mirror of
https://github.com/firmai/financial-machine-learning.git
synced 2026-07-27 18:57:54 +00:00
Bin Yang
86 lines
3.7 KiB
Python
86 lines
3.7 KiB
Python
from conf import PROJECT_ROOT_DIR
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import os
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import pandas as pd
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import numpy as np
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import re
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from git_status import get_repo_list
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def get_wiki_status_color(input_text):
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if input_text is None or input_text == 'inactive':
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result_text = ":heavy_multiplication_x:"
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else:
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result_text = ":heavy_check_mark:"
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return '<sub>{}</sub>'.format(result_text)
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def get_wiki_rating(input_rating):
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result_text = ''
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if input_rating is not None and not np.isnan(input_rating):
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rating = int(input_rating)
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result_text = ':star:x{}'.format(rating)
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return '<sub>{}</sub>'.format(result_text)
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def generate_wiki_per_category(output_path, update_readme: bool = True):
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"""
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:param update_readme:
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:param output_path:
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"""
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repo_df = get_repo_list()
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for category in repo_df['category'].unique():
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category_df = repo_df[repo_df['category'] == category].copy()
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url_md_list = []
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for idx, irow in category_df[['name', 'url']].iterrows():
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url_md_list.append('<sub>[{}]({})</sub>'.format(irow['name'], irow['url']))
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formatted_df = pd.DataFrame({
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'repo': url_md_list,
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'comment': category_df['comment'].apply(lambda x: '<sub>{}</sub>'.format(x)),
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'created_at': category_df['created_at'].apply(lambda x: '<sub>{}</sub>'.format(x)),
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'last_commit': category_df['last_commit'].apply(lambda x: '<sub>{}</sub>'.format(x)),
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'star_count': category_df['star_count'].apply(lambda x: '<sub>{}</sub>'.format(x)),
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'repo_status': category_df['repo_status'],
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'rating': category_df['rating']
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})
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# add color for the status
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formatted_df = formatted_df.sort_values(by=['rating', 'star_count'], ascending=False).reset_index(drop=True)
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formatted_df['repo_status'] = formatted_df['repo_status'].apply(lambda x: get_wiki_status_color(x))
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formatted_df['rating'] = formatted_df['rating'].apply(lambda x: get_wiki_rating(x))
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formatted_df.columns = ['<sub>{}</sub>'.format(x) for x in formatted_df.columns]
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clean_category_name = category.lower().replace(' ', '_')
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output_path_full = os.path.join(output_path, '{}.md'.format(clean_category_name))
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with open(output_path_full, 'w') as f:
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f.write(formatted_df.to_markdown(index=False))
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print('wiki generated in [{}]'.format(output_path_full))
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if update_readme:
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check_str = '[PLACEHOLDER_START:{}]'.format(clean_category_name)
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with open(os.path.join(PROJECT_ROOT_DIR, 'README.md')) as f:
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all_read_me = f.read()
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if check_str not in all_read_me:
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print(f'section {check_str} not found')
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continue
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# only display top 5, then expandable for extra 5
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with open(os.path.join(PROJECT_ROOT_DIR, 'README.md'), 'w') as f:
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table_str = formatted_df.iloc[:15].to_markdown(index=False)
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new_str = f"<!-- [PLACEHOLDER_START:{clean_category_name}] --> \n"
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new_str += table_str
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new_str += f"<!-- [PLACEHOLDER_END:{clean_category_name}] -->"
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search_start = re.escape('<!-- [PLACEHOLDER_START:{}] -->'.format(clean_category_name))
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search_end = re.escape('<!-- [PLACEHOLDER_END:{}] -->'.format(clean_category_name))
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pattern_s = re.compile(r'{}.*?{}'.format(search_start, search_end), re.DOTALL)
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write_str = re.sub(pattern_s, new_str, all_read_me)
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f.write(write_str)
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if __name__ == '__main__':
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local_path = os.path.join(PROJECT_ROOT_DIR, 'generated_wiki')
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generate_wiki_per_category(local_path)
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