def get_master_errors(stream):
hit = keen.extraction(stream, 'this_3_years', filters=[
{"property_name": "branch", "operator": "eq",
"property_value": 'HEAD'}])
if not hit:
raise ValueError('No data for master branch found')
return hit[-1]
def get_latest_buildtime(repo=None):
"""
Query Keen.io database and retrieve buildtime duration of last build.
Parameters :
- repo : repo name (fe. buildtimetrend/python-lib)
"""
if repo is None or not is_readable():
return -1
try:
result = keen.extraction(
"build_jobs",
property_names="job.duration",
latest=1,
filters=[get_repo_filter(repo)]
)
except requests.ConnectionError:
logger.error("Connection to Keen.io API failed")
return -1
except keen.exceptions.KeenApiError as msg:
logger.error("Error in keenio.get_latest_buildtime() : " + str(msg))
return -1
if is_list(result) and len(result) > 0 and \
check_dict(result[0], None, ['job']) and \
check_dict(result[0]['job'], None, ['duration']):
return result[0]['job']['duration']
return -1
def test_extraction(self, get):
get.return_value = self.LIST_RESPONSE
resp = keen.extraction("query test",
timeframe="today",
property_names=["number"])
self.assertEqual(type(resp), list)
for event in resp:
self.assertTrue("string" not in event)
def query():
final_filter = []
"""Custom queries using keen.io as a backend.
The frontent form must pass values in using the names
`property_name` - The name of the property you wish to query
`property_value` - The value of the property being entered
`operator` - 'eq', 'gt', 'lt'
"""
if current_user.user_type != 'admin':
return 403
if request.method == 'POST':
# Run the query
# Used to display the query filters on the view.
filter_view = [request.form.to_dict()]
number_of_filters = len(request.form) / 3
for filter_number in range(0, number_of_filters):
temp = {}
temp['operator'] = request.form["operator" + str(filter_number)]
temp['property_value'] = request.form["property_value" +
str(filter_number)]
temp['property_name'] = request.form["property_name" +
str(filter_number)]
final_filter.append(temp)
response = keen.extraction('answers', filters=final_filter)
if len(response) == 0:
response = 'No results found'
final_filter = json.dumps(final_filter)
# response = json.dumps(response, indent=2, sort_keys=True)
return render_template('custom_analysis.haml',
filters=final_filter,
questions=Question.get_active(),
filter_view=filter_view,
number_of_filters=number_of_filters,
response=response)
return 'Why'
def test_extraction(self):
resp = keen.extraction("query test", timeframe="today")
self.assertEqual(type(resp), list)
def get_master_errors(stream):
hit = keen.extraction(stream, 'this_5_years', filters=[
{"property_name": "commit", "operator": "eq", "property_value": remote_head}])
if not hit:
raise ValueError('No data for master branch found')
return hit[-1]
def test_extraction(self):
resp = keen.extraction("query test", timeframe="today")
assert type(resp) is list
def test_extraction(self, get):
get.return_value = self.LIST_RESPONSE
resp = keen.extraction("query test", timeframe="today", property_names=["number"])
self.assertEqual(type(resp), list)
for event in resp:
self.assertTrue("string" not in event)
def test_extraction(self):
resp = keen.extraction("query test", timeframe="today")
assert isinstance(resp, list)
def test_extraction(self):
resp = keen.extraction("query test", timeframe="today", property_names=["number"])
self.assertEqual(type(resp), list)
for event in resp:
self.assertTrue("string" not in event)
def test_extraction(self):
resp = keen.extraction("query test", timeframe="today")
assert type(resp) is list
import sys
import csv
import matplotlib.pyplot as plt
import numpy as num
import jdcal
import dateutil
import astropy.time
plt.ion()
duration = input("Duration of analysis until now in days or hours (nd or nh) : ")
if duration[-1:] == 'd' or duration[-1:] == 'D':
tf = "this_"+duration[:-1]+"_days"
if duration[-1:] == 'h' or duration[-1:] == 'H':
tf = "this_"+duration[:-1]+"_hours"
c = keen.extraction("Beehive_MyDatas", property_names="data", timeframe=tf)
ds = keen.extraction("Beehive_MyDatas", property_names="published_at", timeframe=tf)
ne = len(c)
tb = num.empty([ne,5],num.float)
tt = num.empty([ne],num.float)
for i in range(ne):
for j in range(5):
tb[i,j] = float(c[i]['data'].split(" ")[2*j+1])
# parsing de la date pour convertir en julien
dss = ds[i]['published_at']
dt1 = dss.split('-')
dt2 = dt1[-1].split('T')
dt3 = dt2[-1].split(':')
dt4 = dt3[-1].split('Z')
sd = dt1[0]+'.'+dt1[1]+'.'+dt2[0] # year, month, day
