{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Execute notebooks\n",
    "\n",
    "This notebook executes all phconvert notebooks to automate testing.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "from pathlib import Path\n",
    "\n",
    "import nbformat\n",
    "from nbconvert.preprocessors import ExecutePreprocessor\n",
    "from IPython.display import display, FileLink\n",
    "\n",
    "\n",
    "def run_notebook(in_filepath, run_path=None, out_dir=None, out_suffix=''):\n",
    "    \"\"\"Runs the notebook `notebook_name` (file name with no extension).\n",
    "\n",
    "    This function executes notebook with name `notebook_name` (no extension)\n",
    "    and saves the fully executed notebook in a new file appending \"-out\"\n",
    "    to the original file name.\n",
    "\n",
    "    It also displays links to the original and executed notebooks.\n",
    "    \"\"\"\n",
    "    if not in_filepath.is_file():\n",
    "        raise IOError('File \"%s\" not found.' % in_filepath)\n",
    "    in_filepath = in_filepath.resolve()\n",
    "    \n",
    "    if run_path is None:\n",
    "        run_path = str(in_filepath.parent)\n",
    "    \n",
    "    if out_dir is None:\n",
    "        out_dir = in_filepath.parent\n",
    "    else:\n",
    "        out_dir = Path(out_dir).resolve()\n",
    "       \n",
    "    out_filepath = Path(out_dir, \"%s%s.ipynb\" % (in_filepath.stem, out_suffix))\n",
    "    \n",
    "    nb = nbformat.read(in_filepath.open(), as_version=4)\n",
    "    ep = ExecutePreprocessor(timeout = 3600)\n",
    "\n",
    "    try:\n",
    "        out = ep.preprocess(nb, {'metadata': {'path': run_path}})\n",
    "    except Exception:\n",
    "        msg = 'Error executing the notebook \"%s\".\\n\\n' % in_filepath\n",
    "        msg += 'See notebook \"%s\" for the traceback.' % out_filepath\n",
    "        print(msg)\n",
    "        raise\n",
    "    finally:\n",
    "        nbformat.write(nb, out_filepath.open(mode='wt'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "## Monkey patch needed until nbconvert > 4.0.0 is released\n",
    "## https://github.com/jupyter/nbconvert/releases\n",
    "\n",
    "from nbformat.v4 import output_from_msg\n",
    "from nbconvert.preprocessors.execute import CellExecutionError\n",
    "from textwrap import dedent\n",
    "\n",
    "def preprocess_cell(self, cell, resources, cell_index):\n",
    "    \"\"\"\n",
    "    Apply a transformation on each code cell. See base.py for details.\n",
    "    \"\"\"\n",
    "    if cell.cell_type != 'code':\n",
    "        return cell, resources\n",
    "\n",
    "    outputs = self.run_cell(cell)\n",
    "    cell.outputs = outputs\n",
    "\n",
    "    if not self.allow_errors:\n",
    "        for out in outputs:\n",
    "            if out.output_type == 'error':\n",
    "                pattern = \"\"\"\\\n",
    "                An error occurred while executing the following cell:\n",
    "                ------------------\n",
    "                {cell.source}\n",
    "                ------------------\n",
    "\n",
    "                {out.ename}: {out.evalue}\n",
    "                \"\"\"\n",
    "                msg = dedent(pattern).format(out=out, cell=cell)\n",
    "                raise CellExecutionError(msg)            \n",
    "    return cell, resources\n",
    "\n",
    "def run_cell(self, cell):\n",
    "    msg_id = self.kc.execute(cell.source)\n",
    "    self.log.debug(\"Executing cell:\\n%s\", cell.source)\n",
    "    # wait for finish, with timeout\n",
    "    while True:\n",
    "        try:\n",
    "            msg = self.kc.shell_channel.get_msg(timeout=self.timeout)\n",
    "        except Empty:\n",
    "            self.log.error(\"\"\"Timeout waiting for execute reply (%is).\n",
    "            If your cell should take longer than this, you can increase the timeout with:\n",
    "\n",
    "                c.ExecutePreprocessor.timeout = SECONDS\n",
    "\n",
    "            in jupyter_nbconvert_config.py\n",
    "            \"\"\" % self.timeout)\n",
    "            if self.interrupt_on_timeout:\n",
    "                self.log.error(\"Interrupting kernel\")\n",
    "                self.km.interrupt_kernel()\n",
    "                break\n",
    "            else:\n",
    "                try:\n",
    "                    exception = TimeoutError\n",
    "                except NameError:\n",
    "                    exception = RuntimeError\n",
    "                raise exception(\"Cell execution timed out, see log\"\n",
    "                                \" for details.\")\n",
    "\n",
    "        if msg['parent_header'].get('msg_id') == msg_id:\n",
    "            break\n",
    "        else:\n",
    "            # not our reply\n",
    "            continue\n",
    "\n",
    "    outs = []\n",
    "\n",
    "    while True:\n",
    "        try:\n",
    "            msg = self.kc.iopub_channel.get_msg(timeout=self.timeout)\n",
    "        except Empty:\n",
    "            self.log.warn(\"Timeout waiting for IOPub output\")\n",
    "            break\n",
    "        if msg['parent_header'].get('msg_id') != msg_id:\n",
    "            # not an output from our execution\n",
    "            continue\n",
    "\n",
    "        msg_type = msg['msg_type']\n",
    "        self.log.debug(\"output: %s\", msg_type)\n",
    "        content = msg['content']\n",
    "\n",
    "        # set the prompt number for the input and the output\n",
    "        if 'execution_count' in content:\n",
    "            cell['execution_count'] = content['execution_count']\n",
    "\n",
    "        if msg_type == 'status':\n",
    "            if content['execution_state'] == 'idle':\n",
    "                break\n",
    "            else:\n",
    "                continue\n",
    "        elif msg_type == 'execute_input':\n",
    "            continue\n",
    "        elif msg_type == 'clear_output':\n",
    "            outs = []\n",
    "            continue\n",
    "        elif msg_type.startswith('comm'):\n",
    "            continue\n",
    "\n",
    "        try:\n",
    "            out = output_from_msg(msg)\n",
    "        except ValueError:\n",
    "            self.log.error(\"unhandled iopub msg: \" + msg_type)\n",
    "        else:\n",
    "            outs.append(out)\n",
    "\n",
    "    return outs\n",
    "\n",
    "ExecutePreprocessor.preprocess_cell = preprocess_cell\n",
    "ExecutePreprocessor.run_cell = run_cell"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pathlist = list(f for f in Path('../notebooks').glob('*.ipynb') if not f.name.startswith('_'))\n",
    "pathlist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for nbpath in pathlist:\n",
    "    print(nbpath.stem)\n",
    "    run_notebook(nbpath, out_dir=Path(nbpath.parent, 'out'))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}