def load_licensed_repositories_to_bq(
date: datetime.datetime) -> bigquery.table.Table:
"""Load licensed repositories to BigQuery for a given day"""
df = DataLake().staging.get_repositories(date)
return DataLake().big_query.load_dataframe(
df=df,
table_id=BigQueryLicensedRepository.table_id,
schema=BigQueryLicensedRepository.schema)
def staging_repository_df():
return pd.DataFrame([
{
DataLake().staging.schemas.repositories.name: "epam/OSCI",
DataLake().staging.schemas.repositories.language: "Python",
DataLake().staging.schemas.repositories.license: "gpl-3.0",
DataLake().staging.schemas.repositories.downloaded_at: "2021-01-01"
},
])
def __init__(self, sheet_name: str, from_date: datetime, to_date: datetime, top_size: int):
self.writer, self.buffer = DataLake().public.get_excel_writer()
self.workbook: Workbook = self.writer.book
self.worksheet: Worksheet = self.workbook.add_worksheet(sheet_name)
self.from_date = from_date
self.to_date = to_date
self.top_size = top_size
self.superscript_format = self.get_format(self.superscript_format_rule)
def get_daily_active_repositories(date: datetime.datetime) -> pd.DataFrame:
df = DataLake().staging.get_union_daily_raw_push_events_commits(date=date)
result_df = df[[LandingSchemas.push_commits.repo_name]].drop_duplicates()
result_df = result_df[
result_df.apply(lambda row: not Blacklist().is_blocked_repo_by_account(
repository_name=row[LandingSchemas.push_commits.repo_name]
), axis=1)
]
DataLake().landing.save_repositories(df=result_df, date=date)
return result_df
def filter_out_unlicensed(date: datetime):
"""Read row PEC, filter and save them with license, language
:param date: push events on this day
"""
log.debug(
f'Filter out unlicensed push events commits for date {date:%Y-%m-%d}')
log.debug(f'Read licensed repos for date {date:%Y-%m-%d}')
licensed_repos_df = Repositories(date=date).read()
for company, df in DataLake().staging.get_daily_raw_push_events_commits(
date):
log.debug(
f'Filter out unlicensed push events commits for date {date:%Y-%m-%d} for {company}'
)
filtered_df = filter_and_adjunct_push_event_commit(
df,
licensed_repos_df,
[DataLake().staging.schemas.repositories.license], [
DataLake().staging.schemas.repositories.name,
DataLake().staging.schemas.repositories.language,
DataLake().staging.schemas.repositories.license
],
DataLake().staging.schemas.push_commits.required,
right_index=DataLake().staging.schemas.repositories.name,
left_index=DataLake().staging.schemas.push_commits.repo_name)
if not filtered_df.empty:
DataLake().staging.save_push_events_commits(
push_event_commits=filtered_df,
company_name=company,
date=date)
def load_repositories(date: datetime) -> pd.DataFrame:
log.debug(f'Load repositories information for {date:%Y-%m-%d}')
repositories = Repositories(date=date)
df = pd.DataFrame(data=[], columns=Repositories.schema.required)
repositories_names = DataLake().landing.get_repositories(date=date)
if not repositories_names.empty:
df = _load_repositories(repos_names=repositories_names[
DataLake().landing.schemas.repositories_names.name])
repositories.save(df)
return df
def _execute(self, day: datetime, company: str):
df = ReposRankingMTD(date=day, company=company).read()
out_df = filter_projects(
df=df,
projects_filter_list=DataLake().staging.load_projects_filter(),
commits_amount_field=DataLake(
).public.schemas.repo_commits_ranking.commits,
repo_name_field=DataLake(
).public.schemas.repo_commits_ranking.repo)
DataLake().public.save_report(report_df=out_df,
report_name='projects_activity_MTD',
date=day,
company=company)
def load_push_events_to_bq(date: datetime.datetime,
hour: int) -> Dict[str, Dict[str, Any]]:
date = date.replace(hour=hour)
df = DataLake().staging.get_push_events_commits(
from_date=date, to_date=date, date_period_type=DatePeriodType.DTD)
job_results = DataLake().big_query.load_dataframe(
df=df,
table_id=BigQueryPushEventsCommitsColumns.table_id,
schema=BigQueryPushEventsCommitsColumns.schema)
return {
'num_rows': job_results.num_rows,
'num_columns': len(job_results.schema),
'table_id': BigQueryPushEventsCommitsColumns.table_id
}
def process_github_daily_push_events(day: datetime.datetime):
push_events_commits = DataLake().landing.get_daily_push_events_commits(
date=day)
if push_events_commits is not None and not push_events_commits.empty:
companies_events = process_push_commits(
push_events_commits,
email_field=DataLake().landing.schemas.push_commits.author_email,
company_field=DataLake().staging.schemas.push_commits.company,
datetime_field=DataLake(
).landing.schemas.push_commits.event_created_at)
for company, commits in companies_events:
log.debug(f'Save company {company}')
DataLake().staging.save_raw_push_events_commits(
push_event_commits=commits, date=day, company_name=company)
def generate_email_body(date: datetime, company=Config().default_company):
report = OSCIChangeRanking(date=date)
company_contributors_ranking_schema = DataLake(
).public.schemas.company_contributors_ranking
change_ranking = report.read().reset_index()
change_ranking = change_ranking.rename(
columns={'index': company_contributors_ranking_schema.position})
change_ranking[company_contributors_ranking_schema.position] += 1
change_ranking = __cast_columns_to_int(
df=change_ranking,
columns=[
report.schema.total,
report.schema.active,
company_contributors_ranking_schema.position,
report.schema.total_change,
report.schema.active_change,
report.schema.position_change,
])
shift_up = __add_arrows_prefix(df=__get_shift_up(
change_ranking=change_ranking,
change_position_field=report.schema.position_change),
column=report.schema.position_change)
shift_down = __add_arrows_prefix(df=__get_shift_down(
change_ranking=change_ranking,
change_position_field=report.schema.position_change),
column=report.schema.position_change)
company_position = __add_arrows_prefix(
df=__get_company_neighbors(
df=change_ranking,
company=company,
company_field=report.schema.company,
rank_field=company_contributors_ranking_schema.position),
column=report.schema.position_change)
DataLake().public.save_email(email_body=EmailBodyTemplate().render(
date=date,
compared_date=get_previous_date(date),
shift_up=shift_up,
shift_down=shift_down,
company=company,
company_position=company_position,
solutionshub_osci_change_ranking=OSCIChangeRankingExcel(
to_date=date).url,
osci_reports_urls={
name: report_cls(date=date).url
for name, report_cls in OSCI_REPORTS_URLS.items()
}),
date=date)
def load_companies_contrib_repos_to_bq(date: datetime.datetime) -> bigquery.table.Table:
"""Load companies contributors repositories to BigQuery for a given day"""
df = CompaniesContributorsRepository(date).read().rename(
columns=BigQueryCompaniesContributorsRepositoriesCommitsColumns.mapping)
return DataLake().big_query.load_dataframe(df=df,
table_id=BigQueryCompaniesContributorsRepositoriesCommitsColumns.table_id,
schema=BigQueryCompaniesContributorsRepositoriesCommitsColumns.schema)
class Repositories:
schema = DataLake().staging.schemas.repositories
def __init__(self, date: datetime.datetime):
self.date = date
@property
def path(self) -> str:
"""
Return the full path to repositories
"""
return DataLake().staging.get_repositories_path(self.date)
@property
def spark_path(self) -> str:
"""
Return the full path to repositories
"""
return DataLake().staging.get_repositories_spark_path(self.date)
def save(self, df: pd.DataFrame):
"""
Save pandas DataFrame as file
:param df:
"""
return DataLake().staging.save_repositories(df, self.date)
def read(self) -> pd.DataFrame:
"""
Read repositories to pandas DataFrame from file
"""
return DataLake().staging.get_repositories(self.date)
class CompaniesContributorsRepository:
schema = DataLake().public.schemas.company_contributors_repository_commits
def __init__(self, date: datetime.datetime):
self.date = date
@property
def path(self) -> str:
"""
Return the full path to company contributors repository commits
"""
return DataLake().public.get_companies_contributors_repository_commits_path(self.date)
@property
def spark_path(self) -> str:
"""
Return the full path to company contributors repository commits
"""
return DataLake().public.get_companies_contributors_repository_commits_spark_path(self.date)
def save(self, df: pd.DataFrame):
"""
Save pandas DataFrame as file
:param df:
"""
return DataLake().public.save_companies_contributors_repository_commits(df, self.date)
def read(self) -> pd.DataFrame:
"""
Read company contributors repository commits to pandas DataFrame from file
"""
return DataLake().public.get_companies_contributors_repository_commits(self.date)
def get_github_daily_push_events(day: datetime.datetime):
with GithubArchiveRest() as rest:
for hour in range(24):
log.info(f'Crawl events for {day}')
day = day.replace(hour=hour)
push_events_commits = get_hour_push_events_commits(day=day,
rest=rest)
DataLake().landing.save_push_events_commits(
push_event_commits=push_events_commits, date=day)
def raw_push_events_commit_df():
return pd.DataFrame([
{
DataLake().staging.schemas.push_commits.event_id: "1111111",
DataLake().staging.schemas.push_commits.event_created_at:
"2021-01-01 00:15:22+00:00",
DataLake().staging.schemas.push_commits.actor_login: "******",
DataLake().staging.schemas.push_commits.repo_name: "epam/OSCI",
DataLake().staging.schemas.push_commits.org_name: 'EPAM',
DataLake().staging.schemas.push_commits.sha:
"aaa656b0d05ec5b8ed5beb2f94c4aa11ea111a1a",
DataLake().staging.schemas.push_commits.author_name: "User Name",
DataLake().staging.schemas.push_commits.author_email:
"*****@*****.**",
DataLake().staging.schemas.push_commits.company: "EPAM"
},
])
def load_osci_general_reports_to_bq(date: datetime.datetime):
report = OSCIGeneralRanking(date=date)
table = BigQueryOSCIGeneralRankingReport
log.debug(f'Load {report.name} for {date:%Y-%m-%d} to {table.table_id}')
report_df = report.read()
report_df = report_df[PublicSchemas.osci_general_report.required]
report_df[table.Columns.position] += 1
report_df = report_df.rename(columns=table.mapping)
report_df[table.Columns.date] = date
return DataLake().big_query.load_dataframe(df=report_df,
table_id=table.table_id,
schema=table.schema)
def load_company_repositories_events_commits(date: datetime, company: str):
events = DataLake().staging.get_push_events_commits(
company=company,
from_date=date,
to_date=date,
date_period_type=DatePeriodType.DTD)
schema = DataLake().staging.schemas.push_commits
if events.empty:
log.warning(f'No {company} events at {date}')
return
with GithubRest(token=Config().github_token) as rest:
company_commits = get_company_repositories_events_commits(
repositories_names=events[schema.repo_name].unique(),
date=date,
company=company,
rest=rest)
company_commits_df = pd.DataFrame(company_commits)
DataLake().staging.save_private_push_events_commits(
push_event_commits=company_commits_df,
company_name=company,
date=date)
def get_contributors_repositories_change(date: datetime, company: str):
ranking = ContributorsReposYTD(date=date, company=company)
ranking_df = ranking.read()
compared_ranking = ContributorsReposYTD(date=get_previous_date(date),
company=company)
compared_ranking_df = compared_ranking.read()
new_contributors = NewContributors(date=date, company=company)
new_contributors_df = pd.DataFrame(
data=set(ranking_df[ranking.schema.author]) -
set(compared_ranking_df[ranking.schema.author]),
columns=[DataLake().public.schemas.new_contributors.author])
new_contributors.save(df=new_contributors_df)
new_repos = NewRepos(date=date, company=company)
new_repos_df = pd.DataFrame(
data=set(ranking_df[ranking.schema.repo]) -
set(compared_ranking_df[ranking.schema.repo]),
columns=[DataLake().public.schemas.new_repos.repo])
new_repos.save(df=new_repos_df)
def no_match_license_raw_push_event_commit_df():
return pd.DataFrame([{
DataLake().staging.schemas.push_commits.event_id:
"222222",
DataLake().staging.schemas.push_commits.event_created_at:
"2021-01-01 00:15:22+00:00",
DataLake().staging.schemas.push_commits.actor_login:
"******",
DataLake().staging.schemas.push_commits.repo_name:
"test/TEST",
DataLake().staging.schemas.push_commits.org_name:
None,
DataLake().staging.schemas.push_commits.sha:
"bbb656b0d05ec5b8ed5beb2f94c4aa11ea111a1a",
DataLake().staging.schemas.push_commits.author_name:
"User Name",
DataLake().staging.schemas.push_commits.author_email:
"*****@*****.**",
DataLake().staging.schemas.push_commits.company:
"EPAM"
}])
def load_osci_daily_ranking_to_bq(date: datetime.datetime):
"""Load Daily Change ranking to Big Query"""
report = OSCIChangeRankingDTD(date=date)
table = BigQueryOSCIDailyChangeRankingReport
log.debug(f'Load {report.name} for {date:%Y-%m-%d} to {table.table_id}')
report_df = report.read()
report_df = report_df.reset_index().rename(
columns={'index': table.Columns.position})
report_df = report_df[PublicSchemas.osci_ranking_schema.required]
report_df[table.Columns.position] += 1
report_df = report_df.rename(columns=table.mapping)
report_df[table.Columns.date] = date.date()
return DataLake().big_query.load_dataframe(df=report_df,
table_id=table.table_id,
schema=table.schema)
def load_osci_ranking_to_bq(date: datetime.datetime,
date_period: str = DatePeriodType.YTD):
if date_period not in (DatePeriodType.MTD, DatePeriodType.YTD):
raise ValueError(f'Unsupported {date_period}')
report = OSCIRankingFactory().get_cls(date_period=date_period)(date=date)
table = date_period_to_table_map[date_period]
log.debug(f'Load {report.name} for {date:%Y-%m-%d} to {table.table_id}')
report_df = report.read()
report_df = report_df[PublicSchemas.company_contributors_ranking.required]
report_df = report_df.reset_index().rename(
columns={'index': table.Columns.position})
report_df[table.Columns.position] += 1
report_df = report_df.rename(columns=table.mapping)
report_df[table.Columns.date] = date.date()
return DataLake().big_query.load_dataframe(df=report_df,
table_id=table.table_id,
schema=table.schema)
def read(self) -> pd.DataFrame:
"""
Read company contributors repository commits to pandas DataFrame from file
"""
return DataLake().public.get_companies_contributors_repository_commits(self.date)
def save(self, df: pd.DataFrame):
"""
Save pandas DataFrame as file
:param df:
"""
return DataLake().public.save_companies_contributors_repository_commits(df, self.date)
def spark_path(self) -> str:
"""
Return the full path to company contributors repository commits
"""
return DataLake().public.get_companies_contributors_repository_commits_spark_path(self.date)
def url(self) -> str:
return DataLake().public.get_report_url(report_name=self.name,
date=self.date)
def transfer_monthly_change_ranking(date: datetime) -> dict:
web_ranking = generate_web_osci_change_ranking(date)
DataLake().web.save_monthly_osci_ranking(ranking=web_ranking, date=date)
return web_ranking
def read(self) -> pd.DataFrame:
return DataLake().public.get_report(report_name=self.name,
date=self.date)
def path(self) -> str:
return DataLake().public.get_report_path(report_name=self.name,
date=self.date)
def save(self, df: pd.DataFrame):
DataLake().public.save_report(report_df=df,
report_name=self.name,
date=self.date)
def adjunct_columns():
return [
DataLake().staging.schemas.repositories.name,
DataLake().staging.schemas.repositories.language,
DataLake().staging.schemas.repositories.license
]
