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‎.github/update.py

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import urllib.request
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import re
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import os
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import json5
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import xml.etree.ElementTree as ET
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from mdutils.mdutils import MdUtils
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import pandas as pd
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def get_languages():
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with urllib.request.urlopen('https://raw.githubusercontent.com/vcmi/vcmi/develop/lib/Languages.h') as f:
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src = f.read().decode('utf-8')
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languages = [x for x in re.findall(r"{ ?\"([\w]*)?\" ?,", src, re.IGNORECASE) if "other" not in x]
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return languages
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def get_base_mod():
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return json5.loads(urllib.request.urlopen('https://raw.githubusercontent.com/vcmi/vcmi/develop/Mods/vcmi/mod.json').read())
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def base_mod_existing(languages):
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vcmi_base_mod = get_base_mod()
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return {value:(value in vcmi_base_mod) for value in languages}
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def base_mod_ratio(languages):
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base_mod = get_base_mod()
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translation_english = json5.loads(urllib.request.urlopen('https://raw.githubusercontent.com/vcmi/vcmi/develop/Mods/vcmi/' + base_mod["translations"][0]).read())
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data = {}
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for language in [key for key, value in base_mod_existing(languages).items() if value == True]:
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translation = json5.loads(urllib.request.urlopen('https://raw.githubusercontent.com/vcmi/vcmi/develop/Mods/vcmi/' + next(value for key, value in base_mod.items() if key == language)["translations"][0]).read())
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count_equal = 0
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count_difference = 0
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count_only_english = 0
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for key, value in translation_english.items():
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if key not in translation:
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count_only_english += 1
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continue
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if translation[key] == value:
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count_equal += 1
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else:
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count_difference += 1
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ratio = (count_difference + count_equal) / len(translation_english)
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data[language] = {"ratio": ratio, "count_equal": count_equal, "count_difference": count_difference, "count_only_english": count_only_english}
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return data
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def get_mod_repo():
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settings_schema = json5.loads(urllib.request.urlopen("https://raw.githubusercontent.com/vcmi/vcmi/develop/config/schemas/settings.json").read())
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vcmi_mod_url = settings_schema["properties"]["launcher"]["properties"]["defaultRepositoryURL"]["default"]
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vcmi_mods = json5.loads(urllib.request.urlopen(vcmi_mod_url).read())
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return vcmi_mods
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def get_translation_mods():
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vcmi_translation_mods = {}
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vcmi_mods = get_mod_repo()
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for key, value in vcmi_mods.items():
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url = value["mod"].replace(" ", "%20")
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mod = json5.loads(urllib.request.urlopen(url).read())
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if "language" in mod:
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vcmi_translation_mods[mod["language"]] = (url, mod)
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return vcmi_translation_mods
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def get_translation_mods_translation():
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translation_mods = get_translation_mods()
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data = {}
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for key, value in translation_mods.items():
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tmp = {}
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for item in value[1]["translations"]:
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base_url = value[0].rsplit('/', 1)[0] + "/content/"
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try:
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tmp_str = urllib.request.urlopen(base_url + item).read()
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except:
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tmp_str = urllib.request.urlopen((base_url + item).replace("content", "Content").replace("config", "Config")).read()
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tmp |= json5.loads(tmp_str)
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data[key] = tmp
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return data
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def translation_mod_ratio(translation_mods_translation):
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translation_english = translation_mods_translation["english"]
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data = {}
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for language in [key for key, value in translation_mods_translation.items() if key != "english"]:
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data_ns = {}
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namespaces = [None, "map", "campaign"]
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for namespace in namespaces:
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translation = translation_mods_translation[language]
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count_equal = 0
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count_difference = 0
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count_only_english = 0
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for key, value in translation_english.items():
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if key.split(".", 1)[0] == namespace or (namespace == None and key.split(".", 1)[0] not in namespaces):
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if key not in translation:
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count_only_english += 1
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continue
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if translation[key] == value:
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count_equal += 1
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else:
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count_difference += 1
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ratio = (count_difference + count_equal) / (count_only_english + count_difference + count_equal)
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data_ns[namespace] = {"ratio": ratio, "count_equal": count_equal, "count_difference": count_difference, "count_only_english": count_only_english}
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data[language] = data_ns
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return data
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def get_qt_translations(languages):
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data = {}
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for language in [key for key, value in base_mod_existing(languages).items() if value == True]:
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data_type = {}
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for type in ["mapeditor", "launcher"]:
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count_translated = 0
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count_untranslated = 0
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tmp_str = urllib.request.urlopen("https://raw.githubusercontent.com/vcmi/vcmi/develop/" + type + "/translation/" + language + ".ts").read()
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root = ET.fromstring(tmp_str)
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for item_context in root.iter('context'):
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for item_message in item_context.iter('message'):
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if list(item_message.iter('translation'))[0].get("type") == None:
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count_translated += 1
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else:
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count_untranslated += 1
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ratio = (count_translated) / (count_translated + count_untranslated)
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data_type[type] = {"ratio": ratio, "count_translated": count_translated, "count_untranslated": count_untranslated}
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data[language] = data_type
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return data
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def get_mod_translations(languages):
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vcmi_mods = get_mod_repo()
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data = {}
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for key, value in vcmi_mods.items():
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url = value["mod"].replace(" ", "%20")
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mod = json5.loads(urllib.request.urlopen(url).read())
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if "language" not in mod:
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found_languages = []
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for language in languages:
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if language in mod:
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found_languages.append(language)
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data[key] = found_languages
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return data
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def create_md():
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languages = get_languages()
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languages_translate = [x for x in languages if x != "english"]
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md = MdUtils(file_name='_')
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def format_value(percent):
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if percent < 0.7:
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return "$\\color{red}{\\textsf{" + str(round(percent * 100, 1)) + " \\%" + "}}$"
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elif percent < 0.9:
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return "$\\color{yellow}{\\textsf{" + str(round(percent * 100, 1)) + " \\%" + "}}$"
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else:
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return "$\\color{green}{\\textsf{" + str(round(percent * 100, 1)) + " \\%" + "}}$"
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md.new_header(level=1, title="VCMI translations")
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md.new_line("This tables shows the current translation progress of VCMI. Contains only the state of the translation strings, not for the assets.")
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md.new_header(level=2, title="Main translation")
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tmp = base_mod_ratio(languages_translate)
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df = pd.DataFrame({"Area": "Main-Repo"} | {x:([format_value(tmp[x]["ratio"])] if x in tmp else [format_value(0)]) for x in languages_translate})
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tmp = translation_mod_ratio(get_translation_mods_translation())
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for area in list(tmp.values())[0].keys():
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df = pd.concat([df, pd.DataFrame({"Area": "Mod-Repo" + (' main' if area == None else ' ' + area)} | {x:([format_value(tmp[x][area]["ratio"])] if x in tmp else [format_value(0)]) for x in languages_translate})], ignore_index=True)
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df = df.T.reset_index().T
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md.new_table(columns=df.shape[1], rows=df.shape[0], text=df.to_numpy().flatten(), text_align='center')
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md.new_header(level=2, title="QT tools translation")
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tmp = get_qt_translations(languages_translate)
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df = pd.DataFrame(columns=["Tool"] + languages_translate)
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for tool in list(tmp.values())[0].keys():
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df = pd.concat([df, pd.DataFrame({"Tool": tool} | {x:[format_value(tmp[x][tool]["ratio"])] if x in tmp else [format_value(0)] for x in languages_translate})], ignore_index=True)
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df = df.T.reset_index().T
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md.new_table(columns=df.shape[1], rows=df.shape[0], text=df.to_numpy().flatten(), text_align='center')
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md.new_header(level=2, title="Mod translations")
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tmp = get_mod_translations(languages_translate)
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df = pd.DataFrame(columns=["Mod"] + languages_translate)
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for mod in tmp:
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df = pd.concat([df, pd.DataFrame({"Mod": mod} | {x:["x" if x in tmp[mod] else ""] for x in languages_translate})], ignore_index=True)
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df = df.T.reset_index().T
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md.new_table(columns=df.shape[1], rows=df.shape[0], text=df.to_numpy().flatten(), text_align='center')
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return md.get_md_text()
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if __name__ == "__main__":
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with open(os.path.join('.', 'README.md'), "w") as f:
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f.write(create_md())

‎.github/workflows/main.yml

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name: VCMI translations status
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on:
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push:
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branches:
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- main
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pull_request:
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paths:
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- "**.py"
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schedule:
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- cron: '0 2 * * 0'
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workflow_dispatch:
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jobs:
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update_status:
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runs-on: ubuntu-latest
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defaults:
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run:
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shell: bash
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steps:
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- uses: actions/checkout@v3
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- name: update status
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run: |
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python3 -m pip install -r requirements.txt
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python3 .github/update.py
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- name: Commit changes
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uses: EndBug/add-and-commit@v9
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with:
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default_author: github_actions
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message: Update status
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add: '*.md'

‎LICENSE

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This is free and unencumbered software released into the public domain.
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Anyone is free to copy, modify, publish, use, compile, sell, or
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distribute this software, either in source code form or as a compiled
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binary, for any purpose, commercial or non-commercial, and by any
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means.
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In jurisdictions that recognize copyright laws, the author or authors
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of this software dedicate any and all copyright interest in the
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software to the public domain. We make this dedication for the benefit
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of the public at large and to the detriment of our heirs and
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successors. We intend this dedication to be an overt act of
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relinquishment in perpetuity of all present and future rights to this
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software under copyright law.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
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MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
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IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR
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OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
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ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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OTHER DEALINGS IN THE SOFTWARE.
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For more information, please refer to <https://unlicense.org>

‎requirements.txt

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json5==0.9.11
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pandas==1.5.3
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mdutils==1.6.0

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