def index():
stats = stats_lib.Stats()
extra_vars = {
u'largest_groups': stats.largest_groups(),
u'top_tags': stats.top_tags(),
u'top_package_creators': stats.top_package_creators(),
}
return render(u'ckanext/stats/index.html', extra_vars)
def top_tags(self):
response.content_type = 'application/json; charset=UTF-8'
stats = stats_lib.Stats()
top_tags = stats.top_tags()
data = {}
for tag, num_packages in top_tags:
data[tag.name] = str(num_packages)
data = {"top_tags" : json.dumps(data, ensure_ascii=False)}
return json.dumps(data)
def index():
stats = stats_lib.Stats()
extra_vars: dict[str, Any] = {
'largest_groups': stats.largest_groups(),
'top_tags': stats.top_tags(),
'top_package_creators': stats.top_package_creators(),
'most_edited_packages': stats.most_edited_packages(),
'new_packages_by_week': stats.get_by_week('new_packages'),
'deleted_packages_by_week': stats.get_by_week('deleted_packages'),
'num_packages_by_week': stats.get_num_packages_by_week(),
'package_revisions_by_week': stats.get_by_week('package_revisions')
}
extra_vars['raw_packages_by_week'] = []
for week_date, num_packages, cumulative_num_packages\
in stats.get_num_packages_by_week():
extra_vars['raw_packages_by_week'].append({
'date':
h.date_str_to_datetime(week_date),
'total_packages':
cumulative_num_packages
})
extra_vars['raw_all_package_revisions'] = []
for week_date, _revs, num_revisions, _cumulative_num_revisions\
in stats.get_by_week('package_revisions'):
extra_vars['raw_all_package_revisions'].append({
'date':
h.date_str_to_datetime(week_date),
'total_revisions':
num_revisions
})
extra_vars['raw_new_datasets'] = []
for week_date, _pkgs, num_packages, _cumulative_num_revisions\
in stats.get_by_week('new_packages'):
extra_vars['raw_new_datasets'].append({
'date':
h.date_str_to_datetime(week_date),
'new_packages':
num_packages
})
extra_vars['raw_deleted_datasets'] = []
for week_date, _pkgs, num_packages, cumulative_num_packages\
in stats.get_by_week('deleted_packages'):
extra_vars['raw_deleted_datasets'].append({
'date':
h.date_str_to_datetime(week_date),
'deleted_packages':
num_packages
})
return render(u'ckanext/stats/index.html', extra_vars)
def index():
stats = stats_lib.Stats()
rev_stats = stats_lib.RevisionStats()
c.top_rated_packages = stats.top_rated_packages()
c.most_edited_packages = stats.most_edited_packages()
c.largest_groups = stats.largest_groups()
c.top_tags = stats.top_tags()
c.top_package_creators = stats.top_package_creators()
c.new_packages_by_week = rev_stats.get_by_week(u'new_packages')
c.deleted_packages_by_week = rev_stats.get_by_week(u'deleted_packages')
c.num_packages_by_week = rev_stats.get_num_packages_by_week()
c.package_revisions_by_week = rev_stats.get_by_week(u'package_revisions')
c.raw_packages_by_week = []
for (
week_date, num_packages, cumulative_num_packages
) in c.num_packages_by_week:
c.raw_packages_by_week.append({
u'date': h.date_str_to_datetime(week_date),
u'total_packages': cumulative_num_packages
})
c.all_package_revisions = []
c.raw_all_package_revisions = []
for (
week_date, revs, num_revisions, cumulative_num_revisions
) in c.package_revisions_by_week:
c.all_package_revisions.append(
u'[new Date(%s), %s]' %
(week_date.replace(u'-', u','), num_revisions)
)
c.raw_all_package_revisions.append({
u'date': h.date_str_to_datetime(week_date),
u'total_revisions': num_revisions
})
c.new_datasets = []
c.raw_new_datasets = []
for (
week_date, pkgs, num_packages, cumulative_num_packages
) in c.new_packages_by_week:
c.new_datasets.append(
u'[new Date(%s), %s]' %
(week_date.replace(u'-', u','), num_packages)
)
c.raw_new_datasets.append({
u'date': h.date_str_to_datetime(week_date),
u'new_packages': num_packages
})
return render(u'ckanext/stats/index.html')
def mlg_top_tags(showtags=10): import ckanext.stats.stats as ckanstats classtags = ckanstats.Stats() return classtags.top_tags(limit=showtags)
def index(self):
stats = stats_lib.Stats()
rev_stats = stats_lib.RevisionStats()
stats_response = {
'top_rated_packages': stats.top_rated_packages(),
'most_edited_packages': [],
'largest_groups': [],
'top_tags': [],
'top_package_creators': [],
'new_packages_by_week': rev_stats.get_by_week('new_packages'),
'deleted_packages_by_week':
rev_stats.get_by_week('deleted_packages'),
'num_packages_by_week': rev_stats.get_num_packages_by_week(),
'package_revisions_by_week':
rev_stats.get_by_week('package_revisions'),
'raw_packages_by_week': [],
'all_package_revisions': [],
'raw_all_package_revisions': [],
'new_datasets': [],
'raw_new_datasets': [],
}
for p in stats.most_edited_packages():
stats_response['most_edited_packages'].append({
'title': p[0].title,
'name': p[0].name,
'count': p[1]
})
for p in stats.largest_groups():
stats_response['largest_groups'].append({
'title': p[0].title,
'name': p[0].name,
'count': p[1]
})
for p in stats.top_tags():
stats_response['top_tags'].append({
'name': p[0].name,
'count': p[1]
})
for p in stats.top_package_creators():
stats_response['top_package_creators'].append({
'id':
p[0].id,
'name':
p[0].name,
'fullname':
p[0].fullname,
'gravatar':
hashlib.md5(p[0].email.lower()).hexdigest(),
'count':
p[1]
})
for week_date, num_packages, cumulative_num_packages in stats_response[
'num_packages_by_week']:
stats_response['raw_packages_by_week'].append({
'date':
week_date,
'total_packages':
cumulative_num_packages
})
for week_date, revs, num_revisions, cumulative_num_revisions in stats_response[
'package_revisions_by_week']:
stats_response['all_package_revisions'].append(
'[%s, %s]' % (week_date, num_revisions))
stats_response['raw_all_package_revisions'].append({
'date':
week_date,
'total_revisions':
num_revisions
})
for week_date, pkgs, num_packages, cumulative_num_packages in stats_response[
'new_packages_by_week']:
stats_response['new_datasets'].append('[%s, %s]' %
(week_date, num_packages))
stats_response['raw_new_datasets'].append({
'date':
week_date,
'new_packages':
num_packages
})
return json.dumps(stats_response)
