def get_top_data_authors (startdate, enddate, i_db, filter_, npeople):
top = {}
mauthors = DataSource.get_metrics("authors", SCM)
if mauthors is None: return top
period = None
type_analysis = None
if filter_ is not None:
type_analysis = filter_.get_type_analysis()
mfilter = MetricFilters(period, startdate, enddate, type_analysis, npeople)
mfilter.global_filter = mauthors.filters.global_filter
if filter_ is None:
top['authors.'] = mauthors.get_list(mfilter, 0)
top['authors.last month'] = mauthors.get_list(mfilter, 31)
top['authors.last year'] = mauthors.get_list(mfilter, 365)
elif filter_.get_name() in ["company","repository","project"]:
if filter_.get_name() in ["company","repository","project"]:
top['authors.'] = mauthors.get_list(mfilter, 0)
top['authors.last month'] = mauthors.get_list(mfilter, 31)
top['authors.last year'] = mauthors.get_list(mfilter, 365)
else:
# If we have performance issues with tops, remove filters above
# to avoid computing trends for tops
top = mauthors.get_list(mfilter)
else:
logging.info("Top authors not support for " + filter_.get_name())
return top
def get_top_data_authors(startdate, enddate, i_db, filter_, npeople):
top = {}
mauthors = DataSource.get_metrics("authors", SCM)
if mauthors is None: return top
period = None
type_analysis = None
if filter_ is not None:
type_analysis = filter_.get_type_analysis()
mfilter = MetricFilters(period, startdate, enddate, type_analysis,
npeople)
mfilter.global_filter = mauthors.filters.global_filter
if filter_ is None:
top['authors.'] = mauthors.get_list(mfilter, 0)
top['authors.last month'] = mauthors.get_list(mfilter, 31)
top['authors.last year'] = mauthors.get_list(mfilter, 365)
elif filter_.get_name() in ["company", "repository", "project"]:
if filter_.get_name() in ["company", "repository", "project"]:
top['authors.'] = mauthors.get_list(mfilter, 0)
top['authors.last month'] = mauthors.get_list(mfilter, 31)
top['authors.last year'] = mauthors.get_list(mfilter, 365)
else:
# If we have performance issues with tops, remove filters above
# to avoid computing trends for tops
top = mauthors.get_list(mfilter)
else:
logging.info("Top authors not support for " + filter_.get_name())
return top
def __get_data__ (period, startdate, enddate, identities_db, filter_ = None, evol = False):
data = {}
DS = SCR
from vizgrimoire.GrimoireUtils import fill_and_order_items
type_analysis = None
if filter_ is not None:
type_analysis = [filter_.get_name(), filter_.get_item()]
from vizgrimoire.report import Report
automator = Report.get_config()
if evol:
metrics_on = DS.get_metrics_core_ts()
automator_metrics = DS.get_name()+"_metrics_ts"
else:
metrics_on = DS.get_metrics_core_agg()
automator_metrics = DS.get_name()+"_metrics_agg"
if automator_metrics in automator['r']:
metrics_on = automator['r'][automator_metrics].split(",")
logging.info(automator_metrics + " found ")
# print(metrics_on)
people_out = []
if "people_out" in Report.get_config()['r']:
people_out = Report.get_config()['r']["people_out"]
people_out = people_out.split(",")
metrics_reports = SCR.get_metrics_core_reports()
if filter_ is None:
from vizgrimoire.report import Report
reports_on = Report.get_config()['r']['reports'].split(",")
for r in metrics_reports:
if r in reports_on: metrics_on += [r]
if type_analysis and type_analysis[1] is None:
items = DS.get_filter_items(filter_, startdate, enddate, identities_db)
items = items.pop('name')
if DS.get_name()+"_start_date" in Report.get_config()['r']:
startdate = "'"+Report.get_config()['r'][DS.get_name()+"_start_date"]+"'"
if DS.get_name()+"_end_date" in Report.get_config()['r']:
enddate = "'"+Report.get_config()['r'][DS.get_name()+"_end_date"]+"'"
mfilter = MetricFilters(period, startdate, enddate, type_analysis, 10, people_out, None)
all_metrics = SCR.get_metrics_set(SCR)
# SCR specific: remove some metrics from filters
if filter_ is not None:
metrics_not_filters = SCR.get_metrics_not_filters()
metrics_on_filters = list(set(metrics_on) - set(metrics_not_filters))
if filter_.get_name() == "repository":
if 'review_time' in metrics_on: metrics_on_filters+= ['review_time']
if 'submitted' in metrics_on: metrics_on_filters+= ['submitted']
metrics_on = metrics_on_filters
# END SCR specific
for item in all_metrics:
if item.id not in metrics_on: continue
# logging.info(item.id)
mfilter_orig = item.filters
mfilter.global_filter = mfilter_orig.global_filter
item.filters = mfilter
if not evol: mvalue = item.get_agg()
else: mvalue = item.get_ts()
if type_analysis and type_analysis[1] is None:
logging.info(item.id)
id_field = SCRQuery.get_group_field_alias(type_analysis[0])
mvalue = check_array_values(mvalue)
mvalue = fill_and_order_items(items, mvalue, id_field,
evol, period, startdate, enddate)
data = dict(data.items() + mvalue.items())
item.filters = mfilter_orig
# SCR SPECIFIC #
if evol:
if type_analysis and type_analysis[1] is None: pass
else:
metrics_on_changes = ['merged','abandoned','new']
for item in all_metrics:
if item.id in metrics_on_changes and filter_ is None:
mfilter_orig = item.filters
item.filters = mfilter
mvalue = item.get_ts_changes()
data = dict(data.items() + mvalue.items())
item.filters = mfilter_orig
# END SCR SPECIFIC #
if not evol:
init_date = DS.get_date_init(startdate, enddate, identities_db, type_analysis)
end_date = DS.get_date_end(startdate, enddate, identities_db, type_analysis)
if type_analysis and type_analysis[1] is None:
if id_field is None:
id_field = dsquery.get_group_field_alias(type_analysis[0])
init_date = fill_and_order_items(items, init_date, id_field,
evol, period, startdate, enddate)
end_date = fill_and_order_items(items, end_date, id_field,
evol, period, startdate, enddate)
data = dict(data.items() + init_date.items() + end_date.items())
# Tendencies
metrics_trends = SCR.get_metrics_core_trends()
automator_metrics = DS.get_name()+"_metrics_trends"
if automator_metrics in automator['r']:
metrics_trends = automator['r'][automator_metrics].split(",")
for i in [7,30,365]:
for item in all_metrics:
if item.id not in metrics_trends: continue
mfilter_orig = item.filters
item.filters = mfilter
period_data = item.get_trends(enddate, i)
item.filters = mfilter_orig
data = dict(data.items() + period_data.items())
if type_analysis and type_analysis[1] is None:
id_field = SCRQuery.get_group_field_alias(type_analysis[0])
period_data = fill_and_order_items(items, period_data, id_field)
data = dict(data.items() + period_data.items())
if filter_ is not None: studies_data = {}
else:
studies_data = DataSource.get_studies_data(SCR, period, startdate, enddate, evol)
data = dict(data.items() + studies_data.items())
return data
def get_metrics_data(DS, period, startdate, enddate, identities_db,
filter_ = None, evol = False):
""" Get basic data from all core metrics """
from vizgrimoire.GrimoireUtils import fill_and_order_items
from vizgrimoire.ITS import ITS
from vizgrimoire.MLS import MLS
data = {}
dsquery = DSQuery
if DS == ITS: dsquery = ITSQuery
if DS == MLS: dsquery = MLSQuery
from vizgrimoire.report import Report
automator = Report.get_config()
if evol:
metrics_on = DS.get_metrics_core_ts()
automator_metrics = DS.get_name()+"_metrics_ts"
else:
metrics_on = DS.get_metrics_core_agg()
automator_metrics = DS.get_name()+"_metrics_agg"
if automator_metrics in automator['r']:
metrics_on = automator['r'][automator_metrics].split(",")
people_out = []
if "people_out" in Report.get_config()['r']:
people_out = Report.get_config()['r']["people_out"]
people_out = people_out.split(",")
type_analysis = None
if filter_ is not None:
type_analysis = filter_.get_type_analysis()
if type_analysis and type_analysis[1] is None:
# We need the items for filling later values in group by queries
items = DS.get_filter_items(filter_, startdate, enddate, identities_db)
if items is None: return data
items = items.pop('name')
if DS.get_name()+"_startdate" in Report.get_config()['r']:
startdate = Report.get_config()['r'][DS.get_name()+"_startdate"]
if DS.get_name()+"_enddate" in Report.get_config()['r']:
enddate = Report.get_config()['r'][DS.get_name()+"_enddate"]
# TODO: the hardcoded 10 should be removed, and use instead the npeople provided
# in the config file.
mfilter = MetricFilters(period, startdate, enddate, type_analysis, 10, people_out, None)
metrics_reports = DS.get_metrics_core_reports()
all_metrics = DS.get_metrics_set(DS)
# Reports = filters metrics not available inside filters
if type_analysis is None:
from vizgrimoire.report import Report
reports_on = Report.get_config()['r']['reports'].split(",")
for r in metrics_reports:
if r in reports_on: metrics_on += [r]
for item in all_metrics:
# print item
if item.id not in metrics_on: continue
mfilter_orig = item.filters
mfilter.global_filter = mfilter_orig.global_filter
mfilter.set_closed_condition(mfilter_orig.closed_condition)
item.filters = mfilter
if evol: mvalue = item.get_ts()
else: mvalue = item.get_agg()
if type_analysis and type_analysis[1] is None and mvalue:
logging.info(item.id)
id_field = None
# Support for combined filters
for idf in mvalue.keys():
if "CONCAT(" in idf:
id_field = idf
break
if id_field is None:
id_field = dsquery.get_group_field_alias(type_analysis[0])
mvalue = fill_and_order_items(items, mvalue, id_field,
evol, period, startdate, enddate)
data = dict(data.items() + mvalue.items())
item.filters = mfilter_orig
if not evol:
init_date = DS.get_date_init(startdate, enddate, identities_db, type_analysis)
end_date = DS.get_date_end(startdate, enddate, identities_db, type_analysis)
if type_analysis and type_analysis[1] is None:
if id_field is None:
id_field = dsquery.get_group_field_alias(type_analysis[0])
init_date = fill_and_order_items(items, init_date, id_field,
evol, period, startdate, enddate)
end_date = fill_and_order_items(items, end_date, id_field,
evol, period, startdate, enddate)
if init_date is None: init_date = {}
if end_date is None: end_date = {}
data = dict(data.items() + init_date.items() + end_date.items())
# Tendencies
metrics_trends = DS.get_metrics_core_trends()
automator_metrics = DS.get_name()+"_metrics_trends"
if automator_metrics in automator['r']:
metrics_trends = automator['r'][automator_metrics].split(",")
for i in [7,30,365]:
for item in all_metrics:
if item.id not in metrics_trends: continue
mfilter_orig = item.filters
item.filters = mfilter
period_data = item.get_trends(enddate, i)
item.filters = mfilter_orig
if type_analysis and type_analysis[1] is None:
group_field = dsquery.get_group_field_alias(type_analysis[0])
period_data = fill_and_order_items(items, period_data, group_field)
data = dict(data.items() + period_data.items())
return data
def get_metrics_data(DS,
period,
startdate,
enddate,
identities_db,
filter_=None,
evol=False):
""" Get basic data from all core metrics """
from vizgrimoire.GrimoireUtils import fill_and_order_items
from vizgrimoire.ITS import ITS
from vizgrimoire.MLS import MLS
data = {}
dsquery = DSQuery
if DS == ITS: dsquery = ITSQuery
if DS == MLS: dsquery = MLSQuery
from vizgrimoire.report import Report
automator = Report.get_config()
if evol:
metrics_on = DS.get_metrics_core_ts()
automator_metrics = DS.get_name() + "_metrics_ts"
else:
metrics_on = DS.get_metrics_core_agg()
automator_metrics = DS.get_name() + "_metrics_agg"
if automator_metrics in automator['r']:
metrics_on = automator['r'][automator_metrics].split(",")
people_out = []
if "people_out" in Report.get_config()['r']:
people_out = Report.get_config()['r']["people_out"]
people_out = people_out.split(",")
type_analysis = None
if filter_ is not None:
type_analysis = filter_.get_type_analysis()
if type_analysis and type_analysis[1] is None:
# We need the items for filling later values in group by queries
items = DS.get_filter_items(filter_, startdate, enddate,
identities_db)
if items is None: return data
items = items.pop('name')
if DS.get_name() + "_startdate" in Report.get_config()['r']:
startdate = Report.get_config()['r'][DS.get_name() + "_startdate"]
if DS.get_name() + "_enddate" in Report.get_config()['r']:
enddate = Report.get_config()['r'][DS.get_name() + "_enddate"]
# TODO: the hardcoded 10 should be removed, and use instead the npeople provided
# in the config file.
mfilter = MetricFilters(period, startdate, enddate, type_analysis, 10,
people_out, None)
metrics_reports = DS.get_metrics_core_reports()
all_metrics = DS.get_metrics_set(DS)
# Reports = filters metrics not available inside filters
if type_analysis is None:
from vizgrimoire.report import Report
reports_on = Report.get_config()['r']['reports'].split(",")
for r in metrics_reports:
if r in reports_on: metrics_on += [r]
for item in all_metrics:
# print item
if item.id not in metrics_on: continue
mfilter_orig = item.filters
mfilter.global_filter = mfilter_orig.global_filter
mfilter.set_closed_condition(mfilter_orig.closed_condition)
item.filters = mfilter
if evol: mvalue = item.get_ts()
else: mvalue = item.get_agg()
if type_analysis and type_analysis[1] is None and mvalue:
logging.info(item.id)
id_field = None
# Support for combined filters
for idf in mvalue.keys():
if "CONCAT(" in idf:
id_field = idf
break
if id_field is None:
id_field = dsquery.get_group_field_alias(type_analysis[0])
mvalue = fill_and_order_items(items, mvalue, id_field, evol,
period, startdate, enddate)
data = dict(data.items() + mvalue.items())
item.filters = mfilter_orig
if not evol:
init_date = DS.get_date_init(startdate, enddate, identities_db,
type_analysis)
end_date = DS.get_date_end(startdate, enddate, identities_db,
type_analysis)
if type_analysis and type_analysis[1] is None:
if id_field is None:
id_field = dsquery.get_group_field_alias(type_analysis[0])
init_date = fill_and_order_items(items, init_date, id_field,
evol, period, startdate,
enddate)
end_date = fill_and_order_items(items, end_date, id_field,
evol, period, startdate,
enddate)
if init_date is None: init_date = {}
if end_date is None: end_date = {}
data = dict(data.items() + init_date.items() + end_date.items())
# Tendencies
metrics_trends = DS.get_metrics_core_trends()
automator_metrics = DS.get_name() + "_metrics_trends"
if automator_metrics in automator['r']:
metrics_trends = automator['r'][automator_metrics].split(",")
for i in [7, 30, 365]:
for item in all_metrics:
if item.id not in metrics_trends: continue
mfilter_orig = item.filters
item.filters = mfilter
period_data = item.get_trends(enddate, i)
item.filters = mfilter_orig
if type_analysis and type_analysis[1] is None:
group_field = dsquery.get_group_field_alias(
type_analysis[0])
period_data = fill_and_order_items(
items, period_data, group_field)
data = dict(data.items() + period_data.items())
return data