def is_field_number(report, field_name):
model = loads(report.model)
classobj = model.get_class_object()
field = classobj._meta.get_field_by_name(field_name)[0]
if number_field_regex.match(field.get_internal_type()):
return True
return False
def is_field_number(report, field_name):
model = loads(report.model)
classobj = model.get_class_object()
field = classobj._meta.get_field_by_name(field_name)[0]
if number_field_regex.match(field.get_internal_type()):
return True
return False
def display_chart(context, chart, skip_group=False):
"Return HTML for chart"
request = context['request']
response_format = 'html'
if 'response_format' in context:
response_format = context['response_format']
options = loads(chart.options)
content = _get_report_content(chart.report, request)
objs = content['set']
chart_dict = {}
field_name = options['grouping']
model = loads(chart.report.model)
chart_dict['yAxis'] = {'allowDecimals': False,
'title': {
'text': model.name.split('.')[-1] + " Count vs. " + field_name.replace('_', ' ').title()}
}
chart_dict['xAxis'] = {}
try:
xfield = objs[0]._meta.get_field_by_name(field_name)[0]
except:
chart.delete()
return
def get_date(g, mindate):
if g and g != datetime.min.date():
return g
else:
return mindate
if xfield.get_internal_type() == 'ManyToManyField':
l = []
for obj in objs:
for mi in getattr(obj, field_name).all():
l.append(unicode(mi))
elif xfield.get_internal_type() == 'DateTimeField' or xfield.get_internal_type() == 'DateField':
chart_dict['xAxis']['labels'] = { # 'rotation':90,
'align': 'left',
'x': 3,
'y': 15}
l, m, datelist = [], [], []
maxdate = None
mindate = None
for obj in objs:
if getattr(obj, field_name):
x = getattr(obj, field_name)
if xfield.get_internal_type() == 'DateTimeField':
x = x.date()
if not maxdate or x > maxdate:
maxdate = x
if not mindate or x < mindate:
mindate = x
datelist.append(x)
if unicode(x) not in m:
m.append(unicode(x))
else:
datelist.append(datetime.min.date())
while datetime.min.date() in datelist:
datelist.append(mindate)
datelist.remove(datetime.min.date())
datelist = sorted(datelist, key=lambda g: get_date(g, mindate))
l = [unicode(g) for g in datelist]
# chart_dict['xAxis']['categories']=m
chart_dict['xAxis']['type'] = 'datetime'
td = maxdate - mindate
# print (td.microseconds + (td.seconds + td.days * 24 * 3600) * 10**6) / 10**6
chart_dict['zoomType'] = 'x'
chart_dict['xAxis']['tickInterval'] = (
td.microseconds + (
td.seconds + td.days * 24 * 3600) * 10 ** 6) / 10 ** 4
# chart_dict['xAxis']['tickWidth']= 0,
chart_dict['maxZoom'] = 14 * 24 * 3600000 # 2wks
# chart_dict['xAxis']['gridLineWidth']= 1,
chart_dict['series'] = [{'name': model.name.split('.')[-1], 'data': []}]
for x in set(l):
chart_dict['series'][0]['data'].append(('{0!s} UTC'.format(x), l.count(x)))
else:
l = [unicode(obj.get_field_value(field_name)) for obj in objs]
if 'series' not in chart_dict:
chart_dict['series'] = []
# chart_dict['series'].append({'name':field_name, 'data': [{'name': x, 'y':l.count(x)} for x in set(l)]})
chart_dict['series'].append({'name': field_name.replace(
'_', ' ').title(), 'data': [[x, l.count(x)] for x in set(l)]})
# for x in set(l):
# chart_dict['series'].append({'name':x, 'data': l.count(x)})
# chart_dict['series'].append({'data':[{'name':x, 'y': [l.count(x)]} for x in set(l)]})
if 'xAxis' not in chart_dict:
chart_dict['xAxis']['categories'] = [x for x in set(l)]
# Chart type specific options
if 'legend' in options and options['legend'] == 'on':
chart_dict['legend'] = {
'layout': 'vertical',
'align': 'right',
'verticalAlign': 'top',
'x': -10,
'y': 100,
'borderWidth': 0
}
if 'title' in options:
chart_dict['title'] = {'text': options['title']}
# Create a hash and use it as a unqiue div id and var name for the chart.
hasher = hashlib.md5()
hasher.update(str(random()))
id = 'chartcontainer' + str(hasher.hexdigest())
# Disable animation for when saving as PDF
chart_dict['chart'] = {'renderTo': id,
'defaultSeriesType': options['type']}
# chart_dict['plotOptions'] = {'series': {'animation': False}}
chart_dict['plotOptions'] = {'pie': {
'allowPointSelect': True,
'cursor': 'pointer',
'dataLabels': {
'enabled': False
},
'showInLegend': True
}}
chart_dict['credits'] = {'enabled': False}
rendered_options = json.dumps(chart_dict)
rendered_options = rendered_options[
:-1] + ", tooltip: {formatter: function() {return '<b>'+ this.point.name +'</b>: '+ this.y;}}}"
if 'type' in chart_dict['xAxis'] and chart_dict['xAxis']['type'] == 'datetime':
rendered_options += """
datedata = [];
jQuery.each(options.series[0].data, function(i,item){
date = Date.parse(item[0]);
count = item[1];
datedata.push([date, count]);
});
options.series[0].data = datedata;
function merge_options(obj1,obj2){
var obj3 = {};
for (attrname in obj1) { obj3[attrname] = obj1[attrname]; }
for (attrname in obj2) { obj3[attrname] = obj2[attrname]; }
return obj3;
}
var dateoptions = {
tooltip: {
shared: true,
crosshairs: true
},
};
options = merge_options(options, dateoptions);
"""
return Markup(render_to_string('reports/tags/chart',
{'rendered_options': rendered_options,
'id': id,
'chart_id': chart.id,
'chart': chart,
'name': options['title']},
context_instance=RequestContext(request),
response_format=response_format))
def display_chart(context, chart, skip_group=False):
"Return HTML for chart"
request = context['request']
response_format = 'html'
if 'response_format' in context:
response_format = context['response_format']
options = loads(chart.options)
content = _get_report_content(chart.report, request)
objs = content['set']
chart_dict = {}
field_name = options['grouping']
model = loads(chart.report.model)
chart_dict['yAxis'] = {
'allowDecimals': False,
'title': {
'text':
model.name.split('.')[-1] + " Count vs. " +
field_name.replace('_', ' ').title()
}
}
chart_dict['xAxis'] = {}
try:
xfield = objs[0]._meta.get_field_by_name(field_name)[0]
except:
chart.delete()
return
def get_date(g, mindate):
if g and g != datetime.min.date():
return g
else:
return mindate
if xfield.get_internal_type() == 'ManyToManyField':
l = []
for obj in objs:
for mi in getattr(obj, field_name).all():
l.append(unicode(mi))
elif xfield.get_internal_type(
) == 'DateTimeField' or xfield.get_internal_type() == 'DateField':
chart_dict['xAxis']['labels'] = { # 'rotation':90,
'align': 'left',
'x': 3,
'y': 15
}
l, m, datelist = [], [], []
maxdate = None
mindate = None
for obj in objs:
if getattr(obj, field_name):
x = getattr(obj, field_name)
if xfield.get_internal_type() == 'DateTimeField':
x = x.date()
if not maxdate or x > maxdate:
maxdate = x
if not mindate or x < mindate:
mindate = x
datelist.append(x)
if unicode(x) not in m:
m.append(unicode(x))
else:
datelist.append(datetime.min.date())
while datetime.min.date() in datelist:
datelist.append(mindate)
datelist.remove(datetime.min.date())
datelist = sorted(datelist, key=lambda g: get_date(g, mindate))
l = [unicode(g) for g in datelist]
# chart_dict['xAxis']['categories']=m
chart_dict['xAxis']['type'] = 'datetime'
td = maxdate - mindate
# print (td.microseconds + (td.seconds + td.days * 24 * 3600) * 10**6) / 10**6
chart_dict['zoomType'] = 'x'
chart_dict['xAxis']['tickInterval'] = (
td.microseconds +
(td.seconds + td.days * 24 * 3600) * 10**6) / 10**4
# chart_dict['xAxis']['tickWidth']= 0,
chart_dict['maxZoom'] = 14 * 24 * 3600000 # 2wks
# chart_dict['xAxis']['gridLineWidth']= 1,
chart_dict['series'] = [{
'name': model.name.split('.')[-1],
'data': []
}]
for x in set(l):
chart_dict['series'][0]['data'].append(
('{0!s} UTC'.format(x), l.count(x)))
else:
l = [unicode(obj.get_field_value(field_name)) for obj in objs]
if 'series' not in chart_dict:
chart_dict['series'] = []
# chart_dict['series'].append({'name':field_name, 'data': [{'name': x, 'y':l.count(x)} for x in set(l)]})
chart_dict['series'].append({
'name':
field_name.replace('_', ' ').title(),
'data': [[x, l.count(x)] for x in set(l)]
})
# for x in set(l):
# chart_dict['series'].append({'name':x, 'data': l.count(x)})
# chart_dict['series'].append({'data':[{'name':x, 'y': [l.count(x)]} for x in set(l)]})
if 'xAxis' not in chart_dict:
chart_dict['xAxis']['categories'] = [x for x in set(l)]
# Chart type specific options
if 'legend' in options and options['legend'] == 'on':
chart_dict['legend'] = {
'layout': 'vertical',
'align': 'right',
'verticalAlign': 'top',
'x': -10,
'y': 100,
'borderWidth': 0
}
if 'title' in options:
chart_dict['title'] = {'text': options['title']}
# Create a hash and use it as a unqiue div id and var name for the chart.
hasher = hashlib.md5()
hasher.update(str(random()))
id = 'chartcontainer' + str(hasher.hexdigest())
# Disable animation for when saving as PDF
chart_dict['chart'] = {
'renderTo': id,
'defaultSeriesType': options['type']
}
# chart_dict['plotOptions'] = {'series': {'animation': False}}
chart_dict['plotOptions'] = {
'pie': {
'allowPointSelect': True,
'cursor': 'pointer',
'dataLabels': {
'enabled': False
},
'showInLegend': True
}
}
chart_dict['credits'] = {'enabled': False}
rendered_options = json.dumps(chart_dict)
rendered_options = rendered_options[:-1] + ", tooltip: {formatter: function() {return '<b>'+ this.point.name +'</b>: '+ this.y;}}}"
if 'type' in chart_dict['xAxis'] and chart_dict['xAxis'][
'type'] == 'datetime':
rendered_options += """
datedata = [];
jQuery.each(options.series[0].data, function(i,item){
date = Date.parse(item[0]);
count = item[1];
datedata.push([date, count]);
});
options.series[0].data = datedata;
function merge_options(obj1,obj2){
var obj3 = {};
for (attrname in obj1) { obj3[attrname] = obj1[attrname]; }
for (attrname in obj2) { obj3[attrname] = obj2[attrname]; }
return obj3;
}
var dateoptions = {
tooltip: {
shared: true,
crosshairs: true
},
};
options = merge_options(options, dateoptions);
"""
return Markup(
render_to_string('reports/tags/chart', {
'rendered_options': rendered_options,
'id': id,
'chart_id': chart.id,
'chart': chart,
'name': options['title']
},
context_instance=RequestContext(request),
response_format=response_format))
