Holes, and Quantum Foam: A Life in Physics', u'Commentary': u'', u'Issue': u'0', u'DPI': 0, u'ASIN': u'', u'Extension': u'epub', u'UDC': u'', u'Visible': u'', u'Local': 0, u'ISSN': u'', u'LBC': u'', u'IdentifierWODash': u'0393319911,9780393319910', u'Pages': u'416', u'TimeLastModified': datetime.datetime(2016, 3, 20, 9, 50, 50), u'Cleaned': u'', u'Publisher': u'W. W. Norton & Company', u'TimeAdded': datetime.datetime(2015, 12, 10, 2, 44, 42), u'Doi': u'', u'Language': u'English', u'Googlebookid': u'', u'OpenLibraryID': u'', u'Coverurl': u'1412000/67b0d2116b5926efc6ab990fa27f1ae7-d.jpg', u'Locator': u'0393319911GBHF.epub', u'DDC': u'', u'Identifier': u'0393319911,9780393319910', u'ID': 1412770, u'MD5': u'67b0d2116b5926efc6ab990fa27f1ae7', u'VolumeInfo': u'', u'Orientation': u'', u'Searchable': u'', u'Color': u'', u'Series': u'', u'Tags': u'Scientists Professionals Academics Biographies Memoirs History Philosophy Science Math Physics Acoustics Sound Applied Astrophysics Biophysics Chaos Theory Chemical Cosmology Dynamics Electromagnetism Electron Microscopy Energy Engineering Entropy Gas Mechanics Geophysics Gravity Light Mathematical Nanostructures Nuclear Optics Quantum Chemistry Relativity Solid State System Time Waves Wave', u'Library': u'', u'Topic': u'', u'Edition': u'1', u'Scanned': u'', u'LCC': u'', u'Periodical': u'', u'Year': u'2000', u'PagesInFile': 0}]\n" ] } ], "source": [ "import pymysql\n", "\n", "conn = pymysql.connect(\n", " host='localhost', user='root', password='toor', db='bookwarrior',\n", " charset='utf8mb4', cursorclass=pymysql.cursors.DictCursor)\n", "\n", "try:\n", " with conn.cursor() as cur:\n", " sql = 'select * from updated where title like %s'\n", " cur.execute(sql, ['%quantum foam%'])\n", " print cur.fetchall()\n", "finally:\n", " conn.close()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "В целях консистентности `cursor.execute` возвращает число затронутых записей, а не `cursor`, а для подстановки параметров в SQL-запрос служит плейсхолдер `%s` вместо `?`" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Иногда SQL нужно парсить вне БД, тогда может пригодиться библиотека `sqlparse`" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```\n", "pip install sqlparse\n", "```" ] }, { "cell_type": "code", "execution_count": 41, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import sqlparse" ] }, { "cell_type": "code", "execution_count": 48, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 0 DML 'SELECT'\n", " 1 Whitespace ' '\n", " 2 Identifier 'image_...'\n", " | 0 Name 'image_...'\n", " 3 Whitespace ' '\n", " 4 Keyword 'FROM'\n", " 5 Whitespace ' '\n", " 6 Identifier 'favico...'\n", " | 0 Name 'favico...'\n", " 7 Whitespace ' '\n", " 8 Where 'WHERE ...'\n", " | 0 Keyword 'WHERE'\n", " | 1 Whitespace ' '\n", " | 2 Identifier 'icon_id'\n", " | | 0 Name 'icon_id'\n", " | 3 Whitespace ' '\n", " | 4 Keyword 'IN'\n", " | 5 Whitespace ' '\n", " | 6 Parenthesis '(SELEC...'\n", " | | 0 Punctuation '('\n", " | | 1 DML 'SELECT'\n", " | | 2 Whitespace ' '\n", " | | 3 Identifier 'id'\n", " | | | 0 Name 'id'\n", " | | 4 Whitespace ' '\n", " | | 5 Keyword 'FROM'\n", " | | 6 Whitespace ' '\n", " | | 7 Identifier 'favico...'\n", " | | | 0 Name 'favico...'\n", " | | 8 Whitespace ' '\n", " | | 9 Where 'WHERE ...'\n", " | | | 0 Keyword 'WHERE'\n", " | | | 1 Whitespace ' '\n", " | | | 2 Identifier 'url'\n", " | | | | 0 Name 'url'\n", " | | | 3 Whitespace ' '\n", " | | | 4 Keyword 'LIKE'\n", " | | | 5 Whitespace ' '\n", " | | | 6 Identifier '\"a%\"'\n", " | | | | 0 Symbol '\"a%\"'\n", " | | 10 Punctuation ')'\n" ] } ], "source": [ "sql = 'SELECT image_data FROM favicon_bitmaps WHERE icon_id IN (SELECT id FROM favicons WHERE url LIKE \"a%\")'\n", "for item in sqlparse.parse(sql):\n", " item._pprint_tree()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Упростить отладку SQL-запросов (или написание нарратива) может IPython-расширение `ipython-sql`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```\n", "pip install ipython-sql\n", "```" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": true }, "outputs": [], "source": [ "%load_ext sql\n", "%sql mysql+pymysql://root:toor@localhost/bookwarrior?charset=utf8" ] }, { "cell_type": "code", "execution_count": 110, "metadata": { "collapsed": false, "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " * mysql+pymysql://root:***@localhost/bookwarrior?charset=utf8\n", "11 rows affected.\n" ] }, { "data": { "text/html": [ "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
AuthorTitleFilesize
Academic Press IncEncyclopedia of Physical Science and Technology: v. 1-182301286288
George L Trigg; Wiley InterScience (Online service)Encyclopedia of applied physics2113552329
Библия Скорина1838268939
Birdsall, C.K; Langdon, A.BPlasma Physics via Computer Simulation1835668880
Edward W Abel; F Gordon A Stone; Geoffrey WilkinsonComprehensive organometallic chemistry II : a review of the literature 1982-19941831006210
Справочник корабельного состава военно-морских флотов мира1787078464
Jeffrey C. Posnick (Auth.)Orthognathic Surgery. Principles and Practice1748821843
Aversa, Stefano; Cascini, Leonardo; Picarelli, Luciano; Scavia, ClaudioLandslides and engineered slopes : experience, theory and practice1732284625
Essential Readings in Light Metals: Alumina and Bauxite, Volume 11731794911
Роджер ПенроузПуть к реальности, или законы, управляющие Вселенной1573490760
James W Patterson, Gregory A HoslerWeedon’s Skin Pathology1522413388
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Posnick (Auth.)', u'Orthognathic Surgery. Principles and Practice', 1748821843),\n", " (u'Aversa, Stefano; Cascini, Leonardo; Picarelli, Luciano; Scavia, Claudio', u'Landslides and engineered slopes : experience, theory and practice', 1732284625),\n", " (u'', u'Essential Readings in Light Metals: Alumina and Bauxite, Volume 1', 1731794911),\n", " (u'\\u0420\\u043e\\u0434\\u0436\\u0435\\u0440 \\u041f\\u0435\\u043d\\u0440\\u043e\\u0443\\u0437', u'\\u041f\\u0443\\u0442\\u044c \\u043a \\u0440\\u0435\\u0430\\u043b\\u044c\\u043d\\u043e\\u0441\\u0442\\u0438, \\u0438\\u043b\\u0438 \\u0437\\u0430\\u043a\\u043e\\u043d\\u044b, \\u0443\\u043f\\u0440\\u0430\\u0432\\u043b\\u044f\\u044e\\u0449\\u0438\\u0435 \\u0412\\u0441\\u0435\\u043b\\u0435\\u043d\\u043d\\u043e\\u0439', 1573490760),\n", " (u'James W Patterson, Gregory A Hosler', u'Weedon\\u2019s Skin Pathology', 1522413388)]" ] }, "execution_count": 110, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%sql select Author, Title, Filesize from updated where Filesize > 1500000000 order by Filesize desc" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Семантические БД" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Реляционные таблицы плохо справляются с задачей хранения данных о реальном мире со сложной онтологией, неполнотой, указанием источников данных. Значительно удобнее для этих целей семантические базы данных, хранящие данные в виде троек-утверждений (субъект, предикат, объект), например, (Великобритания, имеет-столицей, Лондон). Субъект и предикат это некоторые URL (в том же синтаксисе, но не отвечают никаким реальным адресам в интернете), а объект может быть как URL, так и литералом (числом, строкой). URL кодифицируют и объекты, и их классы, и отношения, одна и та же сущность может иметь одинаковые URL в разных БД из разных источников, что позволяет их объединять в единый источник данных. Набор таких переиспользуемых URL с их семантикой и отношениями называется онтологией." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Для операций (выборка таблицы, конструирование графа, проверка существования подграфа, вставка/удаление данных) над семантическими БД используется язык SPARQL (https://www.w3.org/TR/rdf-sparql-query/), отдаленно похожий на SQL, но значительно более мощный. Ниже приведен фрагмент данных (12 стран Южной Америки, их столицы и население столиц) из семантической БД в синтаксисе Turtle (https://www.w3.org/TeamSubmission/turtle/). Он получен исполнением такого SPARQL-запроса из SPARQL endpoint одной из крупнейших открытых семантических БД DBpedia, которая хранит все размеченные данные из Wikipedia http://dbpedia.org/sparql/:\n", "\n", " CONSTRUCT WHERE {\n", " ?country a yago:WikicatMemberStatesOfTheUnitedNations, yago:WikicatCountriesInSouthAmerica ;\n", " dbo:capital ?city .\n", " OPTIONAL { ?city dbo:populationTotal ?pop . }\n", " }\n", "\n", "Тройки задаются в виде `S P O .`, либо `S P O ; P O .`, либо `S P O , O .`. Префиксы URL можно объявлять и использовать, что улучшает читабельность. Список общепринятых префиксов широко распространенных онтологий можно найти здесь http://prefix.cc/popular/all ." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```turtle\n", "@prefix rdf: .\n", "@prefix xsd: .\n", "@prefix yago: .\n", "@prefix dbr: .\n", "@prefix dbo: .\n", "\n", "dbr:Argentina\n", " rdf:type yago:WikicatCountriesInSouthAmerica , yago:WikicatMemberStatesOfTheUnitedNations ;\n", " dbo:capital\tdbr:Buenos_Aires .\n", "dbr:Buenos_Aires dbo:populationTotal \"2890151\"^^xsd:nonNegativeInteger .\n", "\n", "dbr:Bolivia\n", " rdf:type yago:WikicatMemberStatesOfTheUnitedNations , yago:WikicatCountriesInSouthAmerica ;\n", " dbo:capital\tdbr:Sucre .\n", "dbr:Sucre dbo:populationTotal \"300000\"^^xsd:nonNegativeInteger .\n", "\n", "dbr:Brazil\n", " rdf:type yago:WikicatMemberStatesOfTheUnitedNations , yago:WikicatCountriesInSouthAmerica ;\n", " dbo:capital .\n", " dbo:populationTotal \"2556149\"^^xsd:nonNegativeInteger .\n", "\n", "dbr:Chile\n", " rdf:type yago:WikicatMemberStatesOfTheUnitedNations , yago:WikicatCountriesInSouthAmerica ;\n", " dbo:capital dbr:Santiago .\n", "dbr:Santiago dbo:populationTotal \"6158080\"^^xsd:nonNegativeInteger .\n", "\n", "dbr:Colombia\n", " rdf:type yago:WikicatCountriesInSouthAmerica , yago:WikicatMemberStatesOfTheUnitedNations ;\n", " dbo:capital .\n", " dbo:populationTotal \"7878783\"^^xsd:nonNegativeInteger .\n", "\n", "dbr:Ecuador\n", " rdf:type yago:WikicatMemberStatesOfTheUnitedNations , yago:WikicatCountriesInSouthAmerica ;\n", " dbo:capital dbr:Quito .\n", "dbr:Quito dbo:populationTotal \"2671191\"^^xsd:nonNegativeInteger .\n", "\n", "dbr:Guyana\n", " rdf:type yago:WikicatMemberStatesOfTheUnitedNations , yago:WikicatCountriesInSouthAmerica ;\n", " dbo:capital .\n", " dbo:populationTotal \"118363\"^^xsd:nonNegativeInteger .\n", "\n", "dbr:Paraguay\n", " rdf:type yago:WikicatMemberStatesOfTheUnitedNations , yago:WikicatCountriesInSouthAmerica ;\n", " dbo:capital .\n", " dbo:populationTotal \"525294\"^^xsd:nonNegativeInteger .\n", "\n", "dbr:Peru\n", " rdf:type yago:WikicatMemberStatesOfTheUnitedNations , yago:WikicatCountriesInSouthAmerica ;\n", " dbo:capital dbr:Lima .\n", "dbr:Lima dbo:populationTotal \"8852000\"^^xsd:nonNegativeInteger .\n", "\n", "dbr:Suriname\n", " rdf:type yago:WikicatMemberStatesOfTheUnitedNations , yago:WikicatCountriesInSouthAmerica ;\n", " dbo:capital dbr:Paramaribo .\n", "dbr:Paramaribo dbo:populationTotal \"240924\"^^xsd:nonNegativeInteger .\n", "\n", "dbr:Uruguay\n", " rdf:type yago:WikicatMemberStatesOfTheUnitedNations , yago:WikicatCountriesInSouthAmerica ;\n", " dbo:capital dbr:Montevideo .\n", "dbr:Montevideo dbo:populationTotal \"1305082\"^^xsd:nonNegativeInteger .\n", "\n", "dbr:Venezuela\n", " rdf:type yago:WikicatMemberStatesOfTheUnitedNations , yago:WikicatCountriesInSouthAmerica ;\n", " dbo:capital dbr:Caracas .\n", "dbr:Caracas dbo:populationTotal \"3273863\"^^xsd:nonNegativeInteger .\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "В качестве клиентской библиотеки к семантическим БД в Python можно использовать `SPARQLWrapper`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```\n", "pip install SPARQLWrapper\n", "```" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import SPARQLWrapper" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "sparql = SPARQLWrapper.SPARQLWrapper('http://dbpedia.org/sparql')\n", "sparql.setQuery('''\n", " PREFIX rdfs: \n", " PREFIX yago: \n", " PREFIX dbr: \n", " PREFIX dbo: \n", " \n", " SELECT * {\n", " ?country a yago:WikicatMemberStatesOfTheUnitedNations, yago:WikicatCountriesInSouthAmerica ;\n", " dbo:capital ?city ;\n", " rdfs:label ?clabel .\n", " ?city rdfs:label ?label .\n", " \n", " OPTIONAL { ?country dbo:populationTotal ?cpop . }\n", " OPTIONAL { ?city dbo:populationTotal ?pop . }\n", " \n", " FILTER (lang(?clabel) = 'ru')\n", " FILTER (lang(?label) = 'ru')\n", " }\n", " ORDER BY ?clabel\n", "''')\n", "sparql.setReturnFormat(SPARQLWrapper.JSON)\n", "results = sparql.query().convert()" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false, "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{u'head': {u'link': [], u'vars': [u'country', u'city', u'clabel', u'label', u'cpop', u'pop']}, u'results': {u'distinct': False, u'bindings': [{u'city': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Buenos_Aires'}, u'country': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Argentina'}, u'pop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'2890151'}, u'label': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u0411\\u0443\\u044d\\u043d\\u043e\\u0441-\\u0410\\u0439\\u0440\\u0435\\u0441'}, u'cpop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'43417000'}, u'clabel': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u0410\\u0440\\u0433\\u0435\\u043d\\u0442\\u0438\\u043d\\u0430'}}, {u'city': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Sucre'}, u'country': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Bolivia'}, u'pop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'300000'}, u'label': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u0421\\u0443\\u043a\\u0440\\u0435 (\\u0433\\u043e\\u0440\\u043e\\u0434)'}, u'cpop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'11410651'}, u'clabel': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u0411\\u043e\\u043b\\u0438\\u0432\\u0438\\u044f'}}, {u'city': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Bras\\xedlia'}, u'country': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Brazil'}, u'pop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'2556149'}, u'label': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u0411\\u0440\\u0430\\u0437\\u0438\\u043b\\u0438\\u0430'}, u'cpop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'206440850'}, u'clabel': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u0411\\u0440\\u0430\\u0437\\u0438\\u043b\\u0438\\u044f'}}, {u'country': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Venezuela'}, u'label': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u041a\\u0430\\u0440\\u0430\\u043a\\u0430\\u0441'}, u'clabel': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u0412\\u0435\\u043d\\u0435\\u0441\\u0443\\u044d\\u043b\\u0430'}, u'pop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'3273863'}, u'city': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Caracas'}}, {u'city': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Georgetown,_Guyana'}, u'country': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Guyana'}, u'pop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'118363'}, u'label': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u0414\\u0436\\u043e\\u0440\\u0434\\u0436\\u0442\\u0430\\u0443\\u043d'}, u'cpop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'735554'}, u'clabel': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u0413\\u0430\\u0439\\u0430\\u043d\\u0430'}}, {u'city': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Bogot\\xe1'}, u'country': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Colombia'}, u'pop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'7878783'}, u'label': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u0411\\u043e\\u0433\\u043e\\u0442\\u0430'}, u'cpop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'48786100'}, u'clabel': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u041a\\u043e\\u043b\\u0443\\u043c\\u0431\\u0438\\u044f'}}, {u'city': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Asunci\\xf3n'}, u'country': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Paraguay'}, u'pop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'525294'}, u'label': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u0410\\u0441\\u0443\\u043d\\u0441\\u044c\\u043e\\u043d'}, u'cpop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'6783272'}, u'clabel': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u041f\\u0430\\u0440\\u0430\\u0433\\u0432\\u0430\\u0439'}}, {u'city': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Lima'}, u'country': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Peru'}, u'pop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'8852000'}, u'label': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u041b\\u0438\\u043c\\u0430'}, u'cpop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'31151643'}, u'clabel': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u041f\\u0435\\u0440\\u0443'}}, {u'city': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Paramaribo'}, u'country': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Suriname'}, u'pop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'240924'}, u'label': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u041f\\u0430\\u0440\\u0430\\u043c\\u0430\\u0440\\u0438\\u0431\\u043e'}, u'cpop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'573311'}, u'clabel': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u0421\\u0443\\u0440\\u0438\\u043d\\u0430\\u043c'}}, {u'city': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Montevideo'}, u'country': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Uruguay'}, u'pop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'1305082'}, u'label': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u041c\\u043e\\u043d\\u0442\\u0435\\u0432\\u0438\\u0434\\u0435\\u043e'}, u'cpop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'3427000'}, u'clabel': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u0423\\u0440\\u0443\\u0433\\u0432\\u0430\\u0439'}}, {u'city': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Santiago'}, u'country': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Chile'}, u'pop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'6158080'}, u'label': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u0421\\u0430\\u043d\\u0442\\u044c\\u044f\\u0433\\u043e'}, u'cpop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'18006407'}, u'clabel': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u0427\\u0438\\u043b\\u0438'}}, {u'city': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Quito'}, u'country': {u'type': u'uri', u'value': u'http://dbpedia.org/resource/Ecuador'}, u'pop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'2671191'}, u'label': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u041a\\u0438\\u0442\\u043e'}, u'cpop': {u'datatype': u'http://www.w3.org/2001/XMLSchema#nonNegativeInteger', u'type': u'typed-literal', u'value': u'16144000'}, u'clabel': {u'xml:lang': u'ru', u'type': u'literal', u'value': u'\\u042d\\u043a\\u0432\\u0430\\u0434\\u043e\\u0440'}}], u'ordered': True}}\n" ] } ], "source": [ "print results" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "На таблице хорошо видна и основная проблема семантических БД — злоупотребление возможностью указывать неполные данные. Для Венесуэлы в DBpedia нет данных о численности населения." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false, "scrolled": false }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
Страна Население Столица Население столицыДоля населения столицы в населении страны
Аргентина43417000 Буэнос-Айрес 28901516.66%
Боливия 11410651 Сукре (город) 3000002.63%
Бразилия 206440850 Бразилиа 25561491.24%
Венесуэла Каракас 3273863nan%
Гайана 735554 Джорджтаун 11836316.09%
Колумбия 48786100 Богота 787878316.15%
Парагвай 6783272 Асунсьон 5252947.74%
Перу 31151643 Лима 885200028.42%
Суринам 573311 Парамарибо 24092442.02%
Уругвай 3427000 Монтевидео 130508238.08%
Чили 18006407 Сантьяго 615808034.20%
Эквадор 16144000 Кито 267119116.55%
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import tabulate, IPython, math\n", "\n", "headers=[u'Страна', u'Население', u'Столица', u'Население столицы', u'Доля населения столицы в населении страны']\n", "lines = []\n", "for result in results['results']['bindings']:\n", " clabel = result['clabel']['value']\n", " cpop = result.get('cpop', {'value': ''})['value']\n", " label = result['label']['value']\n", " pop = result['pop']['value']\n", " lines.append([clabel, cpop, label, pop, '%.2f%%' % (float(pop) / (float(cpop) if cpop else float('nan')) * 100)])\n", "\n", "IPython.display.display(IPython.display.HTML(tabulate.tabulate(lines, tablefmt='html', headers=headers)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Семантическую СУБД можно установить и локально, предпочтительным вариантом является Blazegraph (https://www.blazegraph.com/download/). Скачайте файл `blazegraph.jar`, создайте рядом файл настроек `RWStore.properties`, в котором пропишите (для Windows)\n", "\n", " com.bigdata.rwstore.RWStore.readBlobsAsync=false\n", " com.bigdata.journal.AbstractJournal.file=blazegraph.jnl\n", " \n", " com.bigdata.rdf.sail.truthMaintenance=false\n", " com.bigdata.rdf.store.AbstractTripleStore.quads=false\n", " com.bigdata.rdf.store.AbstractTripleStore.axiomsClass=com.bigdata.rdf.axioms.NoAxioms\n", "\n", "Три последние строки отключают встроенный вывод новых триплов по правилам, сильно уменьшающий производительность и как правило не нужный. Без них пришлось бы перед каждым `INSERT` вставлять `DISABLE ENTAILMENTS;`.\n", "\n", "запустите сервер командой\n", "\n", " java -server -Xmx4g -Djetty.host=127.0.0.1 -Dbigdata.propertyFile=RWStore.properties -jar blazegraph.jar\n", " \n", "Blazegraph создаст файл для данных `blazegraph.jnl` размером 210 МБ." ] }, { "cell_type": "code", "execution_count": 96, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{u'head': {u'vars': [u'c']}, u'results': {u'bindings': [{u'c': {u'datatype': u'http://www.w3.org/2001/XMLSchema#integer', u'type': u'literal', u'value': u'28803'}}]}}\n" ] } ], "source": [ "sparql = SPARQLWrapper.SPARQLWrapper('http://127.0.0.1:9999/blazegraph/sparql')\n", "sparql.setQuery('SELECT (COUNT(*) as ?c) { ?s ?p ?o . }')\n", "sparql.setReturnFormat(SPARQLWrapper.JSON)\n", "print sparql.query().convert()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Последний дамп Wikidata можно скачать тут https://dumps.wikimedia.org/wikidatawiki/entities/latest-all.ttl.bz2 (28 ГБ)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Библиотека `rdflib` работает с графами, которые могут быть получены из SPARQL endpoint или из файлов." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import rdflib" ] }, { "cell_type": "code", "execution_count": 170, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "http://dbpedia.org/resource/Semantic_Web http://www.w3.org/2000/01/rdf-schema#label Web semântica\n", "http://dbpedia.org/resource/Semantic_Web http://www.w3.org/2000/01/rdf-schema#label ويب دلالي\n", "http://dbpedia.org/resource/Semantic_Web http://www.w3.org/2000/01/rdf-schema#label Semantic Web\n", "http://dbpedia.org/resource/Semantic_Web http://www.w3.org/2000/01/rdf-schema#label Web semántica\n", "http://dbpedia.org/resource/Semantic_Web http://www.w3.org/2000/01/rdf-schema#label Semantic Web\n", "http://dbpedia.org/resource/Semantic_Web http://www.w3.org/2000/01/rdf-schema#label 语义网\n", "http://dbpedia.org/resource/Semantic_Web http://www.w3.org/2000/01/rdf-schema#label Семантическая паутина\n", "http://dbpedia.org/resource/Semantic_Web http://www.w3.org/2000/01/rdf-schema#label Web semantico\n", "http://dbpedia.org/resource/Semantic_Web http://www.w3.org/2000/01/rdf-schema#label Semantic Web\n", "http://dbpedia.org/resource/Semantic_Web http://www.w3.org/2000/01/rdf-schema#label Web sémantique\n", "http://dbpedia.org/resource/Semantic_Web http://www.w3.org/2000/01/rdf-schema#label セマンティック・ウェブ\n", "http://dbpedia.org/resource/Semantic_Web http://www.w3.org/2000/01/rdf-schema#label Semantisch web\n" ] } ], "source": [ "g = rdflib.Graph()\n", "g.load('http://dbpedia.org/resource/Semantic_Web') # g.loaf('file.ttl')\n", "\n", "for s,p,o in g:\n", " if str(p) == 'http://www.w3.org/2000/01/rdf-schema#label':\n", " print s,p,o" ] }, { "cell_type": "code", "execution_count": 177, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "@prefix dbo: .\n", "@prefix dbp: .\n", "@prefix dct: .\n", "@prefix foaf: .\n", "@prefix ns8: .\n", "@prefix owl: .\n", "@prefix prov: .\n", "@prefix rdf: .\n", "@prefix rdfs: .\n", "@prefix xml: .\n", "@prefix xsd: .\n", "\n", " dbo:genre .\n", "\n", " dbp:fields .\n", "\n", " dbo:field .\n", "\n", " dbo:wikiPageRedirects .\n", "\n", " dbo:genre .\n", "\n", " dbo:field .\n", "\n", " dbo:knownFor .\n", "\n", " dbo:academicDiscipline .\n", "\n", " dbo:field .\n", "\n", " dbo:field .\n", "\n", " dbo:field .\n", "\n", " dbo:academicDiscipline .\n", "\n", " dbo:knownFor .\n", "\n", " dbo:genre .\n", "\n", " dbo:field .\n", "\n", " dbo:field .\n", "\n", " dbo:genre .\n", "\n", " dbp:genre .\n", "\n", " dbo:field ;\n", " dbo:knownFor .\n", "\n", " dbp:genre .\n", "\n", " dbo:industry .\n", "\n", " dbo:genre .\n", "\n", " dbp:genre .\n", "\n", " dbp:domain .\n", "\n", " dbp:domain .\n", "\n", " dbp:domain .\n", "\n", " dbo:field .\n", "\n", " dbp:focus .\n", "\n", " dbp:domain .\n", "\n", " dbo:wikiPageRedirects .\n", "\n", " dbo:wikiPageRedirects .\n", "\n", " dbo:wikiPageRedirects .\n", "\n", " dbo:wikiPageRedirects .\n", "\n", " dbo:wikiPageRedirects .\n", "\n", " dbo:wikiPageRedirects .\n", "\n", " dbo:wikiPageRedirects .\n", "\n", " dbo:genre .\n", "\n", " dbo:genre .\n", "\n", " dbo:wikiPageRedirects .\n", "\n", " dbo:wikiPageRedirects .\n", "\n", " dbp:genre .\n", "\n", " dbp:genre .\n", "\n", " dbp:genre .\n", "\n", " dbo:genre .\n", "\n", " dbo:wikiPageRedirects .\n", "\n", " dbo:wikiPageRedirects .\n", "\n", " dbo:field .\n", "\n", " dbo:genre .\n", "\n", " foaf:primaryTopic .\n", "\n", " a ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " dbo:Software,\n", " owl:Thing ;\n", " rdfs:label \"ويب دلالي\"@ar,\n", " \"Semantic Web\"@de,\n", " \"Semantic Web\"@en,\n", " \"Web semántica\"@es,\n", " \"Web sémantique\"@fr,\n", " \"Web semantico\"@it,\n", " \"セマンティック・ウェブ\"@ja,\n", " \"Semantisch web\"@nl,\n", " \"Semantic Web\"@pl,\n", " \"Web semântica\"@pt,\n", " \"Семантическая паутина\"@ru,\n", " \"语义网\"@zh ;\n", " dbo:abstract \"إن ورود المعلومات على الإنترنت يزداد بشكل كبير، فقد أصبح الإنترنت مكانًا للتعبير عن الأفكار، سرد القصص، إنشاء المدونات ومشاركة الفيديوهات والصور والملفات الصوتية وما إلى ذلك. وهو ما جعل كمّ المعلومات المتوفرة للفرد الواحد أكبر بكثير ممايُمكن له أن يستفيد منه. تعريض العقل البشري لهذا الكم الهائل من المعلومات من شأنه أن يتسبب فيما يُمكن أن نصفه بوصف \\\"الضياع في فضاء المعلومات\\\"، وذلك راجع إلى بقاء المعلومات المفيدة بعيدة المنال بسبب تراكم الكثير من المعلومات غير المفيدة وغير المرتبطة بالموضوع المراد البحث عنه من قبل المستخدم.لحسن الحظ، مثلما يزداد ورود المعلومات، تزداد مقدرات معالجة المعلومات اوتوماتيكياً، لذا يوجد إمكانيات كبيرة للاستفادة من مقدرات الأتمتة هذه بهدف استخراج المعلومات والخدمات من فيضان الويب والمرتبطة بالمستخدم، وتوصيلها إليه عن طريق واجهة مستخدم معيارية (Standardized User Interface). إن أهمية الحصول على المعلومات بهذه الطريقة التكيفية يزداد بازدياد كتلة المعلومات المتوفرة على الإنترنت. تعتبر شبكة الوب أغنى المصادر المعلوماتية بما تحويه من مستندات ومعلومات ومصادر منوعة يمكن الوصول إليها عن طريق محركات البحث التقليدية. غير أن تنظيم هذه المعلومات والمستندات بصورة تسهل عملية البحث فيها والوصول إليها، يعتبر أمراً غاية في الصعوبة. يضاف إلى ذلك، أنه في ظل التزايد المستمر في حجم المعلومات المنشورة في شبكة الويب أصبح من الصعوبة بمكان قيام محركات البحث بإيجاد المعلومات المناسبة. ومن هذه المشكلة ظهرت فكرة \\\"الويب ذات الدلالات والمعاني اللفظية\\\"، أو ما يطلق عليه بالإنجليزية مصطلح (Semantic Web)، والتي هي امتداد للويب الحالية ولكن تختلف عنها بأنها تتفهم مدلولات الألفاظ والمعاني البشرية.\"@ar,\n", " \"Das Semantic Web erweitert das Web, um Daten zwischen Rechnern einfacher austauschbar und für sie einfacher verwertbar zu machen; so kann beispielsweise der Begriff „Bremen“ in einem Webdokument um die Information ergänzt werden, ob hier ein Schiffs-, Familien- oder der Stadtname gemeint ist. Diese zusätzlichen Informationen explizieren die sonst nur unstrukturiert vorkommenden Daten. Zur Realisierung dienen Standards zur Veröffentlichung und Nutzung maschinenlesbarer Daten (insbesondere RDF). Während Menschen solche Informationen aus dem gegebenen Kontext schließen können (aus dem Gesamttext, über die Art der Publikation oder der Rubrik in selbiger, Bilder etc.) und derartige Verknüpfungen unbewusst aufbauen, muss Maschinen dieser Kontext erst beigebracht werden; hierzu werden die Inhalte mit weiterführenden Informationen verknüpft. Das Semantic Web beschreibt dazu konzeptionell einen „Giant Global Graph“ (engl. ‚gigantischer globaler Graph‘). Dabei werden sämtliche Sachen von Interesse identifiziert und mit einer eindeutigen Adresse versehen als Knoten angelegt, die wiederum durch Kanten (ebenfalls jeweils eindeutig benannt) miteinander verbunden sind. Einzelne Dokumente im Web beschreiben dann eine Reihe von Kanten, und die Gesamtheit all dieser Kanten entspricht dem globalen Graphen.\"@de,\n", " \"The Semantic Web is an extension of the Web through standards by the World Wide Web Consortium (W3C). The standards promote common data formats and exchange protocols on the Web, most fundamentally the Resource Description Framework (RDF). According to the W3C, \\\"The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries\\\". The term was coined by Tim Berners-Lee for a web of data that can be processed by machines.While its critics have questioned its feasibility, proponents argue that applications in industry, biology and human sciences research have already proven the validity of the original concept. The 2001 Scientific American article by Berners-Lee, Hendler, and Lassila described an expected evolution of the existing Web to a Semantic Web. In 2006, Berners-Lee and colleagues stated that: \\\"This simple idea…remains largely unrealized\\\".In 2013, more than four million Web domains contained Semantic Web markup.\"@en,\n", " \"La web semántica (del inglés semantic web) es un conjunto de actividades desarrolladas en el seno de World Wide Web Consortium con tendencia a la creación de tecnologías para publicar datos legibles por aplicaciones informáticas (máquinas en la terminología de la Web semántica). Se basa en la idea de añadir metadatos semánticos y ontológicos a la World Wide Web. Esas informaciones adicionales —que describen el contenido, el significado y la relación de los datos— se deben proporcionar de manera formal, para que así sea posible evaluarlas automáticamente por máquinas de procesamiento. El objetivo es mejorar Internet ampliando la interoperabilidad entre los sistemas informáticos usando \\\"agentes inteligentes\\\". Agentes inteligentes son programas en las computadoras que buscan información sin operadores humanos. El precursor de la idea, Tim Berners-Lee, intentó desde el principio incluir información semántica en su creación, la World Wide Web, pero por diferentes causas no fue posible. Por ese motivo introdujo el concepto de semántica con la intención de recuperar dicha omisión.\"@es,\n", " \"Le Web sémantique, ou toile sémantique, est une extension du Web standardisée par le World Wide Web Consortium (W3C). Ces standards encouragent l'utilisation de formats de données et de protocoles d'échange normés sur le Web, avec comme format de base le Resource Description Framework (RDF). Selon le W3C, « le Web sémantique fournit un modèle qui permet aux données d'être partagées et réutilisées entre plusieurs applications, entreprises et groupes d'utilisateurs ». L'expression a été inventée par Tim Berners-Lee (inventeur du Web et directeur du W3C), qui supervise le développement des technologies communes du Web sémantique. Il le définit comme « une toile de données qui peuvent être traitées directement et indirectement par des machines pour aider leurs utilisateurs à créer de nouvelles connaissances ». Pour y parvenir, le Web sémantique met en œuvre le Web des données qui consiste à lier et structurer l'information sur Internet pour accéder simplement à la connaissance qu'elle contient déjà. Alors que ses détracteurs ont mis en doute sa faisabilité, ses promoteurs font valoir que les applications réalisées par les chercheurs dans l'industrie, la biologie et les sciences humaines ont déjà prouvé la validité de ce nouveau concept. L'article original de Tim Berners-Lee en 2001 dans le Scientific American a décrit une évolution attendue du Web existant vers un Web sémantique, mais cela n'a pas encore eu lieu. En 2006, Tim Berners-Lee et ses collègues ont déclaré : « Cette idée simple… reste largement inexploitée. »\"@fr,\n", " \"Con il termine web semantico, termine coniato dal suo ideatore, Tim Berners-Lee, si intende la trasformazione del World Wide Web in un ambiente dove i documenti pubblicati (pagine HTML, file, immagini, e così via) sono associati ad informazioni e dati (metadati) che ne specificano il contesto semantico in un formato adatto all'interrogazione e l'interpretazione (es. tramite motori di ricerca) e, più in generale, all'elaborazione automatica. Con l'interpretazione del contenuto dei documenti che il Web semantico impone, saranno possibili ricerche molto più evolute delle attuali, basate sulla presenza nel documento di parole chiave, e altre operazioni specialistiche come la costruzione di reti di relazioni e connessioni tra documenti secondo logiche più elaborate del semplice collegamento ipertestuale.\"@it,\n", " \"セマンティック・ウェブ（英: semantic web）は W3C のティム・バーナーズ＝リーによって提唱された、ウェブページの意味を扱うことを可能とする標準やツール群の開発によってワールド・ワイド・ウェブの利便性を向上させるプロジェクト。セマンティック・ウェブの目的はウェブページの閲覧という行為に、データの交換の側面に加えて意味の疎通を付け加えることにある。 現在のワールド・ワイド・ウェブ上のコンテンツは主にHTMLで記述されている。HTMLでは文書構造を伝えることは可能だが、個々の単語の意味をはじめとする詳細な意味を伝えることはできない。これに対し、セマンティック・ウェブはXMLによって記述した文書にRDFやOWLを用いてタグを付け加える。この、データの意味を記述したタグが文書の含む意味を形式化し、コンピュータによる自動的な情報の収集や分析へのアプローチが可能となると期待されている。オントロジーを扱う階層まではW3Cにより標準化されているが、それ以上の階層の開発は難しいため、実現と標準化には長期間掛かると予想されている。また、既存のWebサイトに対するメタデータ付与の作業が必要であるため、Web全域への普及に関しても長期間掛かると予想されている。 セマンティックウェブはXML、XML Schema、RDF、RDF Schema、OWLなどの標準およびツール群から構成されている。「OWL ウェブ・オントロジー言語概要」はセマンティックウェブにおけるこれら標準およびツール群の機能・関連について述べている。\"@ja,\n", " \"Het semantisch web verschaft een standaardframework waarmee data gedeeld en hergebruikt kunnen worden. Het is een samenwerking onder leiding van het internationale orgaan voor internetstandaarden, het World Wide Web Consortium (W3C). Het semantisch web is geen synoniem voor Web 2.0, zoals soms wel wordt verondersteld. Tim Berners-Lee beschreef het semantische web als een component van 'Web 3.0'. Soms wordt het gebruikt als synoniem voor Web 3.0, hoewel de definities verschillen.\"@nl,\n", " \"\"\"Semantic Web (sieci semantyczne) – projekt, który ma przyczynić się do utworzenia i rozpowszechnienia standardów opisywania treści w Internecie w sposób, który umożliwi maszynom i programom (np. tzw. agentom) przetwarzanie informacji w sposób odpowiedni do ich znaczenia. Wśród standardów sieci semantycznych znajdują się m.in. OWL, RDF, RDF Schema (inaczej RDFS). Znaczenia zasobów informacyjnych określa się za pomocą tzw. ontologii. Sieć semantyczna jest wizją Tima Bernersa-Lee (twórcy standardu WWW i pierwszej przeglądarki internetowej, a także przewodniczącego W3C). W swoich założeniach sieć semantyczna ma korzystać z istniejącego protokołu komunikacyjnego, na którym bazuje dzisiejszy Internet. Różnica miałaby polegać na tym, że przesyłane dane mogłyby być 'rozumiane' także przez maszyny. Owo 'rozumienie' polegałoby na tym, że dane przekazywane byłyby w postaci, w której można by powiązać ich znaczenia między sobą a także w ramach odpowiedniego kontekstu. Informacje przekazywane w ramach sieci semantycznej wymagałyby nie tylko samych danych, ale także informacji o tychże (tzw. meta-danych). To właśnie meta-dane zawierałyby sformułowania dotyczące relacji między danymi oraz prawa logiki, które można do nich zastosować. Dzięki temu można by: \n", "* powiązać różne dane znajdujące się w Internecie w ramach wspólnych jednostek znaczeniowych (np. strony dotyczące filmów, dziedzin nauki, kuchni francuskiej, etc.) \n", "* rozróżnić dane, które dla maszyn są w tej chwili nierozróżnialne ze względu na identyczny zapis tekstowy (np. zamek - urządzenie do zamykania drzwi; urządzenie do łączenia w ustalonym położeniu elementów ubrania; okazała budowla mieszkalno-obronna) \n", "* przeprowadzać na tychże danych wnioskowania, tzn. otrzymywać informacje na ich temat, które nie są zawarte explicite (np. na podstawie danej \"Ewa jest żoną Adama\", możemy też dowiedzieć się, że Ewa jest kobietą, Adam mężczyzną, Adam jest mężem Ewy, żaden inny mężczyzna nie jest mężem Ewy, etc.)\"\"\"@pl,\n", " \"A Web semântica é uma extensão da World Wide Web atual, que permitirá aos computadores e humanos trabalharem em cooperação. A Web semântica interliga significados de palavras e, neste âmbito, tem como finalidade conseguir atribuir um significado (sentido) aos conteúdos publicados na Internet de modo que seja perceptível tanto pelo humano como pelo computador. A ideia da Web Semântica surgiu em 2001, quando Tim Berners-Lee, James Hendler e Ora Lassila publicaram um artigo na revista Scientific American, intitulado: “Web Semântica: um novo formato de conteúdo para a Web que tem significado para computadores vai iniciar uma revolução de novas possibilidades.” A web semântica é a relação de interatividade do homem e o computador, onde um depende do outro para a conclusão de tarefas, assim acepção de entendimento do comando estipulado do ser humano à interface operacional da maquina dando um significado de ordem a ser executada. Sendo desta forma uma espécie de escrita de entendimento tanto para o computador e para usuário, por meio de organização das informações contida na máquina, através do seu perfil de suas últimas pesquisas realizadas, originando um repositório de dados lincados, como se fosse um verbete de enciclopédia. Podemos fazer uma assimilação da web semântica com a Ciência da Informação, pelo fato de possuir a ideia estrutural de arranjo sistêmico, agrupando um conjunto de coleta de análise, classificação, armazenamento, disseminação e recuperação de informação como se fosse uma enciclopédia. O objetivo principal da web semântica não é, pelo menos para já, treinar as máquinas para que se comportem como pessoas, mas sim desenvolver tecnologias e linguagens que tornem a informação legível para as máquinas. A finalidade passa pelo desenvolvimento de um modelo tecnológico que permita a partilha global de conhecimento assistido por máquinas (W3C 2001). A integração das linguagens ou tecnologias eXtensible Markup Language (XML), Resource Description Framework (RDF), arquiteturas de metadados, ontologias, agentes computacionais, entre outras, favorecerá o aparecimento de serviços Web que garantam a interoperabilidade e cooperação. Ultimamente tem-se associado a Web Semântica à Web 3.0, como um próximo movimento da internet depois da Web 2.0 que já inicia seu crescimento.\"@pt,\n", " \"Семанти́ческая паути́на (англ. semantic web) — это общедоступная глобальная семантическая сеть, формируемая на базе Всемирной паутины путём стандартизации представления информации в виде, пригодном для машинной обработки. В обычной Всемирной паутине, основанной на HTML-страницах, информация заложена в тексте страниц и предназначена для чтения и понимания человеком. Семантическая паутина состоит из машинно-читаемых элементов — узлов семантической сети, с опорой на онтологии. Благодаря этому программы-клиенты получают возможность непосредственно получать из интернета утверждения вида «предмет — вид взаимосвязи — другой предмет» и вычислять по ним логические заключения. Семантическая паутина работает параллельно с обычной Всемирной паутиной и на её основе, используя протокол HTTP и идентификаторы ресурсов URI. Название «Семантическая паутина» было впервые введено сэром Тимом Бернерсом-Ли (изобретателем Всемирной паутины) в сентябре 1998 года, и называется им «следующим шагом в развитии Всемирной паутины». Позже в своём блоге он предложил в качестве синонима термин «гигантский глобальный граф» (англ. giant global graph, GGG, по аналогии с WWW). Концепция семантической паутины была принята и продвигается консорциумом Всемирной паутины.\"@ru,\n", " \"\"\"语义网（Semantic Web）是由万维网联盟的蒂姆·伯纳斯-李（Tim Berners-Lee）在1998年提出的一个概念，它的核心是：通过给万维网上的文档（如: HTML）添加能够被计算机所理解的语义（Meta data），从而使整个互联网成为一个通用的信息交换媒介。语义万维网通过使用标准、置标语言和相关的处理工具来扩展万维网的能力。不过语意网概念实际上是基于很多已有技术的，也依赖于后来和text-and-markup与知识表现的综合。那些渊源甚至可以追溯到20世纪60年代末期的Allan M. Collins、M. Ross Quillian、Elizabeth F. Loftus等人的研究，还有之后70年代初R.F.Simon、R.C.Schamk、Minsky等人陆续提出的一些理论上的成果，其中Simon在进行自然语言理解的应用研究时提出了语义网络Semantic Network（不是现在的Semantic Web）的概念。当时人们甚至发明了以逻辑为基础的程序设计语言Prolog。 \"语义\"网是由比现今成熟的网际搜索工具更加行之有效的、更加广泛意义的并且自动聚集和搜集信息的文档组成的。其最基本的元素就是语义链接。 通过下列方法可以提升全球資訊網以及其互连的资源的易用性（usability）和實用性（usefulness）： \n", "* \"标记\"了语义信息的文档。这可以是机器可以理解的关于文档内容（例如文档的作者,标题,简介等)的描述,或者是描述该网站所拥有的服务和资源.(注意:任何东西都是能被URI-统一资源定位符-所描述的,因此语义网能理解人物、地方、想法、類別等等) \n", "* 通用元数据詞滙表(本体论)及詞滙間的影射使得文檔作者知道如何來標記文檔方可讓機器識別他想提供的元數據. \n", "* 利用元数据为语义网用户执行任务的自动软件代理(agent). \n", "* 為自動軟件代理提供特定信息的網絡服务 (例如,可信度服務可以讓軟件代理查詢某個在线商店是否曾經有過不良紀錄或者發送過垃圾郵件).\"\"\"@zh ;\n", " dbo:thumbnail ;\n", " dbo:wikiPageExternalLink ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ;\n", " dbo:wikiPageID 29123 ;\n", " dbo:wikiPageRevisionID 741952532 ;\n", " dbp:b \"no\"^^rdf:langString ;\n", " dbp:commons \"Category:Semantic Web\"^^rdf:langString ;\n", " dbp:d \"Q54837\"^^rdf:langString ;\n", " dbp:n \"no\"^^rdf:langString ;\n", " dbp:q \"no\"^^rdf:langString ;\n", " dbp:s \"no\"^^rdf:langString ;\n", " dbp:v \"no\"^^rdf:langString ;\n", " dbp:wikt \"no\"^^rdf:langString ;\n", " dct:subject ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ;\n", " ns8:hypernym ;\n", " rdfs:comment \"إن ورود المعلومات على الإنترنت يزداد بشكل كبير، فقد أصبح الإنترنت مكانًا للتعبير عن الأفكار، سرد القصص، إنشاء المدونات ومشاركة الفيديوهات والصور والملفات الصوتية وما إلى ذلك. وهو ما جعل كمّ المعلومات المتوفرة للفرد الواحد أكبر بكثير ممايُمكن له أن يستفيد منه. تعريض العقل البشري لهذا الكم الهائل من المعلومات من شأنه أن يتسبب فيما يُمكن أن نصفه بوصف \\\"الضياع في فضاء المعلومات\\\"، وذلك راجع إلى بقاء المعلومات المفيدة بعيدة المنال بسبب تراكم الكثير من المعلومات غير المفيدة وغير المرتبطة بالموضوع المراد البحث عنه من قبل المستخدم.لحسن الحظ، مثلما يزداد ورود المعلومات، تزداد مقدرات معالجة المعلومات اوتوماتيكياً، لذا يوجد إمكانيات كبيرة للاستفادة من مقدرات الأتمتة هذه بهدف استخراج المعلومات والخدمات من فيضان الويب والمرتبطة بالمستخدم، وتوصيلها إليه عن طريق واجهة مستخدم معيارية (Standardized User Inte\"@ar,\n", " \"Das Semantic Web erweitert das Web, um Daten zwischen Rechnern einfacher austauschbar und für sie einfacher verwertbar zu machen; so kann beispielsweise der Begriff „Bremen“ in einem Webdokument um die Information ergänzt werden, ob hier ein Schiffs-, Familien- oder der Stadtname gemeint ist. Diese zusätzlichen Informationen explizieren die sonst nur unstrukturiert vorkommenden Daten. Zur Realisierung dienen Standards zur Veröffentlichung und Nutzung maschinenlesbarer Daten (insbesondere RDF).\"@de,\n", " \"The Semantic Web is an extension of the Web through standards by the World Wide Web Consortium (W3C). The standards promote common data formats and exchange protocols on the Web, most fundamentally the Resource Description Framework (RDF). The 2001 Scientific American article by Berners-Lee, Hendler, and Lassila described an expected evolution of the existing Web to a Semantic Web. In 2006, Berners-Lee and colleagues stated that: \\\"This simple idea…remains largely unrealized\\\".In 2013, more than four million Web domains contained Semantic Web markup.\"@en,\n", " \"La web semántica (del inglés semantic web) es un conjunto de actividades desarrolladas en el seno de World Wide Web Consortium con tendencia a la creación de tecnologías para publicar datos legibles por aplicaciones informáticas (máquinas en la terminología de la Web semántica). Se basa en la idea de añadir metadatos semánticos y ontológicos a la World Wide Web. Esas informaciones adicionales —que describen el contenido, el significado y la relación de los datos— se deben proporcionar de manera formal, para que así sea posible evaluarlas automáticamente por máquinas de procesamiento. El objetivo es mejorar Internet ampliando la interoperabilidad entre los sistemas informáticos usando \\\"agentes inteligentes\\\". Agentes inteligentes son programas en las computadoras que buscan información sin o\"@es,\n", " \"Le Web sémantique, ou toile sémantique, est une extension du Web standardisée par le World Wide Web Consortium (W3C). Ces standards encouragent l'utilisation de formats de données et de protocoles d'échange normés sur le Web, avec comme format de base le Resource Description Framework (RDF).\"@fr,\n", " \"Con il termine web semantico, termine coniato dal suo ideatore, Tim Berners-Lee, si intende la trasformazione del World Wide Web in un ambiente dove i documenti pubblicati (pagine HTML, file, immagini, e così via) sono associati ad informazioni e dati (metadati) che ne specificano il contesto semantico in un formato adatto all'interrogazione e l'interpretazione (es. tramite motori di ricerca) e, più in generale, all'elaborazione automatica.\"@it,\n", " \"セマンティック・ウェブ（英: semantic web）は W3C のティム・バーナーズ＝リーによって提唱された、ウェブページの意味を扱うことを可能とする標準やツール群の開発によってワールド・ワイド・ウェブの利便性を向上させるプロジェクト。セマンティック・ウェブの目的はウェブページの閲覧という行為に、データの交換の側面に加えて意味の疎通を付け加えることにある。 現在のワールド・ワイド・ウェブ上のコンテンツは主にHTMLで記述されている。HTMLでは文書構造を伝えることは可能だが、個々の単語の意味をはじめとする詳細な意味を伝えることはできない。これに対し、セマンティック・ウェブはXMLによって記述した文書にRDFやOWLを用いてタグを付け加える。この、データの意味を記述したタグが文書の含む意味を形式化し、コンピュータによる自動的な情報の収集や分析へのアプローチが可能となると期待されている。オントロジーを扱う階層まではW3Cにより標準化されているが、それ以上の階層の開発は難しいため、実現と標準化には長期間掛かると予想されている。また、既存のWebサイトに対するメタデータ付与の作業が必要であるため、Web全域への普及に関しても長期間掛かると予想されている。\"@ja,\n", " \"Het semantisch web verschaft een standaardframework waarmee data gedeeld en hergebruikt kunnen worden. Het is een samenwerking onder leiding van het internationale orgaan voor internetstandaarden, het World Wide Web Consortium (W3C). Het semantisch web is geen synoniem voor Web 2.0, zoals soms wel wordt verondersteld. Tim Berners-Lee beschreef het semantische web als een component van 'Web 3.0'. Soms wordt het gebruikt als synoniem voor Web 3.0, hoewel de definities verschillen.\"@nl,\n", " \"Semantic Web (sieci semantyczne) – projekt, który ma przyczynić się do utworzenia i rozpowszechnienia standardów opisywania treści w Internecie w sposób, który umożliwi maszynom i programom (np. tzw. agentom) przetwarzanie informacji w sposób odpowiedni do ich znaczenia. Wśród standardów sieci semantycznych znajdują się m.in. OWL, RDF, RDF Schema (inaczej RDFS). Znaczenia zasobów informacyjnych określa się za pomocą tzw. ontologii.\"@pl,\n", " \"A Web semântica é uma extensão da World Wide Web atual, que permitirá aos computadores e humanos trabalharem em cooperação. A Web semântica interliga significados de palavras e, neste âmbito, tem como finalidade conseguir atribuir um significado (sentido) aos conteúdos publicados na Internet de modo que seja perceptível tanto pelo humano como pelo computador. A ideia da Web Semântica surgiu em 2001, quando Tim Berners-Lee, James Hendler e Ora Lassila publicaram um artigo na revista Scientific American, intitulado: “Web Semântica: um novo formato de conteúdo para a Web que tem significado para computadores vai iniciar uma revolução de novas possibilidades.”\"@pt,\n", " \"Семанти́ческая паути́на (англ. semantic web) — это общедоступная глобальная семантическая сеть, формируемая на базе Всемирной паутины путём стандартизации представления информации в виде, пригодном для машинной обработки.\"@ru,\n", " \"语义网（Semantic Web）是由万维网联盟的蒂姆·伯纳斯-李（Tim Berners-Lee）在1998年提出的一个概念，它的核心是：通过给万维网上的文档（如: HTML）添加能够被计算机所理解的语义（Meta data），从而使整个互联网成为一个通用的信息交换媒介。语义万维网通过使用标准、置标语言和相关的处理工具来扩展万维网的能力。不过语意网概念实际上是基于很多已有技术的，也依赖于后来和text-and-markup与知识表现的综合。那些渊源甚至可以追溯到20世纪60年代末期的Allan M. Collins、M. Ross Quillian、Elizabeth F. Loftus等人的研究，还有之后70年代初R.F.Simon、R.C.Schamk、Minsky等人陆续提出的一些理论上的成果，其中Simon在进行自然语言理解的应用研究时提出了语义网络Semantic Network（不是现在的Semantic Web）的概念。当时人们甚至发明了以逻辑为基础的程序设计语言Prolog。 \\\"语义\\\"网是由比现今成熟的网际搜索工具更加行之有效的、更加广泛意义的并且自动聚集和搜集信息的文档组成的。其最基本的元素就是语义链接。 通过下列方法可以提升全球資訊網以及其互连的资源的易用性（usability）和實用性（usefulness）：\"@zh ;\n", " owl:sameAs ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ;\n", " prov:wasDerivedFrom ;\n", " foaf:depiction ;\n", " foaf:homepage ;\n", " foaf:isPrimaryTopicOf .\n", "\n", "\n" ] } ], "source": [ "print g.serialize(format='turtle')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Для подстановки пользовательских литералов в SPARQL-запрос можно использовать сериализацию литералов `rdflib`." ] }, { "cell_type": "code", "execution_count": 162, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "u''" ] }, "execution_count": 162, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rdflib.URIRef('http://ya.ru/rdf').n3()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "u'\"1267650600228229401496703205376\"^^'" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rdflib.Literal(2 ** 100).n3()" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "u'\"hello\\x00\\\\\"\\u041f\\u0440\\u0438\\u0432\\u0435\\u0442\"@ru'" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rdflib.Literal('hello\\0\"Привет', lang='ru').n3()" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": false, "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "u'\"2018-05-18T13:32:41.819000\"^^'" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import datetime\n", "rdflib.Literal(datetime.datetime.now()).n3()" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1000\n" ] } ], "source": [ "import pymysql, pandas\n", "conn = pymysql.connect(\n", " host='localhost', user='root', password='toor', db='bookwarrior',\n", " charset='utf8mb4', cursorclass=pymysql.cursors.DictCursor)\n", "df = pandas.read_sql('SELECT * FROM updated WHERE Id <= 1000', conn)\n", "data = df.to_dict('records')\n", "print len(data)" ] }, { "cell_type": "code", "execution_count": 52, "metadata": { "collapsed": true }, "outputs": [], "source": [ "class Blazegraph:\n", " def __init__(self, endpoint='http://localhost:9999/blazegraph/namespace/kb/sparql'):\n", " self.db = SPARQLWrapper.SPARQLWrapper(endpoint)\n", " def send(self, sparql):\n", " self.db.setQuery(sparql)\n", " self.db.method = 'POST'\n", " self.db.setReturnFormat(SPARQLWrapper.JSON)\n", " return self.db.query()\n", " def from_sparql_response(self, v):\n", " if 'datatype' in v and v['datatype'] == 'http://www.w3.org/2001/XMLSchema#integer':\n", " return int(v['value'])\n", " else:\n", " return v['value']\n", " def query(self, sparql):\n", " results = self.send(sparql).convert()\n", " return [{k: self.from_sparql_response(v) for k,v in result.iteritems()} for result in results[\"results\"][\"bindings\"]]\n", " def execute(self, sparql):\n", " return self.send(sparql).response.read()" ] }, { "cell_type": "code", "execution_count": 58, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import os" ] }, { "cell_type": "code", "execution_count": 55, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Wall time: 4min 9s\n" ] } ], "source": [ "%%time\n", "bg = Blazegraph()\n", "for rec in data:\n", " subj = 'http://gen.lib.rus.ec/book/index.php?md5=%s' % rec['MD5'].upper()\n", " sparql_props = ['lg:%s %s' % (k, rdflib.Literal(v).n3()) for k, v in rec.items() if v != '']\n", " sparql = '''\n", " PREFIX lg: \n", " INSERT DATA { %s ''' % rdflib.URIRef(subj).n3() + ';\\n'.join(sparql_props) + ' . }'\n", " bg.queryUpdate(sparql)" ] }, { "cell_type": "code", "execution_count": 56, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[{u'c': 26647}]" ] }, "execution_count": 56, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bg.query('SELECT (COUNT(?s) AS ?c) WHERE { ?s ?p ?o . }')" ] }, { "cell_type": "code", "execution_count": 60, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "1184866800L" ] }, "execution_count": 60, "metadata": {}, "output_type": "execute_result" } ], "source": [ "os.path.getsize(\"C:\\\\Temp\\\\blazegraph\\\\blazegraph.jnl\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Вставка 1000 инсертами 26647 триплов 249 сек, вес БД 1.18 ГБ." ] }, { "cell_type": "code", "execution_count": 67, "metadata": { "collapsed": true }, "outputs": [], "source": [ "triples = []\n", "for i, rec in enumerate(data):\n", " subj = 'http://gen.lib.rus.ec/book/index.php?md5=%s' % rec['MD5'].upper()\n", " sparql_props = ['lg:%s %s' % (k, rdflib.Literal(v).n3()) for k, v in rec.items() if v != '']\n", " sparql = '%s ' % rdflib.URIRef(subj).n3() + ';\\n'.join(sparql_props) + ' .'\n", " triples.append(sparql)" ] }, { "cell_type": "code", "execution_count": 68, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "1000" ] }, "execution_count": 68, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(triples)" ] }, { "cell_type": "code", "execution_count": 64, "metadata": { "collapsed": false }, "outputs": [ { "ename": "KeyboardInterrupt", "evalue": "", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun_cell_magic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mu'time'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34mu''\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34mu\"bg = Blazegraph()\\nfor rec in data:\\n subj = 'http://gen.lib.rus.ec/book/index.php?md5=%s' % rec['MD5'].upper()\\n for k, v in rec.items():\\n if v != '':\\n sparql = '''\\n PREFIX lg: \\n INSERT DATA { %s %s %s . }''' % (rdflib.URIRef(subj).n3(), 'lg:%s' % k, rdflib.Literal(v).n3())\\n bg.queryUpdate(sparql)\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[1;32mC:\\Users\\User\\Anaconda2\\lib\\site-packages\\IPython\\core\\interactiveshell.pyc\u001b[0m in \u001b[0;36mrun_cell_magic\u001b[1;34m(self, magic_name, line, cell)\u001b[0m\n\u001b[0;32m 2291\u001b[0m \u001b[0mmagic_arg_s\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvar_expand\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mline\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstack_depth\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2292\u001b[0m \u001b[1;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbuiltin_trap\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2293\u001b[1;33m \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfn\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmagic_arg_s\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcell\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2294\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2295\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m\u001b[0m in \u001b[0;36mtime\u001b[1;34m(self, line, cell, local_ns)\u001b[0m\n", "\u001b[1;32mC:\\Users\\User\\Anaconda2\\lib\\site-packages\\IPython\\core\\magic.pyc\u001b[0m in \u001b[0;36m\u001b[1;34m(f, *a, **k)\u001b[0m\n\u001b[0;32m 191\u001b[0m \u001b[1;31m# but it's overkill for just that one bit of state.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 192\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mmagic_deco\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0marg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 193\u001b[1;33m \u001b[0mcall\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mlambda\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m 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6\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdb\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmethod\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'POST'\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 7\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdb\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msetReturnFormat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mSPARQLWrapper\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mJSON\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 8\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdb\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mquery\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 9\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mexecute\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m 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154\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mopener\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 155\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 156\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0minstall_opener\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mopener\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32mC:\\Users\\User\\Anaconda2\\lib\\urllib2.pyc\u001b[0m in \u001b[0;36mopen\u001b[1;34m(self, fullurl, data, timeout)\u001b[0m\n\u001b[0;32m 427\u001b[0m \u001b[0mreq\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmeth\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mreq\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 428\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 429\u001b[1;33m 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1229\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1230\u001b[0m \u001b[0mhttp_request\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mAbstractHTTPHandler\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdo_request_\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32mC:\\Users\\User\\Anaconda2\\lib\\urllib2.pyc\u001b[0m in \u001b[0;36mdo_open\u001b[1;34m(self, http_class, req, **http_conn_args)\u001b[0m\n\u001b[0;32m 1199\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1200\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1201\u001b[1;33m \u001b[0mr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mh\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgetresponse\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mbuffering\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1202\u001b[0m \u001b[1;32mexcept\u001b[0m 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\u001b[0m_UNKNOWN\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1138\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__state\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_CS_IDLE\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32mC:\\Users\\User\\Anaconda2\\lib\\httplib.pyc\u001b[0m in \u001b[0;36mbegin\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 451\u001b[0m \u001b[1;31m# read until we get a non-100 response\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 452\u001b[0m \u001b[1;32mwhile\u001b[0m \u001b[0mTrue\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 453\u001b[1;33m \u001b[0mversion\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstatus\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreason\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_read_status\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 454\u001b[0m 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\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 410\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mline\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m>\u001b[0m \u001b[0m_MAXLINE\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 411\u001b[0m \u001b[1;32mraise\u001b[0m \u001b[0mLineTooLong\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"header line\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32mC:\\Users\\User\\Anaconda2\\lib\\socket.pyc\u001b[0m in \u001b[0;36mreadline\u001b[1;34m(self, size)\u001b[0m\n\u001b[0;32m 478\u001b[0m \u001b[1;32mwhile\u001b[0m \u001b[0mTrue\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 479\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 480\u001b[1;33m \u001b[0mdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_sock\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrecv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_rbufsize\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 481\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0merror\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 482\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m==\u001b[0m \u001b[0mEINTR\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;31mKeyboardInterrupt\u001b[0m: " ] } ], "source": [ "%%time\n", "bg = Blazegraph()\n", "for rec in data:\n", " subj = 'http://gen.lib.rus.ec/book/index.php?md5=%s' % rec['MD5'].upper()\n", " for k, v in rec.items():\n", " if v != '':\n", " sparql = '''\n", " PREFIX lg: \n", " INSERT DATA { %s %s %s . }''' % (rdflib.URIRef(subj).n3(), 'lg:%s' % k, rdflib.Literal(v).n3())\n", " bg.queryUpdate(sparql)" ] }, { "cell_type": "code", "execution_count": 65, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[{u'c': 2043}]" ] }, "execution_count": 65, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bg.query('SELECT (COUNT(?s) AS ?c) WHERE { ?s ?p ?o . }')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Вставка инсертом на каждый трипл ? триплов ? сек\n", "\n", "Разосрался до 2 ГБ, почти ничего не вставив.\n", "\n", "todo Некомплиментарненько" ] }, { "cell_type": "code", "execution_count": 69, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Wall time: 31.5 s\n" ] } ], "source": [ "%%time\n", "bg = Blazegraph()\n", "step = 10\n", "for i in range(0, len(triples), step):\n", " sparql = '''\n", " PREFIX lg: \n", " INSERT DATA { ''' + '\\n'.join(triples[i : i + step]) + ''' }'''\n", " bg.queryUpdate(sparql)" ] }, { "cell_type": "code", "execution_count": 71, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[{u'c': 26647}]\n", "144700736\n" ] } ], "source": [ "print bg.query('SELECT (COUNT(?s) AS ?c) WHERE { ?s ?p ?o . }')\n", "print os.path.getsize(\"C:\\\\Temp\\\\blazegraph\\\\blazegraph.jnl\")" ] }, { "cell_type": "code", "execution_count": 80, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Wall time: 1.82 s\n" ] } ], "source": [ "%%time\n", "bg = Blazegraph()\n", "step = 100\n", "for i in range(0, len(triples), step):\n", " sparql = '''\n", " PREFIX lg: \n", " DISABLE ENTAILMENTS;\n", " INSERT DATA { ''' + '\\n'.join(triples[i : i + step]) + ''' }'''\n", " bg.queryUpdate(sparql)" ] }, { "cell_type": "code", "execution_count": 81, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[{u'c': 26555}]\n", "44039504\n" ] } ], "source": [ "print bg.query('SELECT (COUNT(?s) AS ?c) WHERE { ?s ?p ?o . }')\n", "print os.path.getsize(\"C:\\\\Temp\\\\blazegraph\\\\blazegraph.jnl\")" ] }, { "cell_type": "code", "execution_count": 86, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Wall time: 17.1 s\n" ] } ], "source": [ "%%time\n", "bg = Blazegraph()\n", "step = 1\n", "for i in range(0, len(triples), step):\n", " sparql = '''\n", " PREFIX lg: \n", " INSERT DATA { ''' + '\\n'.join(triples[i : i + step]) + ''' }'''\n", " bg.queryUpdate(sparql)" ] }, { "cell_type": "code", "execution_count": 85, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[{u'c': 26555}]\n", "1184866800\n" ] } ], "source": [ "print bg.query('SELECT (COUNT(?s) AS ?c) WHERE { ?s ?p ?o . }')\n", "print os.path.getsize(\"C:\\\\Temp\\\\blazegraph\\\\blazegraph.jnl\")" ] }, { "cell_type": "code", "execution_count": 74, "metadata": { "collapsed": false }, "outputs": [], "source": [ "g = rdflib.Graph()\n", "for i, rec in enumerate(data):\n", " for k, v in rec.items():\n", " if v != '':\n", " s = 'http://gen.lib.rus.ec/book/index.php?md5=%s' % rec['MD5'].upper()\n", " p = 'http://gen.lib.rus.ec/#%s' % k\n", " o = v\n", " g.add((rdflib.URIRef(s), rdflib.URIRef(p), rdflib.Literal(o)))" ] }, { "cell_type": "code", "execution_count": 76, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "26368" ] }, "execution_count": 76, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(g)" ] }, { "cell_type": "code", "execution_count": 79, "metadata": { "collapsed": false }, "outputs": [], "source": [ "g.serialize('libgen1000.ttl', format='turtle')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Загрузка этого файла с вкладки Update в Blazegraph Workbench: modified: 26368 milliseconds: 1888, 10.5 МБ" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Поскольку SPARQL-запросы существенно свободнее по форме по сравнению с SQL, семантическая БД при изменениях вынуждена перестраивать куда более заметное количество индексов, что приводит к скорости вставки порядка 100 триплов в секунду. Большинство осмысленных данных значительно больше, поэтому их обычно загружают в семантическую БД в пакетном режиме, из файла." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "todo как заливать в blazegraph ttl, как генерить и читать ttl из питона, как делать запросы с квадами" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "todo как запретить rules.log?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "todo Пример CONSTRUCT, парсинга rdflib, оперирования с rdflib.Graph" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Примеры запросов вставки и удаления:\n", " \n", "```sparql\n", "INSERT DATA {\n", " dc:title \"A new book\" ;\n", " dc:creator \"A.N.Other\" .\n", "}\n", "```\n", "\n", "```sparql\n", "DELETE { ?book ?p ?v } WHERE {\n", " ?book dc:date ?date .\n", " FILTER ( ?date < \"2000-01-01T00:00:00\"^^xsd:dateTime )\n", " ?book ?p ?v\n", "}\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Документы" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### PDF" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ " PyPDF2 (1.26.0)\n", " reportlab -- писать в PDF, векторная графика и все такое\n", " https://github.com/pmaupin/pdfrw pure Python library that reads and writes PDFs" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### MS Word" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "doc?\n", "\n", " pip install python-docx\n", "\n", " from docx import Document\n", " from docx.shared import Inches\n", "\n", " guestnames=['Иван', 'Олег', 'Ольга', 'Мария и Александр']\n", "\n", " for x in guestnames:\n", " document = Document()\n", " document.add_heading('Приглашение на свадьбу', 0)\n", " p = document.add_paragraph(x+', спешим пригласить Вас на свадьбу') \n", " p.add_run(' Татьяны и Дмитрия Раутенко').bold = True\n", " p.add_run(', которая состоится 12.05.2017 в усадьбе Тихая роща.')\n", " document.add_heading('Мы ждём вас, на наш праздник!!!', level=1)\n", " document.add_paragraph('')\n", " document.add_picture('1.jpg', width=Inches(5.25))\n", " document.add_page_break()\n", " document.save(x+'.docx')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### MS Excel" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ " xlrd" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### OpenDocument\n", "\n", " PyUNO" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### textract" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ " textract\n", " .doc via antiword\n", " .docx via python-docx\n", " .csv .eml .json .odt .txt via python builtins\n", " .epub via ebooklib\n", " .gif .jpg .jpeg .png .tiff .tif via tesseract-ocr\n", " .html and .htm via beautifulsoup4\n", " .mp3 .ogg .wav via SpeechRecognition and sox\n", " .msg via msg-extractor\n", " .pdf via pdftotext (default) or pdfminer.six\n", " .pptx via python-pptx\n", " .ps via ps2text\n", " .rtf via unrtf\n", " .xls .xlsx via xlrd" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### DjVu" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Для работы с популярным форматов сканов DjVu можно использовать библиотеку `python-djvulibre`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```\n", "http://djvu.sourceforge.net/ качаем Source TAR.GZ djvulibre-3.5.27.tar.gz\n", "распаковываем\n", "\n", "http://libjpeg.sourceforge.net/ распаковываем в c:\\Temp\\djvulibre-3.5.27\\win32\\jpeg\\jpeg-6b\\\n", "\n", "\"C:\\Temp\\djvulibre-3.5.27\\win32\\djvulibre\\djvulibre.sln\" билдим release x64\n", "\n", "переименовываем djvulibre-3.5.27/win32/djvulibre/x64/Release/libdjvulibre.lib в djvulibre.lib\n", "\n", "pip install python-djvulibre --global-option build_ext --global-option --compiler=msvc --global-option \"--include-dirs=c:/Temp/djvulibre-3.5.27\"\t --global-option \"--library-dirs=c:/Temp/djvulibre-3.5.27/win32/djvulibre/x64/Release\"\n", "\n", "скопировать libdjvulibre.dll и libjpeg.dll в Anaconda2\\Lib\\site-packages\\djvu\\\n", "```" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import djvu\n", "import djvu.decode\n", "import numpy" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Populating the interactive namespace from numpy and matplotlib\n" ] } ], "source": [ "%pylab inline" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": true }, "outputs": [], "source": [ "filename = 'D:\\\\(library)\\\\(__Unsorted)\\\\P. J. Plauger Programming on purpose III essays on software technology 1994.djvu'" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "3250 5010\n" ] } ], "source": [ "djvu_pixel_format = djvu.decode.PixelFormatRgbMask(0xff0000, 0xff00, 0xff, bpp=32)\n", "djvu_pixel_format.rows_top_to_bottom = 1\n", "djvu_pixel_format.y_top_to_bottom = 0\n", "img = None\n", "\n", "class Context(djvu.decode.Context):\n", " def handle_message(self, message):\n", " if isinstance(message, djvu.decode.ErrorMessage):\n", " print message\n", " # Exceptions in handle_message() are ignored, so sys.exit() wouldn't work here.\n", " os._exit(1)\n", "\n", " def process(self, djvu_path, mode):\n", " document = self.new_document(djvu.decode.FileURI(djvu_path))\n", " document.decoding_job.wait()\n", " page = document.pages[2]\n", " page_job = page.decode(wait=True)\n", " width, height = page_job.size\n", " print width, height\n", " rect = (0, 0, width, height)\n", " color_buffer = numpy.zeros((height, width), dtype=numpy.uint32)\n", " page_job.render(mode, rect, rect, djvu_pixel_format, row_alignment=1, buffer=color_buffer)\n", " return color_buffer\n", "\n", "context = Context()\n", "img = context.process(filename, djvu.decode.RENDER_COLOR) # RENDER_FOREGROUND RENDER_BACKGROUND RENDER_MASK_ONLY" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "todo что это?\n", "\n", " #mask_buffer = numpy.zeros((height, bytes_per_line), dtype=numpy.uint32)\n", " #if mode == djvu.decode.RENDER_FOREGROUND:\n", " # page_job.render(djvu.decode.RENDER_MASK_ONLY, rect, rect, djvu_pixel_format, row_alignment=1, buffer=mask_buffer)\n", " # mask_buffer <<= 24\n", " # color_buffer |= mask_buffer\n", " #color_buffer ^= 0xff000000\n", " #surface.write_to_png(png_path)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "collapsed": false }, "outputs": [], "source": [ "img3d = zeros((img.shape[0], img.shape[1], 3), dtype=uint8)\n", "img3d[:,:,0] = img >> 16\n", "img3d[:,:,1] = (img >> 8) & 0xFF\n", "img3d[:,:,2] = img & 0xFF" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "collapsed": false, "scrolled": false }, "outputs": [ { "data": { "image/png": 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K33//PVasWIGnnnoKFoul1vJOpxMnT57EihUrcObMGfVbx1deeQVNmzaFiCA/Px+ff/45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zPM3wVrRMcwDMMwDMMwrYAF1gzDMAzDMAzTClhTkFZmt9tx9uxZ5ObmYsSIEfDy8rrrdfV6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\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YwN3dvVkciVarxZ07d/DLL7+guLgYHh4emDhxIgICAozGn6HNbW1tkZubi7S0NPTt2xcm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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "figure(figsize=(16, 20))\n", "xticks([]); yticks([])\n", "imshow(img3d, interpolation='bilinear');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### OCR" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Распознать скан может помочь библиотека `pyocr`, являющаяся враппером над open-source OCR Tesseract от Google." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```\n", "скачать и поставить https://github.com/tesseract-ocr/tesseract/wiki/Downloads#binaries-for-windows\n", " указать инсталлеру скачать rus training\n", "добавить в PATH\n", "\n", "pip install pyocr\n", "```" ] }, { "cell_type": "code", "execution_count": 108, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import pyocr" ] }, { "cell_type": "code", "execution_count": 114, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Tesseract (sh) [u'eng', u'osd', u'rus']\n" ] } ], "source": [ "for tool in pyocr.get_available_tools():\n", " print tool.get_name(), tool.get_available_languages()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from PIL import Image\n", "im = Image.fromarray(img3d)" ] }, { "cell_type": "code", "execution_count": 118, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Wall time: 10.3 s\n" ] } ], "source": [ "%%time\n", "ocred = tool.image_to_string(im)" ] }, { "cell_type": "code", "execution_count": 119, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "u'Acquisitions editor: Paul Becker\\n\\nEditorial assistant: Noreen Regina\\n\\nCover design director: Eloise Starkweather\\nCover designer: Lundgren Graphics\\nManufacturing buyer: Mary E. McCartney\\n\\n\\xa91994 by P.J. Plauger\\n\\nPublished by PTR Prentice-Hall, Inc.\\nA Simon & Schuster Company\\n\\nEnglewood Cliffs, New Jersey 07632\\n\\n \\n\\nAll rights reserved. No part of this book may be reproduced,\\nin any form or by any means, without permission in writing\\nof the author.\\n\\nThe publisher offers discounts on this book when ordered in\\n\\nbulk quantities. For more information, contact Corporate Sales Department,\\nPTR Prentice Hall, 113 Sylvan Avenue, Englewood Cliffs, NJ 07632.\\nPhone: 201-592-2863; FAX: 201-592-2249.\\n\\nPrinted in the United States of America\\n10 9 8 7 6 5 4 3 2 1\\n\\nISBN - O-13-328113-2\\n\\nPrentice-Hall International (UK) Limited, London\\nPrentice-Hall of Australia, Pty. Limited, Sydney\\nPrentice-Hall Canada Inc., Toronto\\n\\nPrentice-Hall Hispanoamericana, S.A., Mexico\\nPrentice-Hall of India Private Limited, New Delhi\\nPrentice-Hall of Japan, Inc., Tokyo\\n\\nSimon & Schuster Asia Pte. Ltd., Singapore\\n\\nEditora Prentice-Hall do Brazil, Ltda., Rio de Janeiro'" ] }, "execution_count": 119, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ocred" ] }, { "cell_type": "code", "execution_count": 149, "metadata": { "collapsed": true }, "outputs": [], "source": [ "mine = u'''Acquisitions editor: Paul Becker\n", "Editorial assistant: Noreen Regina\n", "Cover design director: Eloise Starkweather\n", "Cover designer: Lundgren Graphics\n", "Manufacturing buyer: Mary E. McCartney\n", "\n", "©1994 by P.J. Plauger\n", "\n", "Published by PTR Prentice-Hall, Inc.\n", "A Simon & Schuster Company\n", "Englewood Cliffs, New Jersey 07632\n", "\n", "All rights reserved. No part of this book may be reproduced,\n", "in any form or by any means, without permission in writing\n", "of the author.\n", "\n", "The publisher offers discounts on this book when ordered in\n", "bulk quantities. For more information, contact Corporate Sales Department,\n", "PTR Prentice Hall, 113 Sylvan Avenue, Englewood Cliffs, NJ 07632.\n", "Phone: 201-592-2863; FAX: 201-592-2249.\n", "\n", "Printed in the United States of America\n", "10 9 8 7 6 5 4 3 2 1\n", "\n", "ISBN 0-13-328113-2\n", "\n", "Prentice-Hall International (UK) Limited, London\n", "Prentice-Hall of Australia, Pty. Limited, Sydney\n", "Prentice-Hall Canada Inc., Toronto\n", "Prentice-Hall Hispanoamericana, S.A., Mexico\n", "Prentice-Hall of India Private Limited, New Delhi\n", "Prentice-Hall of Japan, Inc., Tokyo\n", "Simon & Schuster Asia Pte. Ltd., Singapore\n", "Editora Prentice-Hall do Brazil, Ltda., Rio de Janeiro'''" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "У меня на перепечатку ушло 5 минут ровно" ] }, { "cell_type": "code", "execution_count": 152, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def colored_diff(s_was, s_become):\n", " import difflib\n", " from colorama import Fore, Back, Style\n", " result = []\n", " for item in difflib.Differ().compare(s_was, s_become):\n", " typ, _, ch = item\n", " if typ == ' ':\n", " result.append(ch)\n", " elif typ == '-':\n", " result.append(Fore.YELLOW + Back.RED + ch + Style.RESET_ALL + Fore.BLACK)\n", " elif typ == '+':\n", " result.append(Fore.YELLOW + Back.GREEN + ch + Style.RESET_ALL + Fore.BLACK)\n", " return ''.join(result)" ] }, { "cell_type": "code", "execution_count": 153, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Acquisitions editor: Paul Becker\n", "\u001b[33m\u001b[41m\n", "\u001b[0m\u001b[30mEditorial assistant: Noreen Regina\u001b[33m\u001b[41m\n", "\u001b[0m\u001b[30m\n", "Cover design director: Eloise Starkweather\n", "Cover designer: Lundgren Graphics\n", "Manufacturing buyer: Mary E. McCartney\n", "\n", "©1994 by P.J. Plauger\n", "\n", "Published by PTR Prentice-Hall, Inc.\n", "A Simon & Schuster Company\n", "\u001b[33m\u001b[41m\n", "\u001b[0m\u001b[30mEnglewood Cliffs, New Jersey 07632\n", "\n", "\u001b[33m\u001b[41m \u001b[0m\u001b[30m\u001b[33m\u001b[41m\n", "\u001b[0m\u001b[30m\u001b[33m\u001b[41m\n", "\u001b[0m\u001b[30mAll rights reserved. No part of this book may be reproduced,\n", "in any form or by any means, without permission in writing\n", "of the author.\n", "\n", "The publisher offers discounts on this book when ordered in\u001b[33m\u001b[41m\n", "\u001b[0m\u001b[30m\n", "bulk quantities. For more information, contact Corporate Sales Department,\n", "PTR Prentice Hall, 113 Sylvan Avenue, Englewood Cliffs, NJ 07632.\n", "Phone: 201-592-2863; FAX: 201-592-2249.\n", "\n", "Printed in the United States of America\n", "10 9 8 7 6 5 4 3 2 1\n", "\n", "ISBN \u001b[33m\u001b[42m0\u001b[0m\u001b[30m\u001b[33m\u001b[41m-\u001b[0m\u001b[30m\u001b[33m\u001b[41m \u001b[0m\u001b[30m\u001b[33m\u001b[41mO\u001b[0m\u001b[30m-13-328113-2\n", "\n", "Prentice-Hall International (UK) Limited, London\n", "Prentice-Hall of Australia, Pty. Limited, Sydney\n", "Prentice-Hall Canada Inc., Toronto\n", "\u001b[33m\u001b[41m\n", "\u001b[0m\u001b[30mPrentice-Hall Hispanoamericana, S.A., Mexico\n", "Prentice-Hall of India Private Limited, New Delhi\n", "Prentice-Hall of Japan, Inc., Tokyo\n", "\u001b[33m\u001b[41m\n", "\u001b[0m\u001b[30mSimon & Schuster Asia Pte. Ltd., Singapore\n", "\u001b[33m\u001b[41m\n", "\u001b[0m\u001b[30mEditora Prentice-Hall do Brazil, Ltda., Rio de Janeiro\n" ] } ], "source": [ "print colored_diff(ocred, mine)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Системы контроля версий" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "todo http://gitpython.readthedocs.io/en/stable/tutorial.html" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "Значительное количество информационных артефактов, особенно разрабатываемых коллективно, хранится в системах контроля версий, таких, как `git`. Для автоматизации доступа к ним существует библиотека `GitPython`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "todo Читать блоб в любом месте истории, дифф, git blame, реп посложнее? доступ по пути в tree?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```\n", "pip install GitPython\n", "```" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import git" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [], "source": [ "repo = git.Repo('c:\\\\Temp\\\\python-finediff-copy-for-gitpython')" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "False\n", "[]\n" ] } ], "source": [ "print repo.is_dirty()\n", "print repo.untracked_files" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[,\n", " ]" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "repo.refs" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "repo.tags" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "repo.heads" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "'master'" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "repo.heads.master.name" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Перечисление коммитов" ] }, { "cell_type": "code", "execution_count": 54, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "9596490bbb905d194eff4a34e2920a77dab0acea do 2018-05-24 14:53:46+03:00\n", "\"Installation\" in README.md\n", "[]\n", "\n", "abf3e7bcbd985cd1c00f2b98fac94acdec21ce8e do 2018-05-24 14:47:28+03:00\n", "initial commit\n", "\n" ] } ], "source": [ "for commit in repo.iter_commits(max_count=10):\n", " print commit, commit.author.name, commit.authored_datetime\n", " print commit.message.strip()\n", " if len(commit.parents):\n", " print commit.parents[0].diff(commit)\n", " print" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "last_master_commit = repo.refs['master'].commit\n", "last_master_commit" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Свойства коммита" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "9596490bbb905d194eff4a34e2920a77dab0acea\n", "do sharp-c@yandex.ru\n", "2018-05-24 14:53:46+03:00\n", "\n", "(,)\n", "\n", "README.md README.md\n", "251 bytes -> 354 bytes\n", "\n", "@@ -5,4 +5,10 @@ This is Python port of https://github.com/gorhill/PHP-FineDiff, library for stri\n", " import finediff\n", " finediff.FineDiff('abcdef', 'badefo').renderDiffToHTML()\n", " ```\n", "-`'abcadefo'`\n", "\\ No newline at end of file\n", "+`'abcadefo'`\n", "+\n", "+### Installation\n", "+\n", "+```bash\n", "+pip install https://github.com/sharpden/python-finediff/tarball/master\n", "+```\n", "\n" ] } ], "source": [ "print last_master_commit.hexsha\n", "print last_master_commit.author.name, last_master_commit.author.email\n", "print last_master_commit.authored_datetime\n", "print\n", "print last_master_commit.parents\n", "print\n", "for diff in last_master_commit.parents[0].diff(last_master_commit, create_patch=True):\n", " print diff.a_path, diff.b_path\n", " print '%d bytes -> %d bytes' % (len(diff.a_blob.data_stream.read()), len(diff.b_blob.data_stream.read()))\n", " print\n", " print diff.diff" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Доступ к дереву файлов конкретного коммита" ] }, { "cell_type": "code", "execution_count": 60, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 60, "metadata": {}, "output_type": "execute_result" } ], "source": [ "last_master_commit.tree" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "README.md 354\n", "'# python-finediff\\nThis is Python port of'\n", "finediff.py 16327\n", "'# -*- coding: utf-8 -*-\\n# Based on http:'\n", "setup.py 887\n", "'import sys\\nimport os\\nfrom setuptools imp'\n" ] } ], "source": [ "for blob in last_master_commit.tree.traverse():\n", " print blob.path, blob.size\n", " print repr(blob.data_stream.read()[:40])" ] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.12" } }, "nbformat": 4, "nbformat_minor": 2 }