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main.py
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main.py
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import re
import os
import csv
from tqdm import tqdm
import argparse
import functools
parser = argparse.ArgumentParser(description = 'What the program does')
parser.add_argument('-f', choices=['csv', 'md'], default='md')
args = parser.parse_args()
DIR_ROOT= os.path.dirname(os.path.abspath(__file__))
COLLECTION_CSV = os.path.join(DIR_ROOT, 'collection.csv')
MD_FILE= os.path.join(DIR_ROOT, '../README.md')
HEAD = f"""# Awesome-Inpainting-Tech
[](https://github.com/sindresorhus/awesome)   
A curated list of inpainting papers and resources, inspired by [awesome-computer-vision](https://github.com/jbhuang0604/awesome-computer-vision).
This `README.md` is automatically generated from [`.dev_scripts/collection.csv`](.dev_scripts/collection.csv).
We provide [scripts](.dev_scripts/main.py) to automatically generate `README.md` from CSV file or vice versa.
Welcome to pull request to update or correct this collection. 🥰
"""
def readme_to_csv():
# save all data to csv file
csvfile = open(COLLECTION_CSV, 'w')
csv_writer = csv.writer(csvfile, delimiter=',')
csv_writer.writerow(['Year', 'Conf', 'Type', 'Ttitle', 'URL', 'Code', 'Project'])
# parse data from readme
with open(MD_FILE, 'r', encoding='utf-8') as md:
lines = md.readlines()
type = None
papers = []
i = 0
while i < len(lines):
if '## Year' not in lines[i]:
i += 1
else:
year = int(re.match(r'## Year (.*)', lines[i]).groups()[0])
i += 1
while i < len(lines) and (r'## Year' not in lines[i]):
line = lines[i]
conf, type, title, url = re.match(
r'- \*\*(.*)\*\* \((.*)\) \[(.*)\]\((.*)\)\..*', line).groups()
project, code = None, None
if '[code]' in line:
code = line.split('[[code]](')[-1].split(')')[0]
if '[project]' in line:
project = line.split('[[project]](')[-1].split(')')[0]
papers.append(dict(title=title, url=url, conf=conf, year=year, project=project, code=code, type=type))
i += 1
papers = sorted(papers, key=lambda x: (x['year'], x['conf'], x['type']), reverse=True)
for p in papers:
csv_writer.writerow([p['year'], p['conf'], p['type'], p['title'], p['url'], p['code'], p['project']])
csvfile.close()
def csv_to_readme():
# save all data to csv file
csvfile = open(COLLECTION_CSV)
csv_reader = csv.reader(csvfile, delimiter=',')
papers = {}
# parse data from csv file
for idx, row in enumerate(csv_reader):
if idx == 0:
continue
try:
year, conf, type, title, url, code, project = row
except:
print(row)
p = dict(title=title, url=url, conf=conf, year=year, project=project, code=code, type=type)
if str(year) not in papers:
papers[str(year)] = [p]
else:
papers[str(year)].append(p)
for k, v in papers.items():
papers[k].sort(key=lambda x: (x['year'], x['conf'], x['type']), reverse=True)
message = {}
# generate msg from parsed dict data
years = sorted([y for y in list(papers.keys())], reverse=True)
for k,v in papers.items():
msg = f"## Year {k}\n"
for p in v:
msg += f"- **{p['conf']}** ({p['type']}) [{p['title']}]({p['url']})."
if p['code']:
msg += f" [[code]]({p['code']}) "
if p['project']:
msg += f" [[project]]({p['project']}) "
msg += "\n"
message[k] = msg
# write to readme
readme_content = HEAD
for y in years:
readme_content += message[y]
with open(MD_FILE, 'w') as f:
f.write(readme_content)
if __name__ == '__main__':
if args.f == 'csv':
readme_to_csv()
elif args.f == 'md':
csv_to_readme()
else:
raise ValueError('Invalid target format. Only support csv or md.')