api/pages/issue/issues.py (151 lines of code) (raw):
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
########################################################################
# OPENAPI-URI: /api/issue/issues
########################################################################
# get:
# responses:
# '200':
# content:
# application/json:
# schema:
# $ref: '#/components/schemas/Timeseries'
# description: 200 Response
# default:
# content:
# application/json:
# schema:
# $ref: '#/components/schemas/Error'
# description: unexpected error
# security:
# - cookieAuth: []
# summary: Shows timeseries of issues opened/closed over time
# post:
# requestBody:
# content:
# application/json:
# schema:
# $ref: '#/components/schemas/defaultWidgetArgs'
# responses:
# '200':
# content:
# application/json:
# schema:
# $ref: '#/components/schemas/Timeseries'
# description: 200 Response
# default:
# content:
# application/json:
# schema:
# $ref: '#/components/schemas/Error'
# description: unexpected error
# security:
# - cookieAuth: []
# summary: Shows timeseries of issues opened/closed over time
#
########################################################################
"""
This is the issue timeseries renderer for Kibble
"""
import json
import time
import hashlib
# This creates an empty timeseries object with
# all categories initialized as 0 opened, 0 closed.
def makeTS(dist):
ts = {}
for k in dist:
ts[k + ' opened'] = 0
ts[k + ' closed'] = 0
return ts
def run(API, environ, indata, session):
# We need to be logged in for this!
if not session.user:
raise API.exception(403, "You must be logged in to use this API endpoint! %s")
now = time.time()
# First, fetch the view if we have such a thing enabled
viewList = []
if indata.get('view'):
viewList = session.getView(indata.get('view'))
if indata.get('subfilter'):
viewList = session.subFilter(indata.get('subfilter'), view = viewList)
dateTo = indata.get('to', int(time.time()))
dateFrom = indata.get('from', dateTo - (86400*30*6)) # Default to a 6 month span
interval = indata.get('interval', 'month')
# By default, we lump PRs and issues into the same category
distinct = {
'issues': ['issue', 'pullrequest']
}
# If requested, we split them into two
if indata.get('distinguish', False):
distinct = {
'issues': ['issue'],
'pull requests': ['pullrequest']
}
timeseries = {}
# For each category and the issue types that go along with that,
# grab opened and closed over time.
for iType, iValues in distinct.items():
####################################################################
# ISSUES OPENED #
####################################################################
dOrg = session.user['defaultOrganisation'] or "apache"
query = {
'query': {
'bool': {
'must': [
{'range':
{
'created': {
'from': dateFrom,
'to': dateTo
}
}
},
{
'term': {
'organisation': dOrg
}
},
{
'terms': {
'issuetype': iValues
}
}
]
}
}
}
# Source-specific or view-specific??
if indata.get('source'):
query['query']['bool']['must'].append({'term': {'sourceID': indata.get('source')}})
elif viewList:
query['query']['bool']['must'].append({'terms': {'sourceID': viewList}})
if indata.get('email'):
query['query']['bool']['must'].append({'term': {'issueCreator': indata.get('email')}})
# Get number of opened ones, this period
query['aggs'] = {
'commits': {
'date_histogram': {
'field': 'createdDate',
'interval': interval
}
}
}
res = session.DB.ES.search(
index=session.DB.dbname,
doc_type="issue",
size = 0,
body = query
)
for bucket in res['aggregations']['commits']['buckets']:
ts = int(bucket['key'] / 1000)
count = bucket['doc_count']
timeseries[ts] = timeseries.get(ts, makeTS(distinct))
timeseries[ts][iType + ' opened'] = timeseries[ts].get(iType + ' opened', 0) + count
####################################################################
# ISSUES CLOSED #
####################################################################
dOrg = session.user['defaultOrganisation'] or "apache"
query = {
'query': {
'bool': {
'must': [
{'range':
{
'closed': {
'from': dateFrom,
'to': dateTo
}
}
},
{
'term': {
'organisation': dOrg
}
},
{
'terms': {
'issuetype': iValues
}
}
]
}
}
}
if viewList:
query['query']['bool']['must'].append({'terms': {'sourceID': viewList}})
if indata.get('source'):
query['query']['bool']['must'].append({'term': {'sourceID': indata.get('source')}})
if indata.get('email'):
query['query']['bool']['must'].append({'term': {'issueCloser': indata.get('email')}})
# Get number of closed ones, this period
query['aggs'] = {
'commits': {
'date_histogram': {
'field': 'closedDate',
'interval': interval
}
}
}
res = session.DB.ES.search(
index=session.DB.dbname,
doc_type="issue",
size = 0,
body = query
)
for bucket in res['aggregations']['commits']['buckets']:
ts = int(bucket['key'] / 1000)
count = bucket['doc_count']
timeseries[ts] = timeseries.get(ts, makeTS(distinct))
timeseries[ts][iType + ' closed'] = timeseries[ts].get(iType + ' closed', 0) + count
ts = []
for k, v in timeseries.items():
v['date'] = k
ts.append(v)
JSON_OUT = {
'widgetType': {
'chartType': 'line', # Recommendation for the UI
'nofill': True
},
'timeseries': ts,
'interval': interval,
'okay': True,
'distinguishable': True,
'responseTime': time.time() - now
}
yield json.dumps(JSON_OUT)