Azalea (on HyDEV-Daisy)
53 lines
1.7 KiB
Python
53 lines
1.7 KiB
Python
from __future__ import annotations
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import os
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from datetime import datetime, timezone, date
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from pathlib import Path
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import numpy as np
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import pandas
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from matplotlib import pyplot as plt
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from pandas import DataFrame
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if __name__ == '__main__':
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path = Path('../../data.relative/0/commitsDF')
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project_list=[p.replace('-fix.pickle.gz','') for p in os.listdir(path) if
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p.endswith('pickle.gz')]
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dates_by_repo: list[list[datetime]] = \
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[list(pandas.read_pickle(path / str(p)).commitDate) for p in os.listdir(path) if
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p.endswith('pickle.gz')]
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dates = np.hstack(dates_by_repo)
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plt.hist(dates, bins=50)
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plt.xlabel('Date')
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plt.ylabel('Total Commits')
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plt.xlim([date(2001, 1, 1), date(2022, 6, 1)])
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plt.savefig("fm-dates.png")
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plt.show()
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first_dates = [cs[-1] for cs in dates_by_repo]
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plt.hist(first_dates, bins=20)
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plt.xlabel('First Commit Date')
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plt.xlim([date(2001, 1, 1), date(2022, 6, 1)])
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#plt.show()
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last_dates = [cs[0] for cs in dates_by_repo]
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plt.hist(last_dates, bins=20)
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plt.xlabel('Last Commit Date')
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plt.xlim([date(2001, 1, 1), date(2022, 6, 1)])
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#plt.show()
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mean_dates = [datetime.fromtimestamp(
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float(np.mean([c.replace(tzinfo=timezone.utc).timestamp() for c in cs]))) for cs in
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dates_by_repo]
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plt.hist(mean_dates, bins=20)
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plt.xlabel('Mean Commit Date')
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plt.xlim([date(2001, 1, 1), date(2022, 6, 1)])
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#plt.show()
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csv = []
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for i in range(len(first_dates)):
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csv.append((project_list[i],first_dates[i], last_dates[i]))
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df = DataFrame(csv, columns=('project','first_dates','last commit dates'))
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df.to_csv('commits-dates.csv')
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