osci/notify/get_contributors_ranking_mbm_report.py (27 lines of code) (raw):

"""Copyright since 2019, EPAM Systems This file is part of OSCI. OSCI is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. OSCI is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with OSCI. If not, see <http://www.gnu.org/licenses/>.""" from functools import reduce from typing import Iterable, Tuple from datetime import datetime import pandas as pd from osci.datalake.schemas.public import ContributorsRankingMBMReportSchema def get_contributors_ranking_mbm_change_report(reports: Iterable[Tuple[datetime, pd.DataFrame]], contributor_field: str, commits_amount_field: str) -> pd.DataFrame: """Creates a combined report, that shows the difference between several contributors rankings :param reports: collection of datatime and pandas DataFrame objects :param contributor_field: contributor column name :param commits_amount_field: amount of commits column name """ report = pd.DataFrame(columns=ContributorsRankingMBMReportSchema.required) df_list = [] for item in reports: tmp_df = pd \ .pivot_table(item[1], values=[commits_amount_field, ], index=[item[1].index.values, contributor_field]) \ .rename(columns={commits_amount_field: datetime.strftime(item[0], '%b')}) \ .reset_index(contributor_field) df_list.append(tmp_df) df = reduce(lambda x, y: pd.merge(x, y, how='outer', on=contributor_field), df_list) \ .sort_values(by=contributor_field).fillna(0) df.iloc[:, 1:] = df.iloc[:, 1:].astype(int) df[ContributorsRankingMBMReportSchema.total] = df.sum(axis=1) df = df.sort_values(ContributorsRankingMBMReportSchema.total, ascending=False) for column in report.columns: if column in df.columns: report[column] = df[column] return report