{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%%python module GraphLibrary\n", "\n", "from robot.api import logger\n", "\n", "import io\n", "import urllib\n", "import base64\n", "import matplotlib.pyplot as plt\n", "\n", "\n", "class GraphLibrary:\n", " def log_as_graph(self, *args):\n", " \"\"\"Log list of values as a graph\"\"\"\n", " buffer = io.BytesIO()\n", " # Plot\n", " plt.plot(list(map(float, *args)))\n", " plt.savefig(buffer, format='png')\n", " plt.clf()\n", " # Log\n", " uri = 'data:image/png;base64,' + \\\n", " urllib.parse.quote(base64.b64encode(buffer.getvalue()))\n", " html = ''\n", " logger.info(html, html=True)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "

Log | Report

" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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" }, "metadata": { "image/png": { "height": 288, "width": 432 } }, "output_type": "display_data" } ], "source": [ "*** Settings ***\n", "\n", "Library GraphLibrary\n", "\n", "*** Tasks ***\n", "\n", "Show a graph\n", " ${series}= Create list 5 5 5 5 5 5 4 10 2 5 5 5 5 5\n", " Log as graph ${series}" ] } ], "metadata": { "kernelspec": { "display_name": "Robot Framework", "language": "robotframework", "name": "robotkernel" }, "language_info": { "codemirror_mode": "robotframework", "file_extension": ".robot", "mimetype": "text/plain", "name": "Robot Framework", "pygments_lexer": "robotframework" }, "widgets": { "application/vnd.jupyter.widget-state+json": { "state": {}, "version_major": 2, "version_minor": 0 } } }, "nbformat": 4, "nbformat_minor": 4 }