2020-08-12 19:40:36 +00:00
{
"cells": [
{
"cell_type": "code",
2020-08-13 18:05:09 +00:00
"execution_count": null,
2020-08-12 19:40:36 +00:00
"metadata": {},
"outputs": [],
"source": [
"# Script to build Markdown pages that provide term metadata for complex vocabularies\n",
"# Steve Baskauf 2020-08-12 CC0\n",
"# This script merges static Markdown header and footer documents with term information tables (in Markdown) generated from data in the rs.tdwg.org repo from the TDWG Github site\n",
"\n",
"import re\n",
"import requests # best library to manage HTTP transactions\n",
"import csv # library to read/write/parse CSV files\n",
"import json # library to convert JSON to Python data structures\n",
"import pandas as pd\n",
"\n",
"# -----------------\n",
"# Configuration section\n",
"# -----------------\n",
"\n",
"# !!!! NOTE !!!!\n",
"# There is not currently an example of a complex vocabulary that has the column headers\n",
"# used in the sample files. In order to test this script, it uses the Audubon Core files,\n",
"# which have headers that differ from the samples. So throughout the code, there are\n",
"# pairs of lines where the default header names are commented out and the Audubon Core\n",
"# headers are not. To build a page using the sample files, you will need to reverse the\n",
"# commenting of these pairs.\n",
"\n",
"# This is the base URL for raw files from the branch of the repo that has been pushed to GitHub\n",
"githubBaseUri = 'https://raw.githubusercontent.com/tdwg/rs.tdwg.org/master/'\n",
"\n",
"headerFileName = 'termlist-header.md'\n",
"footerFileName = 'termlist-footer.md'\n",
"outFileName = '../docs/list/index.md'\n",
"\n",
"# This is a Python list of the database names of the term lists to be included in the document.\n",
"termLists = ['terms', 'iri', 'dc-for-dwc', 'dcterms-for-dwc']\n",
"#termLists = ['pathway']\n",
"\n",
"# NOTE! There may be problems unless every term list is of the same vocabulary type since the number of columns will differ\n",
"# However, there probably aren't any circumstances where mixed types will be used to generate the same page.\n",
"vocab_type = 1 # 1 is simple vocabulary, 2 is simple controlled vocabulary, 3 is c.v. with broader hierarchy\n",
"\n",
"# Terms in large vocabularies like Darwin and Audubon Cores may be organized into categories using tdwgutility_organizedInClass\n",
"# If so, those categories can be used to group terms in the generated term list document.\n",
"organized_in_categories = True\n",
"\n",
"# If organized in categories, the display_order list must contain the IRIs that are values of tdwgutility_organizedInClass\n",
"# If not organized into categories, the value is irrelevant. There just needs to be one item in the list.\n",
"display_order = ['', 'http://purl.org/dc/elements/1.1/', 'http://purl.org/dc/terms/', 'http://rs.tdwg.org/dwc/terms/Occurrence', 'http://rs.tdwg.org/dwc/terms/Organism', 'http://rs.tdwg.org/dwc/terms/MaterialSample', 'http://rs.tdwg.org/dwc/terms/Event', 'http://purl.org/dc/terms/Location', 'http://rs.tdwg.org/dwc/terms/GeologicalContext', 'http://rs.tdwg.org/dwc/terms/Identification', 'http://rs.tdwg.org/dwc/terms/Taxon', 'http://rs.tdwg.org/dwc/terms/MeasurementOrFact', 'http://rs.tdwg.org/dwc/terms/ResourceRelationship', 'http://rs.tdwg.org/dwc/terms/attributes/UseWithIRI']\n",
"display_label = ['Record level', 'Dublin Core legacy namespace', 'Dublin Core terms namespace', 'Occurrence', 'Organism', 'Material Sample', 'Event', 'Location', 'Geological Context', 'Identification', 'Taxon', 'Measurement or Fact', 'Resource Relationship', 'IRI-value terms']\n",
"display_comments = ['','','','','','','','','','','','','','']\n",
"display_id = ['record_level', 'dc', 'dcterms', 'occurrence', 'organism', 'material_sample', 'event', 'location', 'geological_context', 'identification', 'taxon', 'measurement_or_fact', 'resource_relationship', 'use_with_iri']\n",
"\n",
"#display_order = ['']\n",
"#display_label = ['Vocabulary'] # these are the section labels for the categories in the page\n",
"#display_comments = [''] # these are the comments about the category to be appended following the section labels\n",
"#display_id = ['Vocabulary'] # these are the fragment identifiers for the associated sections for the categories\n",
"\n",
"# ---------------\n",
"# Function definitions\n",
"# ---------------\n",
"\n",
"# replace URL with link\n",
"#\n",
"def createLinks(text):\n",
" def repl(match):\n",
" if match.group(1)[-1] == '.':\n",
" return '<a href=\"' + match.group(1)[:-1] + '\">' + match.group(1)[:-1] + '</a>.'\n",
" return '<a href=\"' + match.group(1) + '\">' + match.group(1) + '</a>'\n",
"\n",
" pattern = '(https?://[^\\s,;\\)\"]*)'\n",
" result = re.sub(pattern, repl, text)\n",
" return result"
]
},
{
"cell_type": "code",
2020-08-13 18:05:09 +00:00
"execution_count": null,
2020-08-12 19:40:36 +00:00
"metadata": {},
2020-08-13 18:05:09 +00:00
"outputs": [],
2020-08-12 19:40:36 +00:00
"source": [
"# ---------------\n",
"# Retrieve term list metadata from GitHub\n",
"# ---------------\n",
"\n",
"print('Retrieving term list metadata from GitHub')\n",
"term_lists_info = []\n",
"\n",
"frame = pd.read_csv(githubBaseUri + 'term-lists/term-lists.csv', na_filter=False)\n",
"for termList in termLists:\n",
" term_list_dict = {'list_iri': termList}\n",
" term_list_dict = {'database': termList}\n",
" for index,row in frame.iterrows():\n",
" if row['database'] == termList:\n",
" term_list_dict['pref_ns_prefix'] = row['vann_preferredNamespacePrefix']\n",
" term_list_dict['pref_ns_uri'] = row['vann_preferredNamespaceUri']\n",
" term_list_dict['list_iri'] = row['list']\n",
" term_lists_info.append(term_list_dict)\n",
"print(term_lists_info)\n",
"print()"
]
},
{
"cell_type": "code",
2020-08-13 18:05:09 +00:00
"execution_count": null,
2020-08-12 19:40:36 +00:00
"metadata": {},
2020-08-13 18:05:09 +00:00
"outputs": [],
2020-08-12 19:40:36 +00:00
"source": [
"# ---------------\n",
"# Create metadata table and populate using data from namespace databases in GitHub\n",
"# ---------------\n",
"\n",
"# Create column list\n",
"column_list = ['pref_ns_prefix', 'pref_ns_uri', 'term_localName', 'label', 'rdfs_comment', 'dcterms_description', 'examples', 'term_modified', 'term_deprecated', 'rdf_type', 'replaces_term', 'replaces1_term']\n",
"#column_list = ['pref_ns_prefix', 'pref_ns_uri', 'term_localName', 'label', 'definition', 'usage', 'notes', 'term_modified', 'term_deprecated', 'type']\n",
"if vocab_type == 2:\n",
" column_list += ['controlled_value_string']\n",
"elif vocab_type == 3:\n",
" column_list += ['controlled_value_string', 'skos_broader']\n",
"if organized_in_categories:\n",
" column_list.append('tdwgutility_organizedInClass')\n",
"column_list.append('version_iri')\n",
"\n",
"print('Retrieving metadata about terms from all namespaces from GitHub')\n",
"# Create list of lists metadata table\n",
"table_list = []\n",
"for term_list in term_lists_info:\n",
" # retrieve versions metadata for term list\n",
" versions_url = githubBaseUri + term_list['database'] + '-versions/' + term_list['database'] + '-versions.csv'\n",
" versions_df = pd.read_csv(versions_url, na_filter=False)\n",
" \n",
" # retrieve current term metadata for term list\n",
" data_url = githubBaseUri + term_list['database'] + '/' + term_list['database'] + '.csv'\n",
" frame = pd.read_csv(data_url, na_filter=False)\n",
" for index,row in frame.iterrows():\n",
" row_list = [term_list['pref_ns_prefix'], term_list['pref_ns_uri'], row['term_localName'], row['label'], row['rdfs_comment'], row['dcterms_description'], row['examples'], row['term_modified'], row['term_deprecated'], row['rdf_type'], row['replaces_term'], row['replaces1_term']]\n",
" #row_list = [term_list['pref_ns_prefix'], term_list['pref_ns_uri'], row['term_localName'], row['label'], row['definition'], row['usage'], row['notes'], row['term_modified'], row['term_deprecated'], row['type']]\n",
" if vocab_type == 2:\n",
" row_list += [row['controlled_value_string']]\n",
" elif vocab_type == 3:\n",
" if row['skos_broader'] =='':\n",
" row_list += [row['controlled_value_string'], '']\n",
" else:\n",
" row_list += [row['controlled_value_string'], term_list['pref_ns_prefix'] + ':' + row['skos_broader']]\n",
" if organized_in_categories:\n",
" row_list.append(row['tdwgutility_organizedInClass'])\n",
"\n",
" # Borrowed terms really don't have implemented versions. They may be lacking values for version_status.\n",
" # In their case, their version IRI will be omitted.\n",
" found = False\n",
" for vindex, vrow in versions_df.iterrows():\n",
" if vrow['term_localName']==row['term_localName'] and vrow['version_status']=='recommended':\n",
" found = True\n",
" version_iri = vrow['version']\n",
" # NOTE: the current hack for non-TDWG terms without a version is to append # to the end of the term IRI\n",
" if version_iri[len(version_iri)-1] == '#':\n",
" version_iri = ''\n",
" if not found:\n",
" version_iri = ''\n",
" row_list.append(version_iri)\n",
"\n",
" table_list.append(row_list)\n",
"\n",
"# Turn list of lists into dataframe\n",
"terms_df = pd.DataFrame(table_list, columns = column_list)\n",
"\n",
"terms_sorted_by_label = terms_df.sort_values(by='label')\n",
"#terms_sorted_by_localname = terms_df.sort_values(by='term_localName')\n",
"\n",
"# This makes sort case insensitive\n",
"terms_sorted_by_localname = terms_df.iloc[terms_df.term_localName.str.lower().argsort()]\n",
"#terms_sorted_by_localname\n",
"print('done retrieving')\n",
"print()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Run the following cell to generate an index sorted alphabetically by lowercase term local name. Omit this index if the terms have opaque local names."
]
},
{
"cell_type": "code",
2020-08-13 18:05:09 +00:00
"execution_count": null,
2020-08-12 19:40:36 +00:00
"metadata": {},
2020-08-13 18:05:09 +00:00
"outputs": [],
2020-08-12 19:40:36 +00:00
"source": [
"# ---------------\n",
"# generate the index of terms grouped by category and sorted alphabetically by lowercase term local name\n",
"# ---------------\n",
"\n",
"print('Generating term index by CURIE')\n",
"text = '### 3.1 Index By Term Name\\n\\n'\n",
"text += '(See also [3.2 Index By Label](#32-index-by-label))\\n\\n'\n",
"\n",
"text += '**Classes**\\n'\n",
"text += '\\n'\n",
"for row_index,row in terms_sorted_by_localname.iterrows():\n",
" if row['rdf_type'] == 'http://www.w3.org/2000/01/rdf-schema#Class':\n",
" curie = row['pref_ns_prefix'] + \":\" + row['term_localName']\n",
" curie_anchor = curie.replace(':','_')\n",
2020-08-13 18:03:39 +00:00
" text += '[' + curie + '](#' + curie_anchor + ') |\\n'\n",
"text = text[:len(text)-2] # remove final trailing vertical bar and newline\n",
"text += '\\n\\n' # put back removed newline\n",
2020-08-12 19:40:36 +00:00
"\n",
"for category in range(0,len(display_order)):\n",
" text += '**' + display_label[category] + '**\\n'\n",
" text += '\\n'\n",
" if organized_in_categories:\n",
" filtered_table = terms_sorted_by_localname[terms_sorted_by_localname['tdwgutility_organizedInClass']==display_order[category]]\n",
" filtered_table.reset_index(drop=True, inplace=True)\n",
" else:\n",
" filtered_table = terms_sorted_by_localname\n",
" \n",
" for row_index,row in filtered_table.iterrows():\n",
" if row['rdf_type'] != 'http://www.w3.org/2000/01/rdf-schema#Class':\n",
" curie = row['pref_ns_prefix'] + \":\" + row['term_localName']\n",
" curie_anchor = curie.replace(':','_')\n",
2020-08-13 18:03:39 +00:00
" text += '[' + curie + '](#' + curie_anchor + ') |\\n'\n",
" text = text[:len(text)-2] # remove final trailing vertical bar and newline\n",
" text += '\\n\\n' # put back removed newline\n",
"\n",
2020-08-12 19:40:36 +00:00
"index_by_name = text\n",
"\n",
"#print(index_by_name)\n",
"print()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Run the following cell to generate an index by term label"
]
},
{
"cell_type": "code",
2020-08-13 18:05:09 +00:00
"execution_count": null,
2020-08-12 19:40:36 +00:00
"metadata": {},
2020-08-13 18:05:09 +00:00
"outputs": [],
2020-08-12 19:40:36 +00:00
"source": [
"# ---------------\n",
"# generate the index of terms by label\n",
"# ---------------\n",
"\n",
"print('Generating term index by label')\n",
"text = '\\n\\n'\n",
"\n",
"# Comment out the following two lines if there is no index by local names\n",
"text = '### 3.2 Index By Label\\n\\n'\n",
"text += '(See also [3.1 Index By Term Name](#31-index-by-term-name))\\n\\n'\n",
"\n",
"text += '**Classes**\\n'\n",
"text += '\\n'\n",
"for row_index,row in terms_sorted_by_label.iterrows():\n",
" if row['rdf_type'] == 'http://www.w3.org/2000/01/rdf-schema#Class':\n",
" curie_anchor = row['pref_ns_prefix'] + \"_\" + row['term_localName']\n",
2020-08-13 18:03:39 +00:00
" text += '[' + row['label'] + '](#' + curie_anchor + ') |\\n'\n",
"text = text[:len(text)-2] # remove final trailing vertical bar and newline\n",
"text += '\\n\\n' # put back removed newline\n",
2020-08-12 19:40:36 +00:00
"\n",
"for category in range(0,len(display_order)):\n",
" if organized_in_categories:\n",
" text += '**' + display_label[category] + '**\\n'\n",
" text += '\\n'\n",
" filtered_table = terms_sorted_by_label[terms_sorted_by_label['tdwgutility_organizedInClass']==display_order[category]]\n",
" filtered_table.reset_index(drop=True, inplace=True)\n",
" else:\n",
" filtered_table = terms_sorted_by_label\n",
" \n",
" for row_index,row in filtered_table.iterrows():\n",
" if row_index == 0 or (row_index != 0 and row['label'] != filtered_table.iloc[row_index - 1].loc['label']): # this is a hack to prevent duplicate labels\n",
" if row['rdf_type'] != 'http://www.w3.org/2000/01/rdf-schema#Class':\n",
" curie_anchor = row['pref_ns_prefix'] + \"_\" + row['term_localName']\n",
2020-08-13 18:03:39 +00:00
" text += '[' + row['label'] + '](#' + curie_anchor + ') |\\n'\n",
" text = text[:len(text)-2] # remove final trailing vertical bar and newline\n",
" text += '\\n\\n' # put back removed newline\n",
"\n",
2020-08-12 19:40:36 +00:00
"index_by_label = text\n",
"print()\n",
"\n",
"#print(index_by_label)"
]
},
{
"cell_type": "code",
2020-08-13 18:05:09 +00:00
"execution_count": null,
2020-08-12 19:40:36 +00:00
"metadata": {},
2020-08-13 18:05:09 +00:00
"outputs": [],
2020-08-12 19:40:36 +00:00
"source": [
"decisions_df = pd.read_csv('https://raw.githubusercontent.com/tdwg/rs.tdwg.org/master/decisions/decisions-links.csv', na_filter=False)\n",
"\n",
"# ---------------\n",
"# generate a table for each term, with terms grouped by category\n",
"# ---------------\n",
"\n",
"print('Generating terms table')\n",
"# generate the Markdown for the terms table\n",
"text = '## 4 Vocabulary\\n'\n",
"if True:\n",
" filtered_table = terms_sorted_by_localname\n",
"\n",
"#for category in range(0,len(display_order)):\n",
"# if organized_in_categories:\n",
"# text += '### 4.' + str(category + 1) + ' ' + display_label[category] + '\\n'\n",
"# text += '\\n'\n",
"# text += display_comments[category] # insert the comments for the category, if any.\n",
"# filtered_table = terms_sorted_by_localname[terms_sorted_by_localname['tdwgutility_organizedInClass']==display_order[category]]\n",
"# filtered_table.reset_index(drop=True, inplace=True)\n",
"# else:\n",
"# filtered_table = terms_sorted_by_localname\n",
"\n",
" for row_index,row in filtered_table.iterrows():\n",
" text += '<table>\\n'\n",
" curie = row['pref_ns_prefix'] + \":\" + row['term_localName']\n",
" curieAnchor = curie.replace(':','_')\n",
" text += '\\t<thead>\\n'\n",
" text += '\\t\\t<tr>\\n'\n",
" text += '\\t\\t\\t<th colspan=\"2\"><a id=\"' + curieAnchor + '\"></a>Term Name ' + curie + '</th>\\n'\n",
" text += '\\t\\t</tr>\\n'\n",
" text += '\\t</thead>\\n'\n",
" text += '\\t<tbody>\\n'\n",
" text += '\\t\\t<tr>\\n'\n",
" text += '\\t\\t\\t<td>Term IRI</td>\\n'\n",
" uri = row['pref_ns_uri'] + row['term_localName']\n",
" text += '\\t\\t\\t<td><a href=\"' + uri + '\">' + uri + '</a></td>\\n'\n",
" text += '\\t\\t</tr>\\n'\n",
2020-08-13 18:03:39 +00:00
" text += '\\t\\t<tr>\\n'\n",
2020-08-12 19:40:36 +00:00
" text += '\\t\\t\\t<td>Modified</td>\\n'\n",
" text += '\\t\\t\\t<td>' + row['term_modified'] + '</td>\\n'\n",
" text += '\\t\\t</tr>\\n'\n",
"\n",
" if row['version_iri'] != '':\n",
" text += '\\t\\t<tr>\\n'\n",
" text += '\\t\\t\\t<td>Term version IRI</td>\\n'\n",
" text += '\\t\\t\\t<td><a href=\"' + row['version_iri'] + '\">' + row['version_iri'] + '</a></td>\\n'\n",
" text += '\\t\\t</tr>\\n'\n",
"\n",
" text += '\\t\\t<tr>\\n'\n",
" text += '\\t\\t\\t<td>Label</td>\\n'\n",
" text += '\\t\\t\\t<td>' + row['label'] + '</td>\\n'\n",
" text += '\\t\\t</tr>\\n'\n",
"\n",
" if row['term_deprecated'] != '':\n",
" text += '\\t\\t<tr>\\n'\n",
" text += '\\t\\t\\t<td></td>\\n'\n",
" text += '\\t\\t\\t<td><strong>This term is deprecated and should no longer be used.</strong></td>\\n'\n",
" text += '\\t\\t</tr>\\n'\n",
"\n",
" for dep_index,dep_row in filtered_table.iterrows():\n",
" if dep_row['replaces_term'] == uri:\n",
" text += '\\t\\t<tr>\\n'\n",
" text += '\\t\\t\\t<td>Is replaced by</td>\\n'\n",
" text += '\\t\\t\\t<td><a href=\"#' + dep_row['pref_ns_prefix'] + \"_\" + dep_row['term_localName'] + '\">' + dep_row['pref_ns_uri'] + dep_row['term_localName'] + '</a></td>\\n'\n",
" text += '\\t\\t</tr>\\n'\n",
" if dep_row['replaces1_term'] == uri:\n",
" text += '\\t\\t<tr>\\n'\n",
" text += '\\t\\t\\t<td>Is replaced by</td>\\n'\n",
" text += '\\t\\t\\t<td><a href=\"#' + dep_row['pref_ns_prefix'] + \"_\" + dep_row['term_localName'] + '\">' + dep_row['pref_ns_uri'] + dep_row['term_localName'] + '</a></td>\\n'\n",
" text += '\\t\\t</tr>\\n'\n",
"\n",
" text += '\\t\\t<tr>\\n'\n",
" text += '\\t\\t\\t<td>Definition</td>\\n'\n",
" text += '\\t\\t\\t<td>' + row['rdfs_comment'] + '</td>\\n'\n",
" #text += '\\t\\t\\t<td>' + row['definition'] + '</td>\\n'\n",
" text += '\\t\\t</tr>\\n'\n",
"\n",
" if row['dcterms_description'] != '':\n",
" #if row['notes'] != '':\n",
" text += '\\t\\t<tr>\\n'\n",
" text += '\\t\\t\\t<td>Notes</td>\\n'\n",
" text += '\\t\\t\\t<td>' + createLinks(row['dcterms_description']) + '</td>\\n'\n",
" #text += '\\t\\t\\t<td>' + createLinks(row['notes']) + '</td>\\n'\n",
" text += '\\t\\t</tr>\\n'\n",
"\n",
" if row['examples'] != '':\n",
" #if row['usage'] != '':\n",
" text += '\\t\\t<tr>\\n'\n",
" text += '\\t\\t\\t<td>Examples</td>\\n'\n",
" text += '\\t\\t\\t<td>' + createLinks(row['examples']) + '</td>\\n'\n",
" #text += '\\t\\t\\t<td>' + createLinks(row['usage']) + '</td>\\n'\n",
" text += '\\t\\t</tr>\\n'\n",
"\n",
" if vocab_type == 2 or vocab_type ==3: # controlled vocabulary\n",
" text += '\\t\\t<tr>\\n'\n",
" text += '\\t\\t\\t<td>Controlled value</td>\\n'\n",
" text += '\\t\\t\\t<td>' + row['controlled_value_string'] + '</td>\\n'\n",
" text += '\\t\\t</tr>\\n'\n",
"\n",
" if vocab_type == 3 and row['skos_broader'] != '': # controlled vocabulary with skos:broader relationships\n",
" text += '\\t\\t<tr>\\n'\n",
" text += '\\t\\t\\t<td>Has broader concept</td>\\n'\n",
" curieAnchor = row['skos_broader'].replace(':','_')\n",
" text += '\\t\\t\\t<td><a href=\"#' + curieAnchor + '\">' + row['skos_broader'] + '</a></td>\\n'\n",
" text += '\\t\\t</tr>\\n'\n",
"\n",
" text += '\\t\\t<tr>\\n'\n",
" text += '\\t\\t\\t<td>Type</td>\\n'\n",
" if row['rdf_type'] == 'http://www.w3.org/1999/02/22-rdf-syntax-ns#Property':\n",
" #if row['type'] == 'http://www.w3.org/1999/02/22-rdf-syntax-ns#Property':\n",
" text += '\\t\\t\\t<td>Property</td>\\n'\n",
" elif row['rdf_type'] == 'http://www.w3.org/2000/01/rdf-schema#Class':\n",
" #elif row['type'] == 'http://www.w3.org/2000/01/rdf-schema#Class':\n",
" text += '\\t\\t\\t<td>Class</td>\\n'\n",
" elif row['rdf_type'] == 'http://www.w3.org/2004/02/skos/core#Concept':\n",
" #elif row['type'] == 'http://www.w3.org/2004/02/skos/core#Concept':\n",
" text += '\\t\\t\\t<td>Concept</td>\\n'\n",
" else:\n",
" text += '\\t\\t\\t<td>' + row['rdf_type'] + '</td>\\n' # this should rarely happen\n",
" #text += '\\t\\t\\t<td>' + row['type'] + '</td>\\n' # this should rarely happen\n",
" text += '\\t\\t</tr>\\n'\n",
"\n",
" # Look up decisions related to this term\n",
" for drow_index,drow in decisions_df.iterrows():\n",
" if drow['linked_affected_resource'] == uri:\n",
" text += '\\t\\t<tr>\\n'\n",
" text += '\\t\\t\\t<td>Executive Committee decision</td>\\n'\n",
" text += '\\t\\t\\t<td><a href=\"http://rs.tdwg.org/decisions/' + drow['decision_localName'] + '\">http://rs.tdwg.org/decisions/' + drow['decision_localName'] + '</a></td>\\n'\n",
" text += '\\t\\t</tr>\\n' \n",
"\n",
" text += '\\t</tbody>\\n'\n",
" text += '</table>\\n'\n",
" text += '\\n'\n",
" text += '\\n'\n",
"term_table = text\n",
"print('done generating')\n",
"print()\n",
"\n",
"#print(term_table)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Modify to display the indices that you want"
]
},
{
"cell_type": "code",
2020-08-13 18:05:09 +00:00
"execution_count": null,
2020-08-12 19:40:36 +00:00
"metadata": {},
2020-08-13 18:05:09 +00:00
"outputs": [],
2020-08-12 19:40:36 +00:00
"source": [
"# ---------------\n",
"# Merge term table with header and footer Markdown, then save file\n",
"# ---------------\n",
"\n",
"print('Merging term table with header and footer and saving file')\n",
"#text = index_by_label + term_table\n",
"text = index_by_name + index_by_label + term_table"
]
},
{
"cell_type": "code",
2020-08-13 18:05:09 +00:00
"execution_count": null,
2020-08-12 19:40:36 +00:00
"metadata": {},
2020-08-13 18:05:09 +00:00
"outputs": [],
2020-08-12 19:40:36 +00:00
"source": [
"# read in header and footer, merge with terms table, and output\n",
"\n",
"headerObject = open(headerFileName, 'rt', encoding='utf-8')\n",
"header = headerObject.read()\n",
"headerObject.close()\n",
"\n",
"footerObject = open(footerFileName, 'rt', encoding='utf-8')\n",
"footer = footerObject.read()\n",
"footerObject.close()\n",
"\n",
"output = header + text + footer\n",
"outputObject = open(outFileName, 'wt', encoding='utf-8')\n",
"outputObject.write(output)\n",
"outputObject.close()\n",
" \n",
"print('done')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.7.1"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
