def get(self,
output_format='xlsx',
user_id=None,
start_time=None,
end_time=None,
limit=None,
offset=None):
"""Export all charges of special user, output formats supported:
* Excel (Sets + Books)
* JSON (Sets + Books)
* YAML (Sets + Books)
* HTML (Sets)
* TSV (Sets)
* CSV (Sets)
"""
if output_format.lower() not in ["xls", "xlsx", "csv", "json", "yaml"]:
raise exception.InvalidOutputFormat(output_format=output_format)
if limit and limit < 0:
raise exception.InvalidParameterValue(err="Invalid limit")
if offset and offset < 0:
raise exception.InvalidParameterValue(err="Invalid offset")
limit_user_id = acl.get_limited_to_user(request.headers,
'export_charges')
if limit_user_id:
user_id = limit_user_id
headers = (u"充值记录ID", u"充值对象用户名", u"充值对象ID", u"充值对象真实姓名", u"充值对象邮箱",
u"充值对象公司", u"充值金额", u"充值类型", u"充值来源", u"充值人员ID", u"充值人员用户名",
u"充值时间", u"状态")
data = []
users = {}
def _get_user(user_id):
user = users.get(user_id)
if user:
return user
contact = kunkka.get_uos_user(user_id) or {}
user_name = contact.get('name')
email = contact.get('email')
real_name = contact.get('real_name') or 'unknown'
mobile = contact.get('phone') or 'unknown'
company = contact.get('company') or 'unknown'
users[user_id] = models.User(user_id=user_id,
user_name=user_name,
email=email,
real_name=real_name,
mobile=mobile,
company=company)
return users[user_id]
self.conn = pecan.request.db_conn
charges = self.conn.get_charges(request.context,
user_id=user_id,
limit=limit,
offset=offset,
start_time=start_time,
end_time=end_time)
for charge in charges:
charge.charge_time += datetime.timedelta(hours=8)
acharge = models.Charge.from_db_model(charge)
acharge.actor = _get_user(charge.operator)
acharge.target = _get_user(charge.user_id)
charge_time = \
timeutils.strtime(charge.charge_time, fmt=OUTPUT_TIME_FORMAT)
adata = (acharge.charge_id, acharge.target.user_name,
acharge.target.user_id, acharge.target.real_name,
acharge.target.email, acharge.target.company,
str(acharge.value), acharge.type, acharge.come_from,
acharge.actor.user_id, acharge.actor.user_name,
charge_time, u"正常")
data.append(adata)
data = tablib.Dataset(*data, headers=headers)
response.content_type = "application/binary; charset=UTF-8"
response.content_disposition = \
"attachment; filename=charges.%s" % output_format
content = getattr(data, output_format)
if output_format == 'csv':
content = content.decode("utf-8").encode("gb2312")
response.write(content)
return response
def subscriber_export(request):
"""Export CSV file of subscriber record
**Important variable**:
* ``request.session['subscriber_list_kwargs']`` - stores subscriber_list kwargs
**Exported fields**: ['contact', 'updated_date', 'count_attempt',
'completion_count_attempt', 'status', 'disposition',
'collected_data', 'agent']
"""
format_type = request.GET['format']
# get the response object, this can be used as a stream.
response = HttpResponse(content_type='text/%s' % format_type)
# force download.
response[
'Content-Disposition'] = 'attachment;filename=export.%s' % format_type
if request.session.get('subscriber_list_kwargs'):
kwargs = request.session['subscriber_list_kwargs']
if request.user.is_superuser:
subscriber_list = Subscriber.objects.all()
else:
subscriber_list = Subscriber.objects.filter(
campaign__user=request.user)
if kwargs:
subscriber_list = subscriber_list.filter(**kwargs)
headers = (
'contact',
'updated_date',
'count_attempt',
'completion_count_attempt',
'status',
'disposition',
'collected_data',
) # 'agent',
list_val = []
for i in subscriber_list:
updated_date = i.updated_date
if format_type == Export_choice.JSON or Export_choice.XLS:
updated_date = str(i.updated_date)
list_val.append((
i.contact.contact,
updated_date,
i.count_attempt,
i.completion_count_attempt,
get_subscriber_status(i.status),
get_subscriber_disposition(i.campaign_id, i.disposition),
i.collected_data,
# i.agent,
))
data = tablib.Dataset(*list_val, headers=headers)
if format_type == Export_choice.XLS:
response.write(data.xls)
elif format_type == Export_choice.CSV:
response.write(data.csv)
elif format_type == Export_choice.JSON:
response.write(data.json)
return response
def main():
downloader = None
parser = argparse.ArgumentParser()
parser.add_argument("-i", "--insecure", help="use HTTP instead of HTTPS", action="store_true")
parser.add_argument("-e", "--export", help="export immediately without downloading (Only useful if you already downloaded something to the .pickle file)", action="store_true")
parser.add_argument('-E', '--Exchange', help='Only export ticker symbols from this exchange (the filtering is done during the export phase)')
parser.add_argument('type', nargs='?', default='generic', help='The type to download, this can be: '+" ".join(list(options.keys())))
parser.add_argument("-s", "--sleep", help="The time to sleep in seconds between requests", type=float, default=0)
parser.add_argument("-p", "--pandantic", help="Stop and warn the user if some rare assertion fails", action="store_true")
args = parser.parse_args()
protocol = 'http' if args.insecure else 'https'
if args.insecure:
print("Using insecure connection")
if args.export:
print("Exporting pickle file")
tickerType = args.type = args.type.lower()
print("Checking if we can resume a old download session")
try:
downloader = loadDownloader(tickerType)
print("Downloader found on disk, resuming")
except:
print("No old downloader found on disk")
print("Starting a new session")
if tickerType not in options:
print("Error: " + tickerType + " is not a valid type option. See --help")
exit(1)
else:
downloader = options[tickerType]
rp = robotparser.RobotFileParser()
rp.set_url(protocol + '://finance.yahoo.com/robots.txt')
rp.read()
try:
if not args.export:
if(not rp.can_fetch(user_agent, protocol + '://finance.yahoo.com/_finance_doubledown/api/resource/searchassist')):
print('Execution of script halted due to robots.txt')
return 1
if not downloader.isDone():
print("Downloading " + downloader.type)
print("")
downloadEverything(downloader, tickerType, args.insecure, args.sleep, args.pandantic)
print ("Saving downloader to disk...")
saveDownloader(downloader, tickerType)
print ("Downloader successfully saved.")
print ("")
else:
print("The downloader has already finished downloading everything")
print("")
except Exception as ex:
print("A exception occurred while downloading. Suspending downloader to disk")
saveDownloader(downloader, tickerType)
print("Successfully saved download state")
print("Try removing {type}.pickle file if this error persists")
print("Issues can be reported on https://github.com/Benny-/Yahoo-ticker-symbol-downloader/issues")
print("")
raise
except KeyboardInterrupt as ex:
print("Suspending downloader to disk as .pickle file")
saveDownloader(downloader, tickerType)
if downloader.isDone() or args.export:
print("Exporting "+downloader.type+" symbols")
data = tablib.Dataset()
data.headers = downloader.getRowHeader()
for symbol in downloader.getCollectedSymbols():
if(args.Exchange == None):
data.append(symbol.getRow())
elif (symbol.exchange == args.Exchange):
data.append(symbol.getRow())
with io.open(downloader.type + '.csv', 'w', encoding='utf-8') as f:
f.write(text.join(u',', data.headers) + '\n')
writer = csv.writer(f)
for i in range(0, len(data)):
row = [text(y) if not y is None else u"" for y in data[i]]
writer.writerow(row)
try:
with open(downloader.type + '.xlsx', 'wb') as f:
f.write(data.xlsx)
except:
print("Could not export .xlsx due to a internal error")
try:
with open(downloader.type + '.json', 'wb') as f:
f.write(data.json.encode('UTF-8'))
except:
print("Could not export .json due to a internal error")
try:
with open(downloader.type + '.yaml', 'wb') as f:
f.write(data.yaml.encode('UTF-8'))
except:
print("Could not export .yaml due to a internal error")
def export_surveycall_report(request):
"""Export CSV file of Survey VoIP call record
**Important variable**:
* ``request.session['surveycall_record_qs']`` - stores survey voipcall
query set
**Exported fields**: ['starting_date', 'phone_number', 'duration',
'disposition', 'survey results']
"""
format = request.GET['format']
# get the response object, this can be used as a stream.
response = HttpResponse(mimetype='text/' + format)
# force download.
response['Content-Disposition'] = 'attachment;filename=export.' + format
#writer = csv.writer(response)
if request.session.get('session_surveycalls_kwargs'):
kwargs = request.session.get('session_surveycalls_kwargs')
qs = VoIPCall.objects.filter(**kwargs)
campaign_id = request.session['session_campaign_id']
campaign_obj = Campaign.objects.get(pk=campaign_id)
column_list_base = [
'starting_date', 'phone_number', 'duration', 'disposition'
]
column_list = list(column_list_base)
survey_qst = False
if campaign_obj.content_type.model == 'survey':
survey_qst = Section.objects.filter(
survey_id=int(campaign_obj.object_id))
for i in survey_qst:
column = unicode(i.question.replace(',', ' '))
column_list.append(column.encode('utf-8'))
result_row = []
for voipcall in qs:
result_row_list = []
#For each voip call retrieve the results of the survey nodes
results = Result.objects.filter(
callrequest=voipcall.callrequest_id).order_by('section')
result_list = {}
#We will prepare a dictionary result_list to help exporting the result
for result in results:
if result.record_file and len(result.record_file) > 0:
result_list[result.section.question] = result.record_file
else:
result_list[result.section.question] = result.response
#We will build result_row_list which will be a value for each element from column_list
for ikey in column_list:
if ikey in column_list_base:
#This is not a Section result
if ikey == 'starting_date' and format == 'json':
starting_date = str(voipcall.__dict__[ikey])
result_row_list.append(starting_date)
else:
result_row_list.append(voipcall.__dict__[ikey])
else:
#This is a Section result
if ikey in result_list:
result_row_list.append(
result_list[ikey].encode('utf-8'))
else:
#Add empty result
result_row_list.append("")
result_row.append(result_row_list)
data = tablib.Dataset(*result_row, headers=tuple(column_list))
if format == 'xls':
response.write(data.xls)
if format == 'csv':
response.write(data.csv)
if format == 'json':
response.write(data.json)
return response
def export_aggregated_events(pj, parameters, obsId):
"""
export aggregated events
Args:
pj (dict): BORIS project
parameters (dict): subjects, behaviors
obsId (str): observation id
Returns:
tablib.Dataset:
"""
data = tablib.Dataset()
observation = pj[OBSERVATIONS][obsId]
duration1 = [] # in seconds
if observation[TYPE] in [MEDIA]:
try:
for mediaFile in observation[FILE][PLAYER1]:
if "media_info" in observation:
duration1.append(
observation["media_info"]["length"][mediaFile])
except:
duration1 = []
total_length = "{0:.3f}".format(
project_functions.observation_total_length(observation))
ok, msg, connector = db_functions.load_aggregated_events_in_db(
pj, parameters["selected subjects"], [obsId],
parameters["selected behaviors"])
if not ok:
data
cursor = connector.cursor()
for subject in parameters["selected subjects"]:
for behavior in parameters["selected behaviors"]:
cursor.execute(
"select distinct modifiers from aggregated_events where subject=? AND behavior=? order by modifiers",
(
subject,
behavior,
))
rows_distinct_modifiers = list(x[0].strip()
for x in cursor.fetchall())
for distinct_modifiers in rows_distinct_modifiers:
cursor.execute((
"SELECT start, stop, type, modifiers, comment, comment_stop FROM aggregated_events "
"WHERE subject = ? AND behavior = ? AND modifiers = ? ORDER by start"
), (subject, behavior, distinct_modifiers))
rows = list(cursor.fetchall())
for row in rows:
if observation[TYPE] in [MEDIA]:
if duration1:
mediaFileIdx = [
idx1 for idx1, x in enumerate(duration1)
if row["start"] >= sum(duration1[0:idx1])
][-1]
mediaFileString = observation[FILE][PLAYER1][
mediaFileIdx]
fpsString = observation["media_info"]["fps"][
observation[FILE][PLAYER1][mediaFileIdx]]
else:
mediaFileString = "-"
fpsString = "NA"
if observation[TYPE] in [LIVE]:
mediaFileString = "LIVE"
fpsString = "NA"
#if POINT in project_functions.event_type(behavior, pj[ETHOGRAM]):
if row["type"] == POINT:
row_data = []
row_data.extend([
obsId, observation["date"].replace("T", " "),
mediaFileString, total_length, fpsString
])
# independent variables
if INDEPENDENT_VARIABLES in pj:
for idx_var in utilities.sorted_keys(
pj[INDEPENDENT_VARIABLES]):
if pj[INDEPENDENT_VARIABLES][idx_var][
"label"] in observation[
INDEPENDENT_VARIABLES]:
row_data.append(
observation[INDEPENDENT_VARIABLES][
pj[INDEPENDENT_VARIABLES][idx_var]
["label"]])
else:
row_data.append("")
row_data.extend([
subject,
behavior,
row["modifiers"].strip(),
POINT,
"{0:.3f}".format(row["start"]), # start
"{0:.3f}".format(row["stop"]), # stop
"NA", # duration
row["comment"],
""
])
data.append(row_data)
#if STATE in project_functions.event_type(behavior, pj[ETHOGRAM]):
if row["type"] == STATE:
if idx % 2 == 0:
row_data = []
row_data.extend([
obsId, observation["date"].replace("T", " "),
mediaFileString, total_length, fpsString
])
# independent variables
if INDEPENDENT_VARIABLES in pj:
for idx_var in utilities.sorted_keys(
pj[INDEPENDENT_VARIABLES]):
if pj[INDEPENDENT_VARIABLES][idx_var][
"label"] in observation[
INDEPENDENT_VARIABLES]:
row_data.append(
observation[INDEPENDENT_VARIABLES]
[pj[INDEPENDENT_VARIABLES][idx_var]
["label"]])
else:
row_data.append("")
row_data.extend([
subject, behavior, row["modifiers"].strip(),
STATE, "{0:.3f}".format(row["start"]),
"{0:.3f}".format(row["stop"]),
"{0:.3f}".format(row["stop"] - row["start"]),
row["comment"], row["comment_stop"]
])
data.append(row_data)
return data
def export_assets(self, request, queryset):
asset_workbook = tablib.Databook()
participants_headers = (
'DB_id',
'Nr Procesu',
'Lp. procedury do procesu',
'Nazwa uczestnika',
'Skrót nazwy',
'Nazwa zadania realizowanego przez uczestnika',
'Zakres niezbędny do realizacji działań na minimalnym poziomie\
, wymienionych w kolumnach po prawej',
)
participants = tablib.Dataset(
title='Uczestnicy',
headers=participants_headers,
)
participants.append(['', 'Priority', '', '', '', '', ''])
external_suppliers_headers = (
'DB_id',
'Nr Procesu',
'Lp. procedury do procesu',
'Nazwa uczestnika',
'Nazwa zadania realizowanego przez uczestnika',
'Zakres niezbędny do realizacji działań na minimalnym poziomie\
, wymienionych w kolumnach po prawej',
)
external_suppliers = tablib.Dataset(
title='Uczestnicy zewn.',
headers=external_suppliers_headers,
)
external_suppliers.append(['', 'Priority', '', '', '', ''])
personnel_headers = (
'Nr Procesu',
'Nazwa komórki org.',
'Skrót komórki org.',
'Nazwa stanowiska',
'Wymagane uprawnienia, kompetencje (uwagi)',
'Liczba osób',
)
personnel = tablib.Dataset(
title='Pracownicy',
headers=personnel_headers,
)
personnel.append(['Priority', '', '', '', '', ''])
locations_headers = (
'Nr Procesu',
'Nazwa komórki org. zarządzającej lokalizacją',
'Skrót komórki org.',
'Nazwa lokalizacji',
'Dodatkowe wymagania/uwagi dot. lokalizacji',
'Liczba lokalizacji',
'Adres (dla lokalizacji pojedynczych)',
)
locations = tablib.Dataset(
title='Lokalizacje',
headers=locations_headers,
)
locations.append(['Priority', '', '', '', '', '', ''])
office_equipment_headers = (
'Nr Procesu',
'Nazwa urządzenia',
'Model, typ (jeśli ma znaczenie)',
'Dodatkowe wymagania/uwagi dot. urządzenia',
'Ilość',
'Nazwy stanowiska użytkownika (dla urządzeń przyporządkowanych \
konkretnej osobie)',
)
office_equipment = tablib.Dataset(
title='Infr. biurowa i peryferia',
headers=office_equipment_headers,
)
office_equipment.append(['Priority', '', '', '', '', ''])
supplies_headers = (
'Nr Procesu',
'Nazwa materiału',
'Model, typ (jeśli ma znaczenie)',
'Dodatkowe wymagania/uwagi',
'Minimalny zapas',
'Nazwy stanowiska użytkownika (dla urządzeń przyporządkowanych \
konkretnej osobie)',
)
supplies = tablib.Dataset(
title='Materiały eksploat.',
headers=supplies_headers,
)
supplies.append(['Priority', '', '', '', '', ''])
applications_headers = (
'DB_id',
'Nr Procesu',
'Lp. procedury do procesu',
'Nazwa zadania realizowanego z wykorzystaniem aplikacji',
'Skrót nazwy aplikacji',
'Dodatkowe uwagi dot. aplikacji',
'Liczba licencji',
'Nazwy stanowiska użytkownika (dla licencji pojedynczych)',
)
applications = tablib.Dataset(
title='Aplikacje',
headers=applications_headers,
)
applications.append(['', 'Priority', '', '', '', '', '', ''])
documentation_headers = (
'DB_id',
'Nr Procesu',
'Lp. procedury do procesu',
'Opis zadania',
'Nazwa dokumentu/informacji',
'Wejście / wyjście',
'Opis, uwagi dodatkowe',
'Miejsce przechowywania/ścieżka dostępu/źródło zewnetrzne',
'Klasa bezpieczeństwa',
)
documentation = tablib.Dataset(title='Dokumentacja',
headers=documentation_headers)
documentation.append(['', 'Priority', '', '', '', '', '', '', ''])
app_list = tablib.Dataset(title='Lista aplikacji', )
app_list.dict = models.BusinessApp.objects.\
order_by('name').all().values()
org_list = tablib.Dataset(title='Lista jednostek', )
org_list.dict = models.OrgUnit.objects.order_by(
'org_unit_type', 'name').all().values()
print('START OF PROCESSING')
for activity in queryset.order_by('MTPD'):
print('ACTIVITY: %s' % (activity))
act_col = []
act_col.append(activity.MTPD)
while len(participants) > len(act_col):
act_col.append('')
participants.append_col(act_col, header=activity.name)
act_col = []
act_col.append(activity.MTPD)
while len(external_suppliers) > len(act_col):
act_col.append('')
external_suppliers.append_col(act_col, header=activity.name)
act_col = []
act_col.append(activity.MTPD)
while len(personnel) > len(act_col):
act_col.append('')
personnel.append_col(act_col, header=activity.name)
act_col = []
act_col.append(activity.MTPD)
while len(locations) > len(act_col):
act_col.append('')
locations.append_col(act_col, header=activity.name)
act_col = []
act_col.append(activity.MTPD)
while len(office_equipment) > len(act_col):
act_col.append('')
office_equipment.append_col(act_col, header=activity.name)
act_col = []
act_col.append(activity.MTPD)
while len(supplies) > len(act_col):
act_col.append('')
supplies.append_col(act_col, header=activity.name)
act_col = []
act_col.append(activity.MTPD)
while len(applications) > len(act_col):
act_col.append('')
applications.append_col(act_col, header=activity.name)
act_col = []
act_col.append(activity.MTPD)
while len(documentation) > len(act_col):
act_col.append('')
documentation.append_col(act_col, header=activity.name)
print('PREPARED FOR WORK TASKS')
bcm_process = activity.process
print('ACTIONS:')
io_data = tablib.Dataset()
for act in bcm_process.procedure.action_set.all():
if act.trigger_type != 1 and act.effects_type != 1:
continue
existing = False
iter = 0
for r in documentation:
iter = iter + 1
if r[0] != act.id or \
r[1] != act.procedure.process.proc_id or \
r[2] != act.in_process_step:
continue
if (r[5] == 'Wejścia do działania' and r[4] == act.trigger)\
or (r[5] == 'Wyjście z działania' and \
r[4] == act.effects):
existing = True
doc_row = []
for idx in range(len(r) - 1):
doc_row.append(r[idx])
print('FOUND: %s' % (doc_row, ))
print('USUWAM: %s' % (documentation[iter - 1], ))
del documentation[iter - 1]
while (documentation.width - len(doc_row)) > 1:
doc_row.append('')
doc_row.append(activity.MTPD)
print('DODAJĘ: %s' % (doc_row, ))
documentation.append(doc_row)
if existing:
continue
else:
if act.trigger_type == 1:
doc_row = []
doc_row.append(act.id)
doc_row.append(act.procedure.process.proc_id)
doc_row.append(act.in_process_step)
doc_row.append(act.name)
doc_row.append(act.trigger)
doc_row.append('Wejścia do działania')
doc_row.append('')
doc_row.append('')
doc_row.append('')
while (documentation.width - len(doc_row)) > 1:
doc_row.append('')
doc_row.append(activity.MTPD)
print('DODAJĘ: %s' % (doc_row, ))
documentation.append(doc_row)
if act.effects_type == 1:
doc_row = []
doc_row.append(act.id)
doc_row.append(act.procedure.process.proc_id)
doc_row.append(act.in_process_step)
doc_row.append(act.name)
doc_row.append(act.effects)
doc_row.append('Wyjście z działania')
doc_row.append('')
doc_row.append('')
doc_row.append('')
while (documentation.width - len(doc_row)) > 1:
doc_row.append('')
doc_row.append(activity.MTPD)
print('DODAJĘ: %s' % (doc_row, ))
documentation.append(doc_row)
# print('MERGING DOCUMENTATION DATASETS')
# documentation = documentation.stack(io_data)
print(documentation)
io_data.wipe()
for wt in activity.tasks.order_by(
'action__procedure__process__proc_id',
'action__in_process_step',
).all():
for eu in wt.executive_units.all():
existing = False
iter = 0
for r in participants:
iter = iter + 1
if r[0] != eu.id:
continue
if r[1] != activity.process.proc_id:
continue
if r[2] != wt.action.in_process_step:
continue
if r[5] != wt.task:
continue
existing = True
eu_row = []
for idx in range(len(r) - 1):
eu_row.append(r[idx])
print('FOUND: %s' % (eu_row, ))
print('USUWAM: %s' % (participants[iter - 1], ))
del participants[iter - 1]
while (participants.width - len(eu_row)) > 1:
eu_row.append('')
eu_row.append(activity.MTPD)
print('DODAJĘ: %s' % (eu_row, ))
participants.append(eu_row)
break
if existing:
continue
else:
eu_row = []
eu_row.append(eu.id)
eu_row.append(activity.process.proc_id)
eu_row.append(wt.action.in_process_step)
eu_row.append(eu.name)
eu_row.append(eu.acronym)
eu_row.append(wt.task)
eu_row.append(
'do uzupełnienia na podstawie minimalnego \
wymaganego poziomu odtworzenia działania')
while (participants.width - len(eu_row)) > 1:
eu_row.append('')
eu_row.append(activity.MTPD)
print('DODAJĘ: %s' % (eu_row, ))
participants.append(eu_row)
for cu in wt.cooperative_units.all():
existing = False
iter = 0
for r in participants:
iter = iter + 1
if r[0] != cu.id:
continue
if r[1] != activity.process.proc_id:
continue
if r[2] != wt.action.in_process_step:
continue
if r[5] != wt.task:
continue
existing = True
cu_row = []
for idx in range(len(r) - 1):
cu_row.append(r[idx])
print('FOUND: %s' % (cu_row, ))
print('USUWAM: %s' % (participants[iter - 1], ))
del participants[iter - 1]
while (participants.width - len(cu_row)) > 1:
cu_row.append('')
cu_row.append(activity.MTPD)
print('DODAJĘ: %s' % (cu_row, ))
participants.append(cu_row)
break
if existing:
continue
else:
cu_row = []
cu_row.append(cu.id)
cu_row.append(activity.process.proc_id)
cu_row.append(wt.action.in_process_step)
cu_row.append(cu.name)
cu_row.append(cu.acronym)
cu_row.append(wt.task)
cu_row.append(
'do uzupełnienia na podstawie minimalnego \
wymaganego poziomu odtworzenia działania')
while (participants.width - len(cu_row)) > 1:
cu_row.append('')
cu_row.append(activity.MTPD)
print('DODAJĘ: %s' % (cu_row, ))
participants.append(cu_row)
for st in wt.stakeholders.filter(type__exact=False):
existing = False
iter = 0
for r in external_suppliers:
iter = iter + 1
if r[0] != st.id:
continue
if r[1] != activity.process.proc_id:
continue
if r[2] != wt.action.in_process_step:
continue
if r[4] != wt.task:
continue
existing = True
st_row = []
for idx in range(len(r) - 1):
st_row.append(r[idx])
print('FOUND: %s' % (st_row, ))
print('USUWAM: %s' % (external_suppliers[iter - 1], ))
del external_suppliers[iter - 1]
while (external_suppliers.width - len(st_row)) > 1:
st_row.append('')
st_row.append(activity.MTPD)
print('DODAJĘ: %s' % (st_row, ))
external_suppliers.append(st_row)
break
if existing:
continue
else:
st_row = []
st_row.append(st.id)
st_row.append(activity.process.proc_id)
st_row.append(wt.action.in_process_step)
st_row.append(st.name)
st_row.append(wt.task)
st_row.append(
'do uzupełnienia na podstawie minimalnego \
wymaganego poziomu odtworzenia działania')
while (external_suppliers.width - len(st_row)) > 1:
st_row.append('')
st_row.append(activity.MTPD)
external_suppliers.append(st_row)
for ba in wt.business_apps.all():
existing = False
iter = 0
for r in applications:
iter = iter + 1
if r[0] != ba.id:
continue
if r[1] != activity.process.proc_id:
continue
if r[2] != wt.action.in_process_step:
continue
if r[3] != wt.task:
continue
existing = True
ba_row = []
for idx in range(len(r) - 1):
ba_row.append(r[idx])
print('FOUND: %s' % (ba_row, ))
print('USUWAM: %s' % (applications[iter - 1], ))
del applications[iter - 1]
while (applications.width - len(ba_row)) > 1:
ba_row.append('')
ba_row.append(activity.MTPD)
print('DODAJĘ: %s' % (ba_row, ))
applications.append(ba_row)
break
if existing:
continue
else:
ba_row = []
ba_row.append(ba.id)
ba_row.append(activity.process.proc_id)
ba_row.append(wt.action.in_process_step)
ba_row.append(wt.task)
ba_row.append(ba.name)
ba_row.append(ba.description)
ba_row.append('')
ba_row.append('')
while (applications.width - len(ba_row)) > 1:
ba_row.append('')
ba_row.append(activity.MTPD)
print('DODAJĘ: %s' % (ba_row, ))
applications.append(ba_row)
"""
except Exception as e:
return HttpResponse(
_(
u"<h1>%s encountered while</h1>" \
% (type(e).__name__,)
)
)
else:
print('NO EXCEPTION RAISED')
finally:
count_ps = 0
count_es = 0
count_apps = 0
for a in queryset:
for w in a.tasks.all():
count_ps = count_ps + w.executive_units.count()
count_ps = count_ps + w.cooperative_units.count()
count_es = count_es + w.stakeholders.count()
count_apps = count_apps + w.business_apps.count()
print('PARTICIPANTS: %s | %s' % (count_ps, len(participants),))
print('EXTERNAL SRV: %s | %s' % (count_es, len(external_suppliers),))
print('APPLICATIONS: %s | %s' % (count_apps, len(applications),))"""
# participants = participants.sort(col=2)
# participants = participants.sort(col=1)
asset_workbook.add_sheet(participants)
asset_workbook.add_sheet(external_suppliers)
asset_workbook.add_sheet(personnel)
asset_workbook.add_sheet(locations)
asset_workbook.add_sheet(office_equipment)
asset_workbook.add_sheet(supplies)
asset_workbook.add_sheet(applications)
asset_workbook.add_sheet(documentation)
asset_workbook.add_sheet(app_list)
asset_workbook.add_sheet(org_list)
try:
template_file_name = '/app/core/export/template_assets.xlsx'
print('TEMPLATE: %s' % (template_file_name, ))
with open(template_file_name, 'wb') as template:
print('IT IS OPEN')
print('BEFORE_EXPORT')
template.write(asset_workbook.export('xlsx'))
except Exception as e:
return HttpResponse(
_(
u"<h1>%s encountered while trying to read Databook</h1>" \
% (type(e).__name__,)
)
)
import tablib
headers = ('id', 'name')
data = [('test_id_1', 'name_1'), ('test_id_2', 'name_2'),
('test_id_3', 'name_3')]
data = tablib.Dataset(*data, headers=headers)
print(data.export('csv'))
def service_page():
serviceset = tablib.Dataset()
with open(os.path.join(os.path.dirname(__file__),
'serviceAccounts.csv')) as f:
serviceset.csv = f.read()
return serviceset.html
import tablib
headers = ('first_name', 'last_name')
data = [('John', 'Adams'), ('George', 'Washington')]
data = tablib.Dataset(*data, headers=headers)
#print(data)
data.append(('Henry', 'Ford'))
#print(data)
data.append_col((90, 67, 83), header='age')
#print("\n")
#print(data)
# Exporting to JSON
#print(data.export('json'))
# Exporting to YAML
print(data.export('yaml'))
# Exporting to CSV
csv_data = data.export('csv')
print(csv_data)
with open("people.csv", "w") as fd:
fd.write(data.export('csv'))
def view_page():
iamset = tablib.Dataset()
with open(os.path.join(os.path.dirname(__file__),
'projects_iam.csv')) as f:
iamset.csv = f.read()
return iamset.html
def bucket_page():
bucketset = tablib.Dataset()
with open(os.path.join(os.path.dirname(__file__), 'buckets_iam.csv')) as f:
bucketset.csv = f.read()
return bucketset.html
import tablib
# 创建dataset1，方式一：
# dataset1 = tablib.Dataset()
# dataset1.headers = ['id','name','age','sex']
# dataset1.append(['1','朱宇','21','male'])
# dataset1.append(['2','张昊','22','male'])
# 创建dataset2，方式二：
header2 = ['id','name','password']
data = [
['1','杨鹏','123'],
['2','代松柏','567'],
]
dataset2 = tablib.Dataset(headers=header2,*data)
#增
# 增加一行数据(拿dataset2举例子)
dataset2.append(['3','朱宇','123'])
# # 增加一列数据，增加年龄这列数据(实在原有的基础上额)
dataset2.append_col((20,21,22),'age')
# # 行很多时
# import random
# def get_score(row):
# return random.randint(60, 100)
# dataset2.append_col(get_score, headers='score')
# # 查
# # 查看某一行的数据,例如第一行
# dataset2[0]
# # 获取某一列的数据,获取到了score这一列的所有数据
# dataset2['score']
# # 这是通过索引去获取列数据，和上面获取某一行是一样的
# dataset2.get_col(0)
def get_export_data(self, qs, columns):
export_data = tablib.Dataset(headers=[label for key, label in columns] + ['_instance'])
for instance in qs:
export_data.append(self.get_export_data_row(instance, columns) + [instance])
return export_data
def export_xls(cls, proj, ver):
"""
导出图片打分信息为xls文件
:return:
"""
total_imgs = Image.objects.filter(project=proj, version=ver)
resolutions = set(
[r.get('resolution') for r in total_imgs.values("resolution")])
data_set = set()
total_headers = ['名称']
total_stats = tablib.Dataset()
total_stats.title = 'Total Average'
for resolution in resolutions:
imgs = Image.objects.filter(project=proj,
version=ver,
resolution=resolution)
grade_times = [img.get_grade_times() for img in imgs]
width = max(grade_times)
stats = tablib.Dataset()
aver_data = ['Average']
headers = ['名称']
new_col = []
if proj == 'Mark':
stats.title = ver
getter = itemgetter('dem1', 'dem2', 'dem3', 'dem4')
dem_list = ['对焦', '清晰', '曝光', '颜值']
elif proj == 'Zhaidai_Project':
stats.title = resolution
getter = itemgetter('dem1', 'dem2', 'dem3', 'dem4', 'dem5')
dem_list = ['对焦', '清晰', '曝光', '颜值', '纹理']
elif proj == 'AI-case':
stats.title = resolution
getter = itemgetter('dem1', 'dem2', 'dem3', 'dem4')
dem_list = ['振铃效应', '块效应', '噪声', '模糊or失真']
else:
stats.title = resolution
getter = itemgetter('dem1')
dem_list = ['改进空间']
for img in imgs:
data = getter(img.get_stats(width=width))
if isinstance(data, list):
data = (data, )
dct = set(data[0])
if dct == {''}:
continue
row = reduce(add, data)
row.insert(0, img.name)
stats.append(row)
for dem in dem_list:
h = [dem + str(i) for i in (list(range(width)) + ['avg'])]
headers.extend(h)
stats.headers = headers
for header in headers[1:]:
if header.endswith('avg'):
h_list = list(filter(lambda x: x != '', stats[header]))
try:
aver_data.append(
str(round(sum(h_list) / len(h_list), 2)))
except ZeroDivisionError:
aver_data.append(0)
else:
aver_data.append('\\')
stats.append(aver_data)
for s in stats:
data_col = []
for index in range(len(stats.headers)):
if stats.headers[index].endswith('avg'):
data_col.append(float(s[index]))
try:
new_col.append(str(round(sum(data_col) / len(data_col),
2)))
except ZeroDivisionError:
new_col.append(0)
stats.append_col(new_col, header='Average')
dem_list.append('Average')
data_set.add(stats)
last_data = list(stats[-1])
last_data[0] = resolution
filter_aver_data = list(filter(lambda x: x != '\\', last_data))
total_stats.append(filter_aver_data)
total_headers.extend(dem_list)
total_stats.headers = total_headers
total_average = ['Total Average']
for dem in dem_list:
h_list = list(filter(lambda x: x != '', total_stats[dem]))
total_list = [float(x) for x in h_list]
try:
total_average.append(
str(round(sum(total_list) / len(total_list), 2)))
except ZeroDivisionError:
total_average.append(0)
total_stats.append(total_average)
data_set.add(total_stats)
book = tablib.Databook(data_set)
return book.export('xls')
def synthetic_time_budget(pj: dict, selected_observations: list,
parameters_obs: dict):
"""
create a synthetic time budget
Args:
pj (dict): project dictionary
selected_observations (list): list of observations to include in time budget
parameters_obs (dict):
Returns:
bool: True if everything OK
str: message
tablib.Dataset: dataset containing synthetic time budget data
"""
try:
selected_subjects = parameters_obs[SELECTED_SUBJECTS]
selected_behaviors = parameters_obs[SELECTED_BEHAVIORS]
include_modifiers = parameters_obs[INCLUDE_MODIFIERS]
interval = parameters_obs["time"]
start_time = parameters_obs["start time"]
end_time = parameters_obs["end time"]
parameters = [
["duration", "Total duration"],
["number", "Number of occurrences"],
["duration mean", "Duration mean"],
["duration stdev", "Duration std dev"],
["proportion of time", "Proportion of time"],
]
data_report = tablib.Dataset()
data_report.title = "Synthetic time budget"
ok, msg, db_connector = db_functions.load_aggregated_events_in_db(
pj, selected_subjects, selected_observations, selected_behaviors)
if not ok:
return False, msg, None
db_connector.create_aggregate("stdev", 1, StdevFunc)
cursor = db_connector.cursor()
# modifiers
if include_modifiers:
cursor.execute(
"SELECT distinct behavior, modifiers FROM aggregated_events")
distinct_behav_modif = [[rows["behavior"], rows["modifiers"]]
for rows in cursor.fetchall()]
else:
cursor.execute("SELECT distinct behavior FROM aggregated_events")
distinct_behav_modif = [[rows["behavior"], ""]
for rows in cursor.fetchall()]
# add selected behaviors that are not observed
for behav in selected_behaviors:
if [x for x in distinct_behav_modif if x[0] == behav] == []:
distinct_behav_modif.append([behav, ""])
behaviors = init_behav_modif(pj[ETHOGRAM], selected_subjects,
distinct_behav_modif, include_modifiers,
parameters)
param_header = ["", "Total length (s)"]
subj_header, behav_header, modif_header = [""] * len(param_header), [
""
] * len(param_header), [""] * len(param_header)
for subj in selected_subjects:
for behavior_modifiers in distinct_behav_modif:
behavior, modifiers = behavior_modifiers
behavior_modifiers_str = "|".join(
behavior_modifiers) if modifiers else behavior
for param in parameters:
subj_header.append(subj)
behav_header.append(behavior)
modif_header.append(modifiers)
param_header.append(param[1])
'''
if parameters_obs["group observations"]:
cursor.execute("UPDATE aggregated_events SET observation = 'all' " )
#selected_observations = ["all"]
'''
data_report.append(subj_header)
data_report.append(behav_header)
if include_modifiers:
data_report.append(modif_header)
data_report.append(param_header)
# select time interval
for obs_id in selected_observations:
ok, msg, db_connector = db_functions.load_aggregated_events_in_db(
pj, selected_subjects, [obs_id], selected_behaviors)
if not ok:
return False, msg, None
db_connector.create_aggregate("stdev", 1, StdevFunc)
cursor = db_connector.cursor()
# if modifiers not to be included set modifiers to ""
if not include_modifiers:
cursor.execute("UPDATE aggregated_events SET modifiers = ''")
# time
obs_length = project_functions.observation_total_length(
pj[OBSERVATIONS][obs_id])
if obs_length == -1:
obs_length = 0
if interval == TIME_FULL_OBS:
min_time = float(0)
max_time = float(obs_length)
if interval == TIME_EVENTS:
try:
min_time = float(pj[OBSERVATIONS][obs_id][EVENTS][0][0])
except Exception:
min_time = float(0)
try:
max_time = float(pj[OBSERVATIONS][obs_id][EVENTS][-1][0])
except Exception:
max_time = float(obs_length)
if interval == TIME_ARBITRARY_INTERVAL:
min_time = float(start_time)
max_time = float(end_time)
# adapt start and stop to the selected time interval
cursor.execute(
"UPDATE aggregated_events SET start = ? WHERE observation = ? AND start < ? AND stop BETWEEN ? AND ?",
(
min_time,
obs_id,
min_time,
min_time,
max_time,
))
cursor.execute(
"UPDATE aggregated_events SET stop = ? WHERE observation = ? AND stop > ? AND start BETWEEN ? AND ?",
(
max_time,
obs_id,
max_time,
min_time,
max_time,
))
cursor.execute(
"UPDATE aggregated_events SET start = ?, stop = ? WHERE observation = ? AND start < ? AND stop > ?",
(
min_time,
max_time,
obs_id,
min_time,
max_time,
))
cursor.execute(
"DELETE FROM aggregated_events WHERE observation = ? AND (start < ? AND stop < ?) OR (start > ? AND stop > ?)",
(
obs_id,
min_time,
min_time,
max_time,
max_time,
))
for subject in selected_subjects:
# check if behaviors are to exclude from total time
time_to_subtract = 0
if EXCLUDED_BEHAVIORS in parameters_obs:
for excluded_behav in parameters_obs[EXCLUDED_BEHAVIORS]:
cursor.execute((
"SELECT SUM(stop-start) "
"FROM aggregated_events "
"WHERE observation = ? AND subject = ? AND behavior = ? "
), (
obs_id,
subject,
excluded_behav,
))
for row in cursor.fetchall():
if row[0] is not None:
time_to_subtract += row[0]
for behavior_modifiers in distinct_behav_modif:
behavior, modifiers = behavior_modifiers
behavior_modifiers_str = "|".join(
behavior_modifiers) if modifiers else behavior
cursor.execute((
"SELECT SUM(stop-start), COUNT(*), AVG(stop-start), stdev(stop-start) "
"FROM aggregated_events "
"WHERE observation = ? AND subject = ? AND behavior = ? AND modifiers = ? "
), (
obs_id,
subject,
behavior,
modifiers,
))
for row in cursor.fetchall():
behaviors[subject][behavior_modifiers_str][
"duration"] = (0 if row[0] is None else
f"{row[0]:.3f}")
behaviors[subject][behavior_modifiers_str][
"number"] = 0 if row[1] is None else row[1]
behaviors[subject][behavior_modifiers_str][
"duration mean"] = (0 if row[2] is None else
f"{row[2]:.3f}")
behaviors[subject][behavior_modifiers_str][
"duration stdev"] = (0 if row[3] is None else
f"{row[3]:.3f}")
if behavior not in parameters_obs[EXCLUDED_BEHAVIORS]:
try:
behaviors[subject][behavior_modifiers_str][
"proportion of time"] = (
0 if row[0] is None else
f"{row[0] / ((max_time - min_time) - time_to_subtract):.3f}"
)
except ZeroDivisionError:
behaviors[subject][behavior_modifiers_str][
"proportion of time"] = "-"
else:
# behavior subtracted
behaviors[subject][behavior_modifiers_str][
"proportion of time"] = (
0 if row[0] is None else
f"{row[0] / (max_time - min_time):.3f}")
columns = [obs_id, f"{max_time - min_time:0.3f}"]
for subj in selected_subjects:
for behavior_modifiers in distinct_behav_modif:
behavior, modifiers = behavior_modifiers
behavior_modifiers_str = "|".join(
behavior_modifiers) if modifiers else behavior
for param in parameters:
columns.append(
behaviors[subj][behavior_modifiers_str][param[0]])
data_report.append(columns)
except Exception:
error_type, error_file_name, error_lineno = utilities.error_info(
sys.exc_info())
logging.critical(
f"Error in edit_event function: {error_type} {error_file_name} {error_lineno}"
)
msg = f"Error type: {error_type}\nError file name: {error_file_name}\nError line number: {error_lineno}"
logging.critical(msg)
return (False, msg, tablib.Dataset())
return True, msg, data_report
def take_action(self, parsed_args):
self.log.debug('take_action({a})'.format(a=parsed_args))
args = {}
args_id = {}
args_followers = {}
if parsed_args.limit:
args['limit'] = parsed_args.limit
if parsed_args.status:
args['status'] = parsed_args.status
if parsed_args.kind:
args['kind'] = parsed_args.kind
if parsed_args.priority:
args['priority'] = parsed_args.priority
if parsed_args.reported_by:
args['reported_by'] = parsed_args.reported_by
if parsed_args.is_spam:
args['is_spam'] = parsed_args.is_spam
if parsed_args.search:
args['search'] = parsed_args.search
if parsed_args.id:
args_id['id'] = parsed_args.id
if parsed_args.followers:
args_followers['followers'] = parsed_args.followers
issuelist_url = {}
issuedetail_url = {}
issuefilter_url = {}
issuefollowers_url = {}
if all([not(args),
not(args_id),
not(args_followers)]):
url = ("https://bitbucket.org/api/1.0/"
"repositories/{a.account}/{a.reponame}/"
"issues/?").format(a=parsed_args)
issuelist_url['url'] = url
elif args == {} and args_followers == {} and args_id != {}:
url = ("https://bitbucket.org/api/1.0/"
"repositories/{a.account}/{a.reponame}/"
"issues/{a.id}").format(a=parsed_args)
issuedetail_url['url'] = url
elif args_id == {} and args_followers == {} and args != {}:
primaryurl = ("https://bitbucket.org/api/1.0/"
"repositories/{a.account}/{a.reponame}/"
"issues/?").format(a=parsed_args)
params = urllib.urlencode(args)
url = primaryurl + params
issuefilter_url['url'] = url
elif args == {} and args_id != {} and args_followers != {}:
url = ("https://bitbucket.org/api/1.0/"
"repositories/{a.account}/{a.reponame}/"
"issues/{a.id}/"
"followers").format(a=parsed_args)
issuefollowers_url['url'] = url
else:
self.app.stdout.write('\nInvalid argument supplied.\n')
sys.exit(1)
user, passwd = read_creds()
r = requests.get(url, auth=(user, passwd))
try:
data = json.loads(r.text)
except:
print("""
Error: '404' No Issues Found ' or ' Invalid argument supplied.
""")
sys.exit(1)
if all([issuelist_url,
not(issuedetail_url),
not(issuefilter_url),
not(issuefollowers_url)]):
if parsed_args.export:
csvdata = tablib.Dataset()
csvdata.headers = [
"ID",
"Status",
"Title",
"Kind",
"Priority",
"Version",
"Component",
"Milestone",
"Reported By",
"Created On",
"Last Updated",
"Responsible",
"Comment Count",
"is_spam",
"Followers Count"]
with open('issues.xls', 'wb') as f:
for i in data['issues']:
row = []
if 'local_id' in i:
row.append(i['local_id'])
else:
row.append('None')
if 'status' in i:
row.append(i['status'])
else:
row.append('None')
if 'title' in i:
row.append(i['title'])
else:
row.append('None')
if 'metadata' in i:
row.append(i['metadata']['kind'])
else:
row.append('None')
if 'priority' in i:
row.append(i['priority'])
else:
row.append('None')
if 'metadata' in i:
row.append(i['metadata']['version'])
else:
row.append('None')
if 'metadata' in i:
row.append(i['metadata']['component'])
else:
row.append('None')
if 'metadata' in i:
row.append(i['metadata']['milestone'])
else:
row.append('None')
if 'reported_by' in i:
row.append(i['reported_by']['username'])
else:
row.append('None')
if 'utc_created_on' in i:
row.append(i['utc_created_on'])
else:
row.append('None')
if 'utc_last_updated' in i:
row.append(i['utc_last_updated'])
else:
row.append('None')
if 'responsible' in i:
row.append(i['responsible']['username'])
else:
row.append('None')
if 'comment_count' in i:
row.append(i['comment_count'])
else:
row.append('None')
if 'is_spam' in i:
row.append(i['is_spam'])
else:
row.append('None')
if 'follower_count' in i:
row.append(i['follower_count'])
else:
row.append('None')
csvdata.append(row)
f.write(csvdata.csv)
f.close()
print("\n CSV File created.\n")
sys.exit(0)
else:
print("\nTotal Issues: {d[count]}\n".format(d=data))
loopmsg = """Issue_ID: {i[local_id]}
Issue_Status: {i[status]}
Issue_Title: {i[title]}
======================================================================="""
for i in data['issues']:
print(loopmsg.format(i=i))
sys.exit(0)
elif all([issuedetail_url,
not(issuelist_url),
not(issuefilter_url),
not(issuefollowers_url)]):
newdata = {}
newdata['issue id'] = data['local_id']
newdata['status'] = data['status']
newdata['kind'] = data['metadata']['kind']
newdata['priority'] = data['priority']
newdata['version'] = data['metadata']['version']
newdata['component'] = data['metadata']['component']
newdata['milestone'] = data['metadata']['milestone']
newdata['reported by'] = data['reported_by']['username']
newdata['utc_created_on'] = data['utc_created_on']
newdata['utc_last_updated'] = data['utc_last_updated']
newdata['responsible'] = data['responsible']['username']
newdata['created on'] = data['created_on']
newdata['comment_count'] = data['comment_count']
newdata['is_spam'] = data['is_spam']
newdata['follower_count'] = data['follower_count']
columns = newdata.keys()
columndata = newdata.values()
print("\nTitle: %s\n" % (data['title']))
print("Content: %s\n" % (data['content']))
return (columns, columndata)
elif all([issuefilter_url,
not(issuelist_url),
not(issuedetail_url),
not(issuefollowers_url)]):
if parsed_args.export:
csvdata = tablib.Dataset()
csvdata.headers = [
"ID",
"Status",
"Title",
"Kind",
"Priority",
"Version",
"Component",
"Milestone",
"Reported By",
"Created On",
"Last Updated",
"Responsible",
"Title",
"Content",
"Comment Count",
"is_spam",
"Followers Count"]
with open('issues.xls', 'wb') as f:
for i in data['issues']:
row = []
if 'local_id' in i:
row.append(i['local_id'])
else:
row.append('None')
if 'status' in i:
row.append(i['status'])
else:
row.append('None')
if 'title' in i:
row.append(i['title'])
else:
row.append('None')
if 'metadata' in i:
row.append(i['metadata']['kind'])
else:
row.append('None')
if 'priority' in i:
row.append(i['priority'])
else:
row.append('None')
if 'metadata' in i:
row.append(i['metadata']['version'])
else:
row.append('None')
if 'metadata' in i:
row.append(i['metadata']['component'])
else:
row.append('None')
if 'metadata' in i:
row.append(i['metadata']['milestone'])
else:
row.append('None')
if 'reported_by' in i:
row.append(i['reported_by']['username'])
else:
row.append('None')
if 'utc_created_on' in i:
row.append(i['utc_created_on'])
else:
row.append('None')
if 'utc_last_updated' in i:
row.append(i['utc_last_updated'])
else:
row.append('None')
if 'responsible' in i:
row.append(i['responsible']['username'])
else:
row.append('None')
if 'title' in i:
row.append(i['title'])
else:
row.append('None')
if 'content' in i:
row.append(i['content'])
else:
row.append('None')
if 'comment_count' in i:
row.append(i['comment_count'])
else:
row.append('None')
if 'is_spam' in i:
row.append(i['is_spam'])
else:
row.append('None')
if 'follower_count' in i:
row.append(i['follower_count'])
else:
row.append('None')
csvdata.append(row)
f.write(csvdata.csv)
f.close()
print("\n CSV File created.\n")
sys.exit(0)
else:
print("\nTotal Issues: {d[count]}\n".format(d=data))
loopmsg = """Issue_ID: {i[local_id]}
Issue_Status: {i[status]}
Issue_Title: {i[title]}
======================================================================="""
for i in data['issues']:
print(loopmsg.format(i=i))
sys.exit(0)
elif all([issuefollowers_url,
not(issuelist_url),
not(issuedetail_url),
not(issuefilter_url)]):
print("\nFollowers Count: %s\n" % (data['count']))
for i in data['followers']:
print("Followers Name: %s" % (i['username']))
print("\n")
sys.exit(0)
else:
print("Invalid Request no data received.")
sys.exit(1)
def create_behavior_binary_table(pj: dict,
selected_observations: list,
parameters_obs: dict,
time_interval: float) -> dict:
"""
create behavior binary table
Args:
pj (dict): project dictionary
selected_observations (list): list of selected observations
parameters_obs (dict): dcit of parameters
time_interval (float): time interval (in seconds)
Returns:
dict: dictionary of tablib dataset
"""
results_df = {}
state_behavior_codes = [x for x in utilities.state_behavior_codes(pj[ETHOGRAM]) if x in parameters_obs[SELECTED_BEHAVIORS]]
point_behavior_codes = [x for x in utilities.point_behavior_codes(pj[ETHOGRAM]) if x in parameters_obs[SELECTED_BEHAVIORS]]
if not state_behavior_codes and not point_behavior_codes:
return {"error": True, "msg": "No state events selected"}
for obs_id in selected_observations:
if obs_id not in results_df:
results_df[obs_id] = {}
for subject in parameters_obs[SELECTED_SUBJECTS]:
# extract tuple (behavior, modifier)
behav_modif_list = [(idx[2], idx[3])
for idx in pj[OBSERVATIONS][obs_id][EVENTS] if idx[1] == (subject if subject != NO_FOCAL_SUBJECT else "")
and idx[2] in parameters_obs[SELECTED_BEHAVIORS]]
# extract observed subjects NOT USED at the moment
observed_subjects = [event[EVENT_SUBJECT_FIELD_IDX] for event in pj[OBSERVATIONS][obs_id][EVENTS]]
# add selected behavior if not found in (behavior, modifier)
if not parameters_obs[EXCLUDE_BEHAVIORS]:
#for behav in state_behavior_codes:
for behav in parameters_obs[SELECTED_BEHAVIORS]:
if behav not in [x[0] for x in behav_modif_list]:
behav_modif_list.append((behav, ""))
behav_modif_set = set(behav_modif_list)
observed_behav = [(x[0], x[1]) for x in sorted(behav_modif_set)]
if parameters_obs[INCLUDE_MODIFIERS]:
results_df[obs_id][subject] = tablib.Dataset(headers=["time"] + [f"{x[0]}" + f" ({x[1]})" * (x[1] != "")
for x in sorted(behav_modif_set)])
else:
results_df[obs_id][subject] = tablib.Dataset(headers=["time"] + [x[0] for x in sorted(behav_modif_set)])
if subject == NO_FOCAL_SUBJECT:
sel_subject_dict = {"": {SUBJECT_NAME: ""}}
else:
sel_subject_dict = dict([(idx, pj[SUBJECTS][idx]) for idx in pj[SUBJECTS] if pj[SUBJECTS][idx][SUBJECT_NAME] == subject])
row_idx = 0
t = parameters_obs[START_TIME]
while t < parameters_obs[END_TIME]:
# state events
current_states = utilities.get_current_states_modifiers_by_subject_2(state_behavior_codes,
pj[OBSERVATIONS][obs_id][EVENTS],
sel_subject_dict,
t
)
# point events
current_point = utilities.get_current_points_by_subject(point_behavior_codes,
pj[OBSERVATIONS][obs_id][EVENTS],
sel_subject_dict,
t,
time_interval
)
cols = [float(t)] # time
for behav in observed_behav:
if behav[0] in state_behavior_codes:
cols.append(int(behav in current_states[list(current_states.keys())[0]]))
if behav[0] in point_behavior_codes:
cols.append(current_point[list(current_point.keys())[0]].count(behav))
results_df[obs_id][subject].append(cols)
t += time_interval
row_idx += 1
return results_df
def test_latex_export_empty_dataset(self):
self.assertTrue(tablib.Dataset().latex is not None)
def handle(self, *args, **options):
src = options["src"]
from_index = options.pop("from_index")
to_index = options.pop("to_index")
site_id = options.pop("site_id", None)
permament = options.pop("permanent")
dry_run = options.pop("dry_run")
format_ = options.pop("format", None)
ask = options.pop("ask")
errors = []
successes = 0
skipped = 0
total = 0
site = None
if site_id:
site = Site.objects.get(id=site_id)
if not os.path.exists(src):
raise Exception("Missing file '{0}'".format(src))
if not os.path.getsize(src) > 0:
raise Exception("File '{0}' is empty".format(src))
_, extension = os.path.splitext(src)
if extension in [".xls", ".xlsx"]:
mode = "rb"
else:
mode = "r"
if not format_:
format_ = extension
with open(src, mode) as fh:
imported_data = tablib.Dataset().load(fh.read(), format=format_)
sample_data = tablib.Dataset(
*imported_data[:min(len(imported_data), 4)],
headers=imported_data.headers)
try:
self.stdout.write("Sample data:")
self.stdout.write(str(sample_data))
except:
self.stdout.write("Warning: Cannot display sample data")
self.stdout.write("--------------")
if site:
self.stdout.write("Using site: {}".format(site.hostname))
self.stdout.write("Importing redirects:")
for row in imported_data:
total += 1
from_link = row[from_index]
to_link = row[to_index]
data = {
"old_path": from_link,
"redirect_link": to_link,
"is_permanent": permament,
}
if site:
data["site"] = site.pk
form = RedirectForm(data)
if not form.is_valid():
error = form.errors.as_text().replace("\n", "")
self.stdout.write(
"{}. Error: {} -> {} (Reason: {})".format(
total,
from_link,
to_link,
error,
))
errors.append(error)
continue
if ask:
answer = input("{}. Found {} -> {} Create? Y/n: ".format(
total,
from_link,
to_link,
))
if answer != "Y":
skipped += 1
continue
else:
self.stdout.write("{}. {} -> {}".format(
total,
from_link,
to_link,
))
if dry_run:
successes += 1
continue
form.save()
successes += 1
self.stdout.write("\n")
self.stdout.write("Found: {}".format(total))
self.stdout.write("Created: {}".format(successes))
self.stdout.write("Skipped : {}".format(skipped))
self.stdout.write("Errors: {}".format(len(errors)))
def test_latex_export_no_headers(self):
d = tablib.Dataset()
d.append(('one', 'two', 'three'))
self.assertTrue('one' in d.latex)
def format_to_df(data, columns=None):
"""将数据转换为Dataset类型"""
return tl.Dataset(*data, headers=columns)
def test_latex_export_none_values(self):
headers = ['foo', None, 'bar']
d = tablib.Dataset(['foo', None, 'bar'], headers=headers)
output = d.latex
self.assertTrue('foo' in output)
self.assertFalse('None' in output)
def test_error_no_amount(self):
dataset = tablib.Dataset(["15/6/2016", "Example payment"],
headers=["date", "description"])
result = self.makeResource().import_data(dataset)
self.assertEqual(len(result.row_errors()), 1)
self.assertIn("No amount", str(result.row_errors()[0][1][0].error))
def test_str_no_columns(self):
d = tablib.Dataset(['a', 1], ['b', 2], ['c', 3])
output = '%s' % d
self.assertEqual(output.splitlines(), ['a|1', 'b|2', 'c|3'])
def export_events(parameters, obsId, observation, ethogram, file_name,
output_format):
"""
export events
Args:
parameters (dict): subjects, behaviors
obsId (str): observation id
observation (dict): observation
ethogram (dict): ethogram of project
file_name (str): file name for exporting events
output_format (str): output for exporting events
Returns:
bool: result: True if OK else False
str: error message
"""
total_length = "{0:.3f}".format(
project_functions.observation_total_length(observation))
eventsWithStatus = project_functions.events_start_stop(
ethogram, observation[EVENTS])
# check max number of modifiers
max_modifiers = 0
for event in eventsWithStatus:
for c in pj_events_fields:
if c == "modifier" and event[pj_obs_fields[c]]:
max_modifiers = max(max_modifiers,
len(event[pj_obs_fields[c]].split("|")))
# media file number
mediaNb = 0
if observation["type"] in [MEDIA]:
for idx in observation[FILE]:
for media in observation[FILE][idx]:
mediaNb += 1
rows = []
# observation id
rows.append(["Observation id", obsId])
rows.append([""])
# media file name
if observation["type"] in [MEDIA]:
rows.append(["Media file(s)"])
else:
rows.append(["Live observation"])
rows.append([""])
if observation[TYPE] in [MEDIA]:
for idx in observation[FILE]:
for media in observation[FILE][idx]:
rows.append(["Player #{0}".format(idx), media])
rows.append([""])
# date
if "date" in observation:
rows.append(
["Observation date", observation["date"].replace("T", " ")])
rows.append([""])
# description
if "description" in observation:
rows.append(
["Description",
utilities.eol2space(observation["description"])])
rows.append([""])
# time offset
if "time offset" in observation:
rows.append(["Time offset (s)", observation["time offset"]])
rows.append([""])
# independent variables
if INDEPENDENT_VARIABLES in observation:
rows.extend([["independent variables"], ["variable", "value"]])
for variable in observation[INDEPENDENT_VARIABLES]:
rows.append(
[variable, observation[INDEPENDENT_VARIABLES][variable]])
rows.append([""])
# write table header
col = 0
header = ["Time"]
header.extend(["Media file path", "Total length", "FPS"])
header.extend(["Subject", "Behavior"])
for x in range(1, max_modifiers + 1):
header.append("Modifier {}".format(x))
header.extend(["Comment", "Status"])
rows.append(header)
duration1 = [] # in seconds
if observation["type"] in [MEDIA]:
try:
for mediaFile in observation[FILE][PLAYER1]:
duration1.append(
observation["media_info"]["length"][mediaFile])
except:
pass
for event in eventsWithStatus:
if (((event[SUBJECT_EVENT_FIELD] in parameters["selected subjects"]) or
(event[SUBJECT_EVENT_FIELD] == ""
and NO_FOCAL_SUBJECT in parameters["selected subjects"])) and
(event[BEHAVIOR_EVENT_FIELD] in parameters["selected behaviors"])):
fields = []
fields.append(
utilities.intfloatstr(str(event[EVENT_TIME_FIELD_IDX])))
if observation["type"] in [MEDIA]:
time_ = event[EVENT_TIME_FIELD_IDX] - observation[TIME_OFFSET]
if time_ < 0:
time_ = 0
mediaFileIdx = [
idx1 for idx1, x in enumerate(duration1)
if time_ >= sum(duration1[0:idx1])
][-1]
fields.append(
utilities.intfloatstr(
str(observation[FILE][PLAYER1][mediaFileIdx])))
fields.append(total_length)
fields.append(observation["media_info"]["fps"][
observation[FILE][PLAYER1][mediaFileIdx]]) # fps
if observation["type"] in [LIVE]:
fields.append(LIVE) # media
fields.append(total_length) # total length
fields.append("NA") # FPS
fields.append(event[EVENT_SUBJECT_FIELD_IDX])
fields.append(event[EVENT_BEHAVIOR_FIELD_IDX])
modifiers = event[EVENT_MODIFIER_FIELD_IDX].split("|")
while len(modifiers) < max_modifiers:
modifiers.append("")
for m in modifiers:
fields.append(m)
fields.append(event[EVENT_COMMENT_FIELD_IDX].replace(
os.linesep, " "))
# status
fields.append(event[-1])
rows.append(fields)
maxLen = max([len(r) for r in rows])
data = tablib.Dataset()
data.title = obsId
# check if worksheet name will be > 31 char
if output_format in ["xls", "xlsx"]:
for forbidden_char in r"\/*[]:?":
data.title = data.title.replace(forbidden_char, " ")
if output_format in ["xls"]:
if len(data.title) > 31:
data.title = data.title[0:31]
for row in rows:
data.append(utilities.complete(row, maxLen))
r, msg = dataset_write(data, file_name, output_format)
return r, msg
def get_files(
ctx,
workflow,
_format,
filters,
output_format,
filename,
access_token,
page,
size,
human_readable_or_raw,
): # noqa: D301
"""List workspace files.
The ``ls`` command lists workspace files of a workflow specified by the
environment variable REANA_WORKON or provided as a command-line flag
``--workflow`` or ``-w``. The SOURCE argument is optional and specifies a
pattern matching files and directories.
Examples: \n
\t $ reana-client ls --workflow myanalysis.42 \n
\t $ reana-client ls --workflow myanalysis.42 --human-readable \n
\t $ reana-client ls --workflow myanalysis.42 'data/*root*' \n
\t $ reana-client ls --workflow myanalysis.42 --filter name=hello
""" # noqa: W605
import tablib
from reana_client.api.client import current_rs_api_client, list_files
logging.debug("command: {}".format(ctx.command_path.replace(" ", ".")))
for p in ctx.params:
logging.debug("{param}: {value}".format(param=p, value=ctx.params[p]))
search_filter = None
headers = ["name", "size", "last-modified"]
if filters:
_, search_filter = parse_filter_parameters(filters, headers)
if _format:
parsed_format_filters = parse_format_parameters(_format)
if workflow:
logging.info('Workflow "{}" selected'.format(workflow))
try:
response = list_files(workflow, access_token, filename, page, size,
search_filter)
data = []
file_path = get_path_from_operation_id(
current_rs_api_client.swagger_spec.spec_dict["paths"],
"download_file")
urls = []
for file_ in response:
if not file_["name"].startswith(FILES_BLACKLIST):
data.append(
list(
map(
str,
[
file_["name"],
file_["size"][human_readable_or_raw],
file_["last-modified"],
],
)))
urls.append(ctx.obj.reana_server_url + file_path.format(
workflow_id_or_name=workflow, file_name=file_["name"]))
tablib_data = tablib.Dataset()
tablib_data.headers = headers
for row in data:
tablib_data.append(row)
if output_format == URL:
display_message("\n".join(urls))
elif _format:
tablib_data, filtered_headers = format_data(
parsed_format_filters, headers, tablib_data)
if output_format == JSON:
display_message(json.dumps(tablib_data))
else:
tablib_data = [list(item.values()) for item in tablib_data]
click_table_printer(filtered_headers, filtered_headers,
tablib_data)
else:
if output_format == JSON:
display_message(tablib_data.export(output_format))
else:
click_table_printer(headers, _format, data)
except Exception as e:
logging.debug(traceback.format_exc())
logging.debug(str(e))
display_message(
"Something went wrong while retrieving file list"
" for workflow {0}:\n{1}".format(workflow, str(e)),
msg_type="error",
)
def execute(self, avatar=None):
if not avatar:
avatar = Avatar.get(self.user, self.block_id - 1)
dirname = os.path.dirname(__file__)
filename = os.path.join(dirname, 'data/monsters.csv')
monsters = tablib.Dataset().load(open(filename).read()).dict
randoms = self.get_randoms()
monster = monsters[randoms.pop() % len(monsters)]
battle_status = []
for key in ('hp', 'piercing', 'armor'):
monster[key] = int(monster[key])
def get_item(ticker_name):
items = get_related_items(Item)
for item in items:
if item.ticker_name == ticker_name:
return item
return None
weapon = armor = food = None
if 'weapon' in self.details:
weapon = get_item(self.details['weapon'])
if 'armor' in self.details:
armor = get_item(self.details['armor'])
if 'food' in self.details:
food = get_item(self.details['food'])
while True:
try:
if (avatar.hp <= avatar.max_hp * 0.5 and food
and food.ticker_name in avatar.items
and avatar.items[food.ticker_name] > 0):
avatar, status = food().execute(avatar)
battle_status.append(status)
avatar.items[food.ticker_name] -= 1
food = None
if (avatar.hp <= avatar.max_hp * 0.2 and 'BNDG' in avatar.items
and avatar.items['BNDG'] > 0):
rolled = self.roll(randoms, '2d6')
if rolled >= 7:
avatar.hp += 4
avatar.items['BNDG'] -= 1
battle_status.append({
'type': 'item_use',
'item': 'BNDG',
'status_change': 'HP +4'
})
else:
avatar.items['BNDG'] -= 1
battle_status.append({
'type': 'item_use_fail',
'item': 'BNDG',
'status_change': ''
})
rolled = (self.roll(randoms, '2d6') +
avatar.modifier('strength'))
if rolled >= 7:
damage = max(
self.roll(randoms, avatar.damage) - monster['armor'],
0)
if weapon:
damage += weapon.attack_modifier(avatar, monster)
battle_status.append({
'type': 'attack_monster',
'damage': damage,
'monster': monster.copy(),
})
monster['hp'] = monster['hp'] - damage
elif rolled in (2, 3, 4, 5, 6, 7, 8, 9):
monster_damage = self.roll(randoms, monster['damage'])
if armor:
monster_damage -= armor.armor_modifier(avatar, monster)
battle_status.append({
'type': 'attacked_by_monster',
'damage': monster_damage,
'monster': monster.copy(),
})
avatar.hp -= monster_damage
if rolled <= 6:
battle_status.append({
'type': 'get_xp',
})
avatar.xp += 1
if monster['hp'] <= 0:
battle_status.append({
'type': 'kill_monster',
'monster': monster.copy(),
})
reward_code = self.roll(randoms, '1d10')
if len(monster[f'reward{reward_code}']):
avatar.get_item(monster[f'reward{reward_code}'])
battle_status.append({
'type':
'get_item',
'item':
monster[f'reward{reward_code}'],
})
return (avatar,
dict(
type='hack_and_slash',
result='win',
battle_status=battle_status,
))
if avatar.hp <= 0:
battle_status.append({
'type': 'killed_by_monster',
'monster': monster.copy(),
})
return (avatar,
dict(
type='hack_and_slash',
result='lose',
battle_status=battle_status,
))
except OutOfRandomError:
battle_status.append({
'type': 'run',
'monster': monster.copy(),
})
return (avatar,
dict(
type='hack_and_slash',
result='finish',
battle_status=battle_status,
))
from flask import Flask, render_template
import tablib
import os
app = Flask(__name__)
dataset = tablib.Dataset()
with open('result.csv') as f:
dataset.csv = f.read()
@app.route("/")
def index():
return dataset.html
if __name__ == "__main__":
app.run()
def create_dataset(self, in_stream, **kwargs):
data = tablib.Dataset()
self.get_format().import_set(data, in_stream, **kwargs)
return data
def get_all(self,
output_format='xlsx',
type=None,
status=None,
start_time=None,
end_time=None,
limit=None,
offset=None,
region_id=None,
project_id=None,
user_id=None,
owed=None):
"""Get queried orders
If start_time and end_time is not None, will get orders that have bills
during start_time and end_time, or return all orders directly.
"""
limit_user_id = acl.get_limited_to_user(request.headers,
'export_orders')
if limit and limit < 0:
raise exception.InvalidParameterValue(err="Invalid limit")
if offset and offset < 0:
raise exception.InvalidParameterValue(err="Invalid offset")
if limit_user_id: # normal user
user_id = None
projects = keystone.get_projects_by_user(limit_user_id)
_project_ids = [project['id'] for project in projects]
if project_id and project_id in _project_ids:
project_ids = [project_id]
else:
project_ids = _project_ids
else: # accountant
if project_id: # look up specified project
project_ids = [project_id]
else: # look up all projects
project_ids = []
if project_ids:
project_ids = list(set(project_ids) - set(cfg.CONF.ignore_tenants))
users = {}
projects = {}
def _get_user(user_id):
user = users.get(user_id)
if user:
return user
contact = kunkka.get_uos_user(user_id)
user_name = contact['name'] if contact else None
users[user_id] = models.User(user_id=user_id, user_name=user_name)
return users[user_id]
def _get_project(project_id):
project = projects.get(project_id)
if project:
return project
try:
project = keystone.get_project(project_id)
project_name = project.name if project else None
projects[project_id] = models.SimpleProject(
project_id=project_id, project_name=project_name)
return projects[project_id]
except Exception as e:
# Note(chengkun): some project was deleted from keystone,
# But the project's order still in the gringotts. so when
# we get the order it will raise 404 project not found error
LOG.error('error to get project: %s' % e)
return None
MAP = [
{
"running": u"运行中",
"stopped": u"暂停中",
"deleted": u"被删除"
},
{
"instance": u"虚拟机",
"image": u"镜像",
"snapshot": u"硬盘快照",
"volume": u"云硬盘",
"share": u"共享文件",
"floatingip": u"公网IP",
"listener": u"负载均衡监听器",
"router": u"路由器",
"alarm": u"监控报警"
},
]
headers = (u"资源ID", u"资源名称", u"资源类型", u"资源状态", u"单价(元/小时)", u"金额(元)",
u"区域", u"用户ID", u"用户名称", u"项目ID", u"项目名称", u"创建时间")
data = []
adata = (
u"过滤条件: 资源类型: %s, 资源状态: %s，用户ID: %s, 项目ID: %s, 区域: %s, 起始时间: %s, 结束时间: %s"
% (type, status, user_id, project_id, region_id, start_time,
end_time), "", "", "", "", "", "", "", "", "", "", "")
data.append(adata)
conn = pecan.request.db_conn
orders_db, total_count = conn.get_orders(request.context,
type=type,
status=status,
start_time=start_time,
end_time=end_time,
owed=owed,
limit=limit,
offset=offset,
with_count=True,
region_id=region_id,
user_id=user_id,
project_ids=project_ids)
for order in orders_db:
price = self._get_order_price(order,
start_time=start_time,
end_time=end_time)
user = _get_user(order.user_id)
project = _get_project(order.project_id)
if project is None:
continue
order.created_at += datetime.timedelta(hours=8)
created_at = \
timeutils.strtime(order.created_at, fmt=OUTPUT_TIME_FORMAT)
adata = (order.resource_id, order.resource_name,
MAP[1][order.type], MAP[0][order.status],
order.unit_price, price, order.region_id, user.user_id,
user.user_name, project.project_id, project.project_name,
created_at)
data.append(adata)
data = tablib.Dataset(*data, headers=headers)
response.content_type = "application/binary; charset=UTF-8"
response.content_disposition = \
"attachment; filename=orders.%s" % output_format
content = getattr(data, output_format)
if output_format == 'csv':
content = content.decode("utf-8").encode("gb2312")
response.write(content)
return response
