def run(self, form):
form_data = json.dumps(dict(form.data._iterlists()))
size = form.cleaned_data['size']
offset = form.cleaned_data['offset']
show_aggregation = form.cleaned_data['aggregations']
with Timer() as timer:
selection = SelectionSearch(form)
self.monitor.update(1, "Executing query..")
narticles = selection.get_count()
self.monitor.update(39, "Fetching mediums..".format(**locals()))
mediums = selection.get_mediums()
self.monitor.update(59, "Fetching articles..".format(**locals()))
articles = selection.get_articles(size=size, offset=offset)
if show_aggregation:
self.monitor.update(69, "Aggregating..".format(**locals()))
date_aggr = selection.get_aggregate(x_axis="date",
y_axis="total",
interval="day")
medium_aggr = selection.get_aggregate(x_axis="medium",
y_axis="date",
interval="day")
self.monitor.update(79, "Rendering results..".format(**locals()))
return TEMPLATE.render(
Context(
dict(locals(), **{
"project": self.project,
"user": self.user
})))
def run(self, form):
form_data = json.dumps(dict(form.data._iterlists()))
size = form.cleaned_data['size']
offset = form.cleaned_data['offset']
show_aggregation = form.cleaned_data['aggregations']
with Timer() as timer:
selection = SelectionSearch(form)
self.monitor.update(1, "Executing query..")
narticles = selection.get_count()
self.monitor.update(39, "Fetching mediums..".format(**locals()))
mediums = selection.get_mediums()
self.monitor.update(59, "Fetching articles..".format(**locals()))
articles = selection.get_articles(size=size, offset=offset)
if show_aggregation:
self.monitor.update(69, "Aggregating..".format(**locals()))
date_aggr = selection.get_aggregate(x_axis="date", y_axis="total", interval="day")
medium_aggr = selection.get_aggregate(x_axis="medium", y_axis="date", interval="day")
self.monitor.update(79, "Rendering results..".format(**locals()))
return TEMPLATE.render(Context(dict(locals(), **{
"project": self.project, "user": self.user
})))
def run(self, form):
selection = SelectionSearch(form)
try:
# Try to retrieve cache values
primary, secondary, categories, aggregation = self.get_cache()
except NotInCacheError:
self.monitor.update(message="Executing query..")
narticles = selection.get_count()
self.monitor.update(message="Found {narticles} articles. Aggregating..".format(**locals()))
# Get aggregation
order_by = form.cleaned_data["order_by"]
primary = form.cleaned_data["primary"]
secondary = form.cleaned_data["secondary"]
categories = list(filter(None, [primary, secondary]))
aggregation = list(selection.get_aggregate(categories, flat=False))
aggregation = sorted_aggregation(*order_by, aggregation)
self.set_cache([primary, secondary, categories, aggregation])
else:
self.monitor.update(2)
# Matrices are very annoying to construct in javascript due to missing hashtables. If
# the user requests a table, we thus first convert it to a different format which should
# be easier to render.
if form.cleaned_data["output_type"] == "text/json+aggregation+table":
aggregation = aggregation_to_matrix(aggregation, categories)
if form.cleaned_data["output_type"] == "text/csv":
return aggregation_to_csv(aggregation, categories, [CountArticlesValue()])
self.monitor.update(message="Serialising..".format(**locals()))
return json.dumps(aggregation, cls=AggregationEncoder, check_circular=False)
def run(self, form):
selection = SelectionSearch(form)
try:
# Try to retrieve cache values
primary, secondary, categories, aggregation = self.get_cache()
except NotInCacheError:
self.monitor.update(message="Executing query..")
narticles = selection.get_count()
self.monitor.update(message="Found {narticles} articles. Aggregating..".format(**locals()))
# Get aggregation
primary = form.cleaned_data["primary"]
secondary = form.cleaned_data["secondary"]
categories = list(filter(None, [primary, secondary]))
aggregation = list(selection.get_aggregate(categories, flat=False))
self.set_cache([primary, secondary, categories, aggregation])
else:
self.monitor.update(2)
# Matrices are very annoying to construct in javascript due to missing hashtables. If
# the user requests a table, we thus first convert it to a different format which should
# be easier to render.
if form.cleaned_data["output_type"] == "text/json+aggregation+table":
aggregation = aggregation_to_matrix(aggregation, categories)
if form.cleaned_data["output_type"] == "text/csv":
return aggregation_to_csv(aggregation, categories, [CountArticlesValue()])
self.monitor.update(message="Serialising..".format(**locals()))
return json.dumps(aggregation, cls=AggregationEncoder, check_circular=False)
def run(self, form):
form_data = dict(form.data.lists())
for value in form_data.values():
if value == [None]:
value.pop()
form_data = json.dumps(form_data, indent=4)
size = form.cleaned_data['size']
offset = form.cleaned_data['offset']
number_of_fragments = form.cleaned_data['number_of_fragments']
fragment_size = form.cleaned_data['fragment_size']
show_fields = sorted(form.cleaned_data['show_fields'])
show_aggregation = form.cleaned_data['aggregations']
with Timer() as timer:
selection = SelectionSearch(form)
self.monitor.update(message="Executing query..")
narticles = selection.get_count()
self.monitor.update(message="Fetching articles..".format(
**locals()))
articles = selection.get_articles(size=size,
offset=offset).as_dicts()
articles = get_fragments(selection.get_query(),
[a["id"] for a in articles],
fragment_size, number_of_fragments)
if show_aggregation:
self.monitor.update(message="Aggregating..".format(**locals()))
statistics = selection.get_statistics()
try:
delta_start_end = statistics.end_date - statistics.start_date
interval = next(
interval for (interval, delta) in TIMEDELTAS
if MAX_DATE_GROUPS * delta > delta_start_end)
except (StopIteration, TypeError):
interval = "day"
date_aggr = selection.get_aggregate(
[IntervalCategory(interval)], objects=False)
else:
# Increase progress without doing anything (because we don't have to aggregate)
self.monitor.update()
self.monitor.update(message="Rendering results..".format(
**locals()))
return TEMPLATE.render(
Context(
dict(locals(), **{
"project": self.project,
"user": self.user
})))
def run(self, form):
self.monitor.update(1, "Executing query..")
selection = SelectionSearch(form)
narticles = selection.get_count()
self.monitor.update(10, "Found {narticles} articles. Aggregating..".format(**locals()))
# Get aggregation
aggregation = selection.get_aggregate(
form.cleaned_data['x_axis'],
form.cleaned_data['y_axis'],
form.cleaned_data['interval']
)
#
self.monitor.update(20, "Calculating relative values..".format(**locals()))
column = form.cleaned_data['relative_to']
if column is not None:
aggregation = list(get_relative(aggregation, column))
self.monitor.update(60, "Serialising..".format(**locals()))
return json.dumps(list(aggregation), cls=AggregationEncoder, check_circular=False)
def run(self, form):
self.monitor.update(1, "Executing query..")
selection = SelectionSearch(form)
narticles = selection.get_count()
self.monitor.update(
10, "Found {narticles} articles. Aggregating..".format(**locals()))
# Get aggregation
aggregation = selection.get_aggregate(form.cleaned_data['x_axis'],
form.cleaned_data['y_axis'],
form.cleaned_data['interval'])
#
self.monitor.update(20,
"Calculating relative values..".format(**locals()))
column = form.cleaned_data['relative_to']
if column is not None:
aggregation = list(get_relative(aggregation, column))
self.monitor.update(60, "Serialising..".format(**locals()))
return json.dumps(list(aggregation),
cls=AggregationEncoder,
check_circular=False)
