def repo_table(scope): # repos, start, end):
#this drives the list of all repos within an organization, showing the statistics for them within the selected
#time range, along with navigation links.
(repos, authors) = scope.standardize_repos_and_authors()
interval = 'DY'
# FIXME: explain
repos = [x.pk for x in scope.available_repos.all()]
stats = Statistic.queryset_for_range(repos=repos,
authors=authors,
start=scope.start,
end=scope.end,
interval=interval)
stats = Statistic.annotate(
stats.values('repo__name')).order_by('repo__name')
data = _annotations_to_table(stats, 'repo', 'repo__name')
# FIXME: insert in author count, which is ... complicated ... this can be optimized later
# we should be able to grab every repo and annotate it with the author count in one extra query tops
# but it might require manually writing it.
for d in data:
repo = d['repo']
author_count = Author.author_count(repo,
start=scope.start,
end=scope.end)
d['author_count'] = author_count
# some repos won't have been scanned, and this requires a second query to fill them into the table
repos = Repository.objects.filter(last_scanned=None,
organization=scope.org)
for unscanned in repos:
data.append(dict(repo=unscanned.name))
return data
def author_stats_table(scope, limit=None):
"""
this drives the author tables, both ranged and non-ranged, accessed off the main repo list.
the interval 'LF' shows lifetime stats, but elsewhere we just do daily roundups, so this parameter
should really be a boolean. The limit parameter is not yet used.
"""
# FIXME: this performs one query PER author and could be rewritten to be a LOT more intelligent.
(repos, authors) = scope.standardize_repos_and_authors()
interval = 'DY'
stats = Statistic.queryset_for_range(repos=repos,
authors=authors,
start=scope.start,
end=scope.end,
interval=interval)
data = None
if not scope.author:
stats = Statistic.annotate(
stats.values('author__email')).order_by('author__email')
data = _annotations_to_table(stats, 'author', 'author__email')
else:
stats = Statistic.annotate(
stats.values('repo__name')).order_by('repo__name')
data = _annotations_to_table(stats, 'repo', 'repo__name')
return data
def repo_table(scope): # repos, start, end):
"""
this drives the list of all repos within an organization, showing the statistics for them within the selected
time range, along with navigation links.
"""
results = []
for repo in scope.repos:
stats = Statistic.queryset_for_range(repo,
author=None,
interval='DY',
start=scope.start,
end=scope.end)
stat2 = Statistic.compute_interval_statistic(stats,
interval='DY',
repo=repo,
author=None,
start=scope.start,
end=scope.end)
stat2 = stat2.to_dict()
stat2['name'] = repo.name
# providing pk's for link columns in the repo chart
for x in ['details1', 'details2', 'details3']:
stat2[x] = repo.pk
results.append(stat2)
results = sorted(results, key=lambda x: x['name'])
return json.dumps(results)
def add_stat(author, repo):
stat1 = Statistic.queryset_for_range(repo,
author=author,
start=scope.start,
end=scope.end,
interval=scope.interval)
stat2 = Statistic.compute_interval_statistic(stat1,
interval=scope.interval,
repo=repo,
author=author,
start=scope.start,
end=scope.end)
stat2 = stat2.to_dict()
stat2['author'] = author.email
stat2['repo'] = repo.name
if stat2['lines_changed']:
# skip authors with no contribution in the time range
results.append(stat2)