def test_functions(self):
get_switch_list()
get_hangupcause_name(self.hangupcause.pk)
get_hangupcause_name(2)
get_hangupcause_id(self.hangupcause.code)
# Template tags
hangupcause_name_with_title(self.hangupcause.pk)
get_country_id_prefix(['44', '442'])
def test_functions(self):
get_switch_list()
get_hangupcause_name(self.hangupcause.pk)
get_hangupcause_name(2)
get_hangupcause_id(self.hangupcause.code)
# Template tags
hangupcause_name_with_title(self.hangupcause.pk)
get_country_id_prefix(['44', '442'])
def test_functions(self):
get_switch_list()
get_hangupcause_name(self.hangupcause.pk)
get_hangupcause_name(2)
get_hangupcause_id(self.hangupcause.code)
# Template tags
hangupcause_name_with_title(self.hangupcause.pk)
value = {'_id': {'val': 1}}
mongo_id(value, 'val')
get_hc_list()
get_country_id(['44', '442'])
def test_functions(self):
get_switch_list()
get_hangupcause_name(self.hangupcause.pk)
get_hangupcause_name(2)
get_hangupcause_id(self.hangupcause.code)
# Template tags
hangupcause_name_with_title(self.hangupcause.pk)
value = {'_id': {'val': 1}}
mongo_id(value, 'val')
get_hc_list()
get_country_id(['44', '442'])
def custom_sql_aggr_top_hangup(user, switch_id, hangup_cause_id, limit, start_date, end_date):
"""
perform query to retrieve and aggregate calls data by country
"""
result = []
total_calls = total_duration = total_billsec = total_buy_cost = total_sell_cost = 0
with connection.cursor() as cursor:
sqlquery = sqlquery_aggr_hangup_cause
sqlquery = sqlquery.replace("#USER_CONDITION#", condition_user(user))
sqlquery = sqlquery.replace("#SWITCH_CONDITION#", condition_switch_id(switch_id))
sqlquery = sqlquery.replace("#HANGUP_CONDITION#", condition_hangup_cause_id(hangup_cause_id))
params = {
'start_date': start_date,
'end_date': end_date,
'limit': limit,
}
cursor.execute(sqlquery, params)
rows = cursor.fetchall()
for row in rows:
result.append({
"hangup_cause_id": row[0],
"duration": row[1],
"billsec": row[2],
"nbcalls": row[3],
"buy_cost": row[4],
"sell_cost": row[5],
"hangup_cause_name": get_hangupcause_name(row[0]),
})
total_calls += row[1]
total_duration += row[2]
total_billsec += row[3]
total_buy_cost += row[4]
total_sell_cost += row[5]
return (result, total_calls, total_duration, total_billsec, total_buy_cost, total_sell_cost)
def test_functions(self):
get_switch_list()
get_hangupcause_name(self.hangupcause.pk)
get_hangupcause_name(2)
get_hangupcause_id(self.hangupcause.code)
# Template tags
hangupcause_name_with_title(self.hangupcause.pk)
value = {'_id': {'val': 1}}
mongo_id(value, 'val')
seen_unseen(value)
seen_unseen('')
seen_unseen_word(value)
seen_unseen_word('')
def cdr_export_to_csv(request):
"""
**Logic Description**:
Retrieve calls records from Postgresql according to search
parameters, then export the result into CSV/XLS/JSON file
"""
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
# get query_var from request.session
start_date = request.session.get('session_start_date')
end_date = request.session.get('session_end_date')
start_date = ceil_strdate(start_date, 'start', True)
end_date = ceil_strdate(end_date, 'end', True)
if request.session.get('session_export_kwargs'):
kwargs = request.session.get('session_export_kwargs')
if start_date:
kwargs['starting_date__gte'] = start_date
if end_date:
kwargs['starting_date__lte'] = end_date
cdrs = CDR.objects.filter(**kwargs)
headers = ('Call-date', 'CLID', 'Destination', 'Duration', 'Bill sec',
'Hangup cause', 'AccountCode', 'Direction')
list_val = []
for cdr in cdrs:
starting_date = str(cdr.starting_date)
list_val.append((
starting_date,
cdr.caller_id_number + '-' + cdr.caller_id_name,
cdr.destination_number,
cdr.duration,
cdr.billsec,
get_hangupcause_name(cdr.hangup_cause_id),
cdr.accountcode,
cdr.direction,
))
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 cdr_export_to_csv(request):
"""
**Logic Description**:
Retrieve calls records from Postgresql according to search
parameters, then export the result into CSV/XLS/JSON file
"""
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
# get query_var from request.session
start_date = request.session.get('session_start_date')
end_date = request.session.get('session_end_date')
start_date = ceil_strdate(start_date, 'start', True)
end_date = ceil_strdate(end_date, 'end', True)
if request.session.get('session_export_kwargs'):
kwargs = request.session.get('session_export_kwargs')
if start_date:
kwargs['starting_date__gte'] = start_date
if end_date:
kwargs['starting_date__lte'] = end_date
cdrs = CDR.objects.filter(**kwargs)
headers = ('Call-date', 'CLID', 'Destination', 'Duration', 'Bill sec', 'Hangup cause',
'AccountCode', 'Direction')
list_val = []
for cdr in cdrs:
starting_date = str(cdr.starting_date)
list_val.append((
starting_date,
cdr.caller_id_number + '-' + cdr.caller_id_name,
cdr.destination_number,
cdr.duration,
cdr.billsec,
get_hangupcause_name(cdr.hangup_cause_id),
cdr.accountcode,
cdr.direction,
))
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 hangupcause_name_with_title(id):
"""Tag is used to get hangupcause name with lowercase"""
try:
val = get_hangupcause_name(id)
t = re.sub("([a-z])'([A-Z])",
lambda m: m.group(0).lower(), val.title())
return re.sub("\d([A-Z])",
lambda m: m.group(0).lower(), t)
except:
return ''
def custom_sql_aggr_top_hangup(user, switch_id, hangup_cause_id, limit,
start_date, end_date):
"""
perform query to retrieve and aggregate calls data by country
"""
result = []
total_calls = total_duration = total_billsec = total_buy_cost = total_sell_cost = 0
with connection.cursor() as cursor:
sqlquery = sqlquery_aggr_hangup_cause
sqlquery = sqlquery.replace("#USER_CONDITION#", condition_user(user))
sqlquery = sqlquery.replace("#SWITCH_CONDITION#",
condition_switch_id(switch_id))
sqlquery = sqlquery.replace("#HANGUP_CONDITION#",
condition_hangup_cause_id(hangup_cause_id))
params = {
'start_date': start_date,
'end_date': end_date,
'limit': limit,
}
cursor.execute(sqlquery, params)
rows = cursor.fetchall()
for row in rows:
result.append({
"hangup_cause_id": row[0],
"duration": row[1],
"billsec": row[2],
"nbcalls": row[3],
"buy_cost": row[4],
"sell_cost": row[5],
"hangup_cause_name": get_hangupcause_name(row[0]),
})
total_calls += row[1]
total_duration += row[2]
total_billsec += row[3]
total_buy_cost += row[4]
total_sell_cost += row[5]
return (result, total_calls, total_duration, total_billsec, total_buy_cost,
total_sell_cost)
def cdr_dashboard(request):
"""CDR dashboard on the last 24 hours
**Attributes**:
* ``template`` - cdr/dashboard.html
* ``form`` - SwitchForm
**Logic Description**:
Display calls aggregated information for the last 24hours, several report will be
created and displayed such as hourly call report and hangup cause/country analytics.
"""
logging.debug('CDR dashboard view start')
form = SwitchForm(request.POST or None)
if form.is_valid():
logging.debug('CDR dashboard view with search option')
switch_id = int(getvar(request, 'switch_id'))
else:
switch_id = 0
# Get list of calls/duration for each of the last 24 hours
(calls_hour_aggr, total_calls, total_duration, total_billsec, total_buy_cost, total_sell_cost) = custom_sql_matv_voip_cdr_aggr_last24hours(request.user, switch_id)
# Build chart data for last 24h calls
(xdata, ydata, ydata2, ydata3, ydata4, ydata5) = ([], [], [], [], [], [])
for i in calls_hour_aggr:
start_time = (time.mktime(calls_hour_aggr[i]['calltime'].timetuple()) * 1000)
xdata.append(start_time)
ydata.append(int(calls_hour_aggr[i]['nbcalls']))
ydata2.append(int(calls_hour_aggr[i]['duration']/60))
ydata3.append(int(calls_hour_aggr[i]['billsec']/60))
ydata4.append(int(calls_hour_aggr[i]['buy_cost']))
ydata5.append(int(calls_hour_aggr[i]['sell_cost']))
tooltip_date = "%d %b %y %H:%M %p"
extra_serie1 = {"tooltip": {"y_start": "", "y_end": " calls"}, "date_format": tooltip_date}
extra_serie2 = {"tooltip": {"y_start": "", "y_end": " min"}, "date_format": tooltip_date}
extra_serie3 = {"tooltip": {"y_start": "", "y_end": " min"}, "date_format": tooltip_date}
extra_serie4 = {"tooltip": {"y_start": "", "y_end": ""}, "date_format": tooltip_date}
extra_serie5 = {"tooltip": {"y_start": "", "y_end": ""}, "date_format": tooltip_date}
kwargs1 = {}
kwargs1['bar'] = True
final_chartdata = {
'x': xdata,
'name1': 'Calls', 'y1': ydata, 'extra1': extra_serie1, 'kwargs1': kwargs1,
'name2': 'Duration', 'y2': ydata2, 'extra2': extra_serie2,
'name3': 'Billsec', 'y3': ydata3, 'extra3': extra_serie3,
'name4': 'Buy cost', 'y4': ydata4, 'extra4': extra_serie4,
'name5': 'Sell cost', 'y5': ydata5, 'extra5': extra_serie5,
}
final_charttype = "linePlusBarChart"
# Get top 5 of country calls for last 24 hours
country_data = custom_sql_aggr_top_country_last24hours(request.user, switch_id, limit=5)
# Build pie chart data for last 24h calls per country
(xdata, ydata) = ([], [])
for country in country_data:
xdata.append(get_country_name(country["country_id"]))
ydata.append(percentage(country["nbcalls"], total_calls))
color_list = ['#FFC36C', '#FFFF9D', '#BEEB9F', '#79BD8F', '#FFB391']
extra_serie = {"tooltip": {"y_start": "", "y_end": " %"}, "color_list": color_list}
country_analytic_chartdata = {'x': xdata, 'y1': ydata, 'extra1': extra_serie}
country_analytic_charttype = "pieChart"
country_extra = {
'x_is_date': False,
'x_axis_format': '',
'tag_script_js': True,
'jquery_on_ready': True,
}
# Get top 10 of hangup cause calls for last 24 hours
hangup_cause_data = custom_sql_aggr_top_hangup_last24hours(request.user, switch_id)
# hangup analytic pie chart data
(xdata, ydata) = ([], [])
for hangup_cause in hangup_cause_data:
xdata.append(str(get_hangupcause_name(hangup_cause["hangup_cause_id"])))
ydata.append(str(percentage(hangup_cause["nbcalls"], total_calls)))
color_list = ['#2A343F', '#7E8282', '#EA9664', '#30998F', '#449935']
extra_serie = {"tooltip": {"y_start": "", "y_end": " %"}, "color_list": color_list}
hangup_analytic_chartdata = {'x': xdata, 'y1': ydata, 'extra1': extra_serie}
hangup_analytic_charttype = "pieChart"
hangup_extra = country_extra
logging.debug("Result calls_hour_aggr %d" % len(calls_hour_aggr))
logging.debug("Result hangup_cause_data %d" % len(hangup_cause_data))
logging.debug("Result country_data %d" % len(country_data))
# Calculate the Average Time of Call
metric_aggr = calculate_act_acd(total_calls, total_duration)
final_extra = {
'x_is_date': True,
'x_axis_format': '%H:%M',
# 'x_axis_format': '%d %b %Y',
'tag_script_js': True,
'jquery_on_ready': True,
'focus_enable': True,
}
logging.debug('CDR dashboard view end')
variables = {
'total_calls': total_calls,
'total_duration': int_convert_to_minute(total_duration),
'total_buy_cost': total_buy_cost,
'total_sell_cost': total_sell_cost,
'metric_aggr': metric_aggr,
'country_data': country_data,
'hangup_analytic': hangup_cause_data,
'form': form,
'final_chartdata': final_chartdata,
'final_charttype': final_charttype,
'final_chartcontainer': 'final_container',
'final_extra': final_extra,
'hangup_analytic_charttype': hangup_analytic_charttype,
'hangup_analytic_chartdata': hangup_analytic_chartdata,
'hangup_chartcontainer': 'hangup_piechart_container',
'hangup_extra': hangup_extra,
'country_analytic_charttype': country_analytic_charttype,
'country_analytic_chartdata': country_analytic_chartdata,
'country_chartcontainer': 'country_piechart_container',
'country_extra': country_extra,
}
return render_to_response('cdr/dashboard.html', variables, context_instance=RequestContext(request))
def hangupcause_name(id):
"""Tag is used to get hangupcause name"""
return get_hangupcause_name(id)
def cdr_dashboard(request):
"""CDR dashboard on the last 24 hours
**Attributes**:
* ``template`` - cdr/dashboard.html
* ``form`` - SwitchForm
**Logic Description**:
Display calls aggregated information for the last 24hours, several report will be
created and displayed such as hourly call report and hangup cause/country analytics.
"""
logging.debug('CDR dashboard view start')
form = SwitchForm(request.POST or None)
if form.is_valid():
logging.debug('CDR dashboard view with search option')
switch_id = int(getvar(request, 'switch_id'))
else:
switch_id = 0
# Get list of calls/duration for each of the last 24 hours
(calls_hour_aggr, total_calls, total_duration, total_billsec, total_buy_cost, total_sell_cost) = custom_sql_matv_voip_cdr_aggr_last24hours(request.user, switch_id)
# Build chart data for last 24h calls
(xdata, ydata, ydata2, ydata3, ydata4, ydata5) = ([], [], [], [], [], [])
for i in calls_hour_aggr:
start_time = (time.mktime(calls_hour_aggr[i]['calltime'].timetuple()) * 1000)
xdata.append(start_time)
ydata.append(int(calls_hour_aggr[i]['nbcalls']))
ydata2.append(int(calls_hour_aggr[i]['duration']/60))
ydata3.append(int(calls_hour_aggr[i]['billsec']/60))
ydata4.append(int(calls_hour_aggr[i]['buy_cost']))
ydata5.append(int(calls_hour_aggr[i]['sell_cost']))
tooltip_date = "%d %b %y %H:%M %p"
extra_serie1 = {"tooltip": {"y_start": "", "y_end": " calls"}, "date_format": tooltip_date}
extra_serie2 = {"tooltip": {"y_start": "", "y_end": " min"}, "date_format": tooltip_date}
extra_serie3 = {"tooltip": {"y_start": "", "y_end": " min"}, "date_format": tooltip_date}
extra_serie4 = {"tooltip": {"y_start": "", "y_end": ""}, "date_format": tooltip_date}
extra_serie5 = {"tooltip": {"y_start": "", "y_end": ""}, "date_format": tooltip_date}
kwargs1 = {}
kwargs1['bar'] = True
final_chartdata = {
'x': xdata,
'name1': 'Calls', 'y1': ydata, 'extra1': extra_serie1, 'kwargs1': kwargs1,
'name2': 'Duration', 'y2': ydata2, 'extra2': extra_serie2,
'name3': 'Billsec', 'y3': ydata3, 'extra3': extra_serie3,
'name4': 'Buy cost', 'y4': ydata4, 'extra4': extra_serie4,
'name5': 'Sell cost', 'y5': ydata5, 'extra5': extra_serie5,
}
final_charttype = "linePlusBarChart"
# Get top 5 of country calls for last 24 hours
country_data = custom_sql_aggr_top_country_last24hours(request.user, switch_id, limit=5)
# Build pie chart data for last 24h calls per country
(xdata, ydata) = ([], [])
for country in country_data:
xdata.append(get_country_name(country["country_id"]))
ydata.append(percentage(country["nbcalls"], total_calls))
color_list = ['#FFC36C', '#FFFF9D', '#BEEB9F', '#79BD8F', '#FFB391']
extra_serie = {"tooltip": {"y_start": "", "y_end": " %"}, "color_list": color_list}
country_analytic_chartdata = {'x': xdata, 'y1': ydata, 'extra1': extra_serie}
country_analytic_charttype = "pieChart"
country_extra = {
'x_is_date': False,
'x_axis_format': '',
'tag_script_js': True,
'jquery_on_ready': True,
}
# Get top 10 of hangup cause calls for last 24 hours
hangup_cause_data = custom_sql_aggr_top_hangup_last24hours(request.user, switch_id)
# hangup analytic pie chart data
(xdata, ydata) = ([], [])
for hangup_cause in hangup_cause_data:
xdata.append(str(get_hangupcause_name(hangup_cause["hangup_cause_id"])))
ydata.append(str(percentage(hangup_cause["nbcalls"], total_calls)))
color_list = ['#2A343F', '#7E8282', '#EA9664', '#30998F', '#449935']
extra_serie = {"tooltip": {"y_start": "", "y_end": " %"}, "color_list": color_list}
hangup_analytic_chartdata = {'x': xdata, 'y1': ydata, 'extra1': extra_serie}
hangup_analytic_charttype = "pieChart"
hangup_extra = country_extra
logging.debug("Result calls_hour_aggr %d" % len(calls_hour_aggr))
logging.debug("Result hangup_cause_data %d" % len(hangup_cause_data))
logging.debug("Result country_data %d" % len(country_data))
# Calculate the Average Time of Call
metric_aggr = calculate_act_acd(total_calls, total_duration)
final_extra = {
'x_is_date': True,
'x_axis_format': '%H:%M',
# 'x_axis_format': '%d %b %Y',
'tag_script_js': True,
'jquery_on_ready': True,
'focus_enable': True,
}
logging.debug('CDR dashboard view end')
variables = {
'total_calls': total_calls,
'total_duration': int_convert_to_minute(total_duration),
'total_buy_cost': total_buy_cost,
'total_sell_cost': total_sell_cost,
'metric_aggr': metric_aggr,
'country_data': country_data,
'hangup_analytic': hangup_cause_data,
'form': form,
'final_chartdata': final_chartdata,
'final_charttype': final_charttype,
'final_chartcontainer': 'final_container',
'final_extra': final_extra,
'hangup_analytic_charttype': hangup_analytic_charttype,
'hangup_analytic_chartdata': hangup_analytic_chartdata,
'hangup_chartcontainer': 'hangup_piechart_container',
'hangup_extra': hangup_extra,
'country_analytic_charttype': country_analytic_charttype,
'country_analytic_chartdata': country_analytic_chartdata,
'country_chartcontainer': 'country_piechart_container',
'country_extra': country_extra,
}
return render_to_response('cdr/dashboard.html', variables, context_instance=RequestContext(request))