{ "metadata": { "name": "", "signature": "sha256:8c764ebc660400cc2f2dddafacfdb7082971d16cb2b75bac1470575d33428427" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "code", "collapsed": false, "input": [ "from node.models import Node, NodeType, Language\n", "import parsing\n", "from parsing.FileParsers import *" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 1 }, { "cell_type": "code", "collapsed": false, "input": [ "#from node.models import Language\n", "#import pycountry\n", "#for lang in pycountry.languages:\n", "# try:\n", "# Language(iso2=lang.alpha2, iso3=lang.terminology, fullname=lang.name, implemented=1).save()\n", "# except:\n", "# pass" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 2 }, { "cell_type": "code", "collapsed": false, "input": [ "corpus = Node.objects.get(name=\"OneMoreLife PubMed\")\n", "print(corpus.resource.all())" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "[ corpora/alexandre/test_pkqLVdy.zip>]\n" ] } ], "prompt_number": 3 }, { "cell_type": "code", "collapsed": false, "input": [ "from node.models import Project\n", "from django.contrib.auth.models import User\n", "user = User.objects.get(username=\"alexandre\")\n", "project_type = NodeType.objects.get(name=\"Project\")\n", "Project(user=user, type=project_type, name=\"Abeilles\").save()" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 3 }, { "cell_type": "code", "collapsed": false, "input": [ "node = Node.objects.filter(name=\"Abeilles\", user=user)[0]\n", "print(node.pk)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "24\n" ] } ], "prompt_number": 28 }, { "cell_type": "code", "collapsed": false, "input": [ "r = node.children.get(name=\"Pubmed\")" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 40 }, { "cell_type": "code", "collapsed": false, "input": [ "r = r.resource.all()[0]" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 41 }, { "cell_type": "code", "collapsed": false, "input": [ "r.file" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 42, "text": [ "" ] } ], "prompt_number": 42 }, { "cell_type": "code", "collapsed": false, "input": [ "fileparser = PubmedFileParser.PubmedFileParser(file='/var/www/gargantext/media/' + str(r.file))" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 43 }, { "cell_type": "code", "collapsed": false, "input": [ "fileparser.parse(node)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Warning: parsing empty text\n", "Warning: parsing empty text\n", "Warning: parsing empty text" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "\n", "Warning: parsing empty text\n", "Warning: parsing empty text" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "\n", "Warning: parsing empty text\n", "Warning: parsing empty text" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "\n", "Warning: parsing empty text" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "\n", "Warning: parsing empty text" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "\n", "Warning: parsing empty text" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "\n", "Warning: parsing empty text" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "\n", "Warning: parsing empty text" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "\n", "Warning: parsing empty text" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "\n", "Warning: parsing empty text" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "\n", "Warning: parsing empty text" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "\n" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 44, "text": [ "[,\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", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ]" ] } ], "prompt_number": 44 }, { "cell_type": "code", "collapsed": false, "input": [ "from node.models import Ngram" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 6 }, { "cell_type": "markdown", "metadata": {}, "source": [ " Ng" ] }, { "cell_type": "raw", "metadata": {}, "source": [] }, { "cell_type": "code", "collapsed": false, "input": [ "n = node.children.first()" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 14 }, { "cell_type": "code", "collapsed": false, "input": [ "for node_ngram in n.node_ngram_set.all():\n", " print(node_ngram.ngram.terms)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n", "Ngram object\n" ] } ], "prompt_number": 26 }, { "cell_type": "code", "collapsed": false, "input": [ "Project.objects.all().delete()" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 18 }, { "cell_type": "code", "collapsed": false, "input": [ "from node.models import Corpus, Project\n", "Project.objects.all()\n", "Corpus.objects.all()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 7, "text": [ "[]" ] } ], "prompt_number": 7 }, { "cell_type": "code", "collapsed": false, "input": [ "Node.objects.filter(user=user, type=project_type)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 5, "text": [ "[]" ] } ], "prompt_number": 5 }, { "cell_type": "code", "collapsed": false, "input": [ "destruction = Node.objects.filter(id=1038).all()" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 20 }, { "cell_type": "code", "collapsed": false, "input": [ "destruction.delete()" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 21 }, { "cell_type": "code", "collapsed": false, "input": [ "destruction" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 22, "text": [ "[]" ] } ], "prompt_number": 22 }, { "cell_type": "code", "collapsed": false, "input": [ "destruction.children.all().delete()\n", "destruction.delete" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 14, "text": [ ">" ] } ], "prompt_number": 14 }, { "cell_type": "code", "collapsed": false, "input": [ "help(destruction.delete)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Help on method delete in module cte_tree.models:\n", "\n", "delete(method=None, position=None, save=True) method of node.models.Node instance\n", " Prepares the tree for deletion according to the deletion semantics\n", " specified for the :class:`CTENode` Model, and then delegates to the\n", " :class:`CTENode` superclass ``delete`` method.\n", " \n", " Default deletion `method` and `position` callable can be overridden\n", " by being supplied as arguments to this method.\n", " \n", " :param method: optionally a particular deletion method, overriding\n", " the default method specified for this model.\n", " \n", " :param position: optional callable to invoke prior to each move\n", " operation, should the delete method require any moves.\n", " \n", " :param save: optional flag indicating whether this model's\n", " :meth:`save` method should be invoked after each move operation,\n", " should the delete method require any moves.\n", "\n" ] } ], "prompt_number": 15 } ], "metadata": {} } ] }