mirror of
https://github.com/ISEAL-Community/iseal-core.git
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197 lines
6.9 KiB
Python
Executable File
197 lines
6.9 KiB
Python
Executable File
#!/usr/bin/env python3
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#
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# generate-hugo-content.py v0.0.1
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#
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# SPDX-License-Identifier: GPL-3.0-only
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import argparse
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import os
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import re
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import sys
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from shutil import rmtree
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import pandas as pd
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def parseSchema(schema_df):
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# Iterate over all rows (the "index, row" syntax allows us to access column
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# headings in each row, which isn't possible if we just do row).
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for index, row in schema_df.iterrows():
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element_name = row["element name"]
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# Make sure element name is URL friendly because we need to use it in
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# the file system and in the URL.
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#
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# Replace two or more whitespaces with one
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element_name = re.sub(r"\s{2,}", " ", element_name)
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# Replace unnecessary stuff in some element names (I should tell Peter
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# that these belong in the description)
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element_name = re.sub(r"\s?\(\w+\)", "", element_name)
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# Remove commas and question marks
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element_name = re.sub(r"[,?]", "", element_name)
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# Replace ": " with a dash (as in "Evaluation: ")
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element_name = element_name.replace(": ", "-")
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# Replace " / " with a dash (as in "biome / zone")
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element_name = element_name.replace(" / ", "-")
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# Replace whitespace, colons, and slashes with dashes
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element_name = re.sub(r"[\s/]", "-", element_name)
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# Lower case it
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element_name = element_name.lower()
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# Strip just in case
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element_name = element_name.strip()
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# For example Certifying Body, FSC audit, Certificate, etc
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cluster = row["idss element cluster"].capitalize()
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# For example Assurance, Certification, Core, Impact, etc
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module = row["idss schema module"].capitalize()
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# Generate a "safe" version of the element name for use in URLs and
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# files by combining the cluster and the element name. This could
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# change in the future.
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element_name_safe = cluster.replace(" ", "-").lower() + "-" + element_name
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print(f"element name: {element_name_safe}")
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# Create output directory for term using the URL-safe version
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outputDirectory = f"site/content/terms/{element_name_safe}"
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os.makedirs(outputDirectory, mode=0o755, exist_ok=True)
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if args.debug:
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print(f"Created terms directory: site/content/terms/{element_name_safe}")
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# Take the element description as is, but remove quotes
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element_description = row["element description"].replace("'", "")
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# Take the element guidance as is
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if row["element guidance"]:
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comment = row["element guidance"]
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else:
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comment = False
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example = row["element link for more information"]
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# How to use these in the HTML, slightly overlapping?
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cardinality = row["element options"].capitalize()
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prop_type = row["element type"].capitalize()
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if row["element controlled values or terms"]:
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controlled_vocab = True
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exportVocabulary(
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row["element controlled values or terms"], element_name_safe
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)
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else:
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controlled_vocab = False
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if row["mandatory?"] == "MANDATORY":
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required = True
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else:
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required = False
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if row["dspace field name"] is not None and row["dspace field name"] != "":
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dspace_field_name = row["dspace field name"]
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else:
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dspace_field_name = False
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# Combine element type and options into a "policy" of sorts and convert
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# them to sentence case because they are ALL CAPS in the Excel. We don't
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# need to do any checks because these fields should always exist.
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policy = f'{row["element type"].capitalize()}. {row["element options"].capitalize()}.'
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if args.debug:
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print(f"Processed: {row['element name']}")
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# Create an empty list with lines we'll write to the term's index.md in
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# TOML frontmatter format for Hugo.
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indexLines = []
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indexLines.append("---\n")
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# Use the full title for now (even though it's ugly). Better to fix the
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# schema spreadsheet than try to process the title here.
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indexLines.append("title: '" + row["element name"] + "'\n")
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if dspace_field_name:
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indexLines.append(f"field: '{dspace_field_name}'\n")
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indexLines.append(f"slug: '{element_name_safe}'\n")
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if element_description:
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indexLines.append(f"description: '{element_description}'\n")
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if comment:
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indexLines.append(f"comment: '{comment}'\n")
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indexLines.append(f"required: {required}\n")
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if controlled_vocab:
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indexLines.append(f"vocabulary: '{element_name_safe}.txt'\n")
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if module:
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indexLines.append(f"module: '{module}'\n")
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if cluster:
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indexLines.append(f"cluster: '{cluster}'\n")
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indexLines.append(f"policy: '{policy}'\n")
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## TODO: use some real date...?
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# indexLines.append(f"date: '2019-05-04T00:00:00+00:00'\n")
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indexLines.append("---")
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with open(f"site/content/terms/{element_name_safe}/index.md", "w") as f:
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f.writelines(indexLines)
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def exportVocabulary(vocabulary: str, element_name_safe: str):
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# Create an empty list where we'll add all the values (we don't need to do
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# it this way, but using a list allows us to de-duplicate the values).
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controlledVocabularyLines = []
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for value in vocabulary.split("||"):
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if value not in controlledVocabularyLines:
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controlledVocabularyLines.append(value)
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with open(
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f"site/content/terms/{element_name_safe}/{element_name_safe}.txt", "w"
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) as f:
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for value in controlledVocabularyLines:
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f.write(f"{value}\n")
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if args.debug:
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print(f"Exported controlled vocabulary: {element_name_safe}")
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parser = argparse.ArgumentParser(
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description="Parse an ISEAL schema Excel file to produce documentation about metadata requirements."
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)
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parser.add_argument(
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"--clean",
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help="Clean output directory before building.",
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action="store_true",
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)
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parser.add_argument(
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"-d",
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"--debug",
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help="Print debug messages.",
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action="store_true",
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)
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parser.add_argument(
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"-i",
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"--input-file",
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help="Path to schema fields file (schema-fields.csv).",
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required=True,
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type=argparse.FileType("r"),
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)
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args = parser.parse_args()
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if args.clean:
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if args.debug:
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print(f"Cleaning terms output directory")
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rmtree("site/content/terms", ignore_errors=True)
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if args.debug:
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print(f"Creating terms output directory")
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# Make sure content directory exists. This is where we will deposit all the term
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# metadata and controlled vocabularies for Hugo to process.
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os.makedirs("site/content/terms", mode=0o755, exist_ok=True)
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if args.debug:
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print(f"Opening {args.input_file.name}")
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df = pd.read_csv(args.input_file.name)
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# Added inplace=True
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df.dropna(how="all", axis=1, inplace=True)
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df.fillna("", inplace=True)
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parseSchema(df)
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