2020-10-19 03:42:32 +00:00
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Script to build Markdown pages that provide term metadata for simple vocabularies\n",
"# Steve Baskauf 2020-06-28 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",
"# Note: this script calls a function from http_library.py, which requires importing the requests, csv, and json modules\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",
"# This is an example of a simple vocabulary without categories. For a complex example\n",
"# with multiple namespaces and several categories, see build-page-categories.ipynb\n",
"\n",
"# This is the base URL for raw files from the branch of the repo that has been pushed to GitHub. In this example,\n",
"# the branch is named \"pathway\"\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/pw/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 = ['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 = 3 # 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 = False\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 = ['']\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",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"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)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Create column list\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",
"# 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['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",
"terms_sorted_by_label"
]
},
{
"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",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# generate the index of terms grouped by category and sorted alphabetically by lowercase term local name\n",
"\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",
"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",
" filtered_table.reset_index(drop=True, inplace=True)\n",
" \n",
" for row_index,row in filtered_table.iterrows():\n",
" curie = row['pref_ns_prefix'] + \":\" + row['term_localName']\n",
" curie_anchor = curie.replace(':','_')\n",
" text += '[' + curie + '](#' + curie_anchor + ')'\n",
" if row_index < len(filtered_table) - 1:\n",
" text += ' |'\n",
" text += '\\n'\n",
" text += '\\n'\n",
"index_by_name = text\n",
"\n",
"print(index_by_name)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Run the following cell to generate an index by term label"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"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",
"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",
" filtered_table.reset_index(drop=True, inplace=True)\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",
" curie_anchor = row['pref_ns_prefix'] + \"_\" + row['term_localName']\n",
" text += '[' + row['label'] + '](#' + curie_anchor + ')'\n",
" if row_index < len(filtered_table) - 2 or (row_index == len(filtered_table) - 2 and row['label'] != filtered_table.iloc[row_index + 1].loc['label']):\n",
" text += ' |'\n",
" text += '\\n'\n",
" text += '\\n'\n",
"index_by_label = text\n",
"\n",
"print(index_by_label)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"decisions_df = pd.read_csv('https://raw.githubusercontent.com/tdwg/rs.tdwg.org/master/decisions/decisions-links.csv', na_filter=False)\n",
"\n",
"# generate a table for each term, with terms grouped by category\n",
"\n",
"# generate the Markdown for the terms table\n",
"text = '## 4 Vocabulary\\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",
" filtered_table.reset_index(drop=True, inplace=True)\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",
2020-10-29 12:38:09 +00:00
" text += '\\t\\t<tr>\\n'\n",
2020-10-19 03:42:32 +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",
" text += '\\t\\t<tr>\\n'\n",
" text += '\\t\\t\\t<td>Definition</td>\\n'\n",
" text += '\\t\\t\\t<td>' + row['definition'] + '</td>\\n'\n",
" text += '\\t\\t</tr>\\n'\n",
"\n",
" if row['usage'] != '':\n",
" text += '\\t\\t<tr>\\n'\n",
" text += '\\t\\t\\t<td>Usage</td>\\n'\n",
" text += '\\t\\t\\t<td>' + createLinks(row['usage']) + '</td>\\n'\n",
" text += '\\t\\t</tr>\\n'\n",
"\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['notes']) + '</td>\\n'\n",
" text += '\\t\\t</tr>\\n'\n",
"\n",
" if (vocab_type == 2 or vocab_type == 3) and row['controlled_value_string'] != '': # 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['type'] == 'http://www.w3.org/1999/02/22-rdf-syntax-ns#Property':\n",
" text += '\\t\\t\\t<td>Property</td>\\n'\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['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['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",
"\n",
"print(term_table)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Modify to display the indices that you want"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"text = index_by_label + term_table\n",
"#text = index_by_name + index_by_label + term_table"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"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": []
}
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