def topic_sentence_count(topics_id):
if access_public_topic(topics_id):
response = topic_sentence_counts(TOOL_API_KEY,
topics_id,
snapshots_id=None,
timespans_id=None,
foci_id=None,
q=None)
elif is_user_logged_in():
response = topic_sentence_counts(user_mediacloud_key(), topics_id)
else:
return jsonify({'status': 'Error', 'message': 'Invalid attempt'})
return jsonify(response)
def stream_sentence_count_csv(user_mc_key, filename, topics_id, **kwargs):
results = topic_sentence_counts(user_mc_key, topics_id, **kwargs)
clean_results = [{
'date': date,
'numFound': count
} for date, count in results['split'].iteritems()
if date not in ['gap', 'start', 'end']]
sorted_results = sorted(clean_results, key=itemgetter('date'))
props = ['date', 'numFound']
return csv.stream_response(sorted_results, props, filename)
def topic_focal_set_sentences_compare(topics_id, focal_sets_id):
snapshots_id, timespans_id, foci_id, q = filters_from_args(request.args)
all_focal_sets = topic_focal_sets(user_mediacloud_key(), topics_id,
snapshots_id)
# need the timespan info, to find the appropriate timespan with each focus
base_snapshot_timespans = cached_topic_timespan_list(
user_mediacloud_key(), topics_id, snapshots_id=snapshots_id)
# if they have a focus selected, we need to find the appropriate overall timespan
if foci_id is not None:
timespan = topic_timespan(topics_id, snapshots_id, foci_id,
timespans_id)
for t in base_snapshot_timespans:
if timespans_match(timespan, t):
base_timespan = t
else:
base_timespan = None
for t in base_snapshot_timespans:
if t['timespans_id'] == int(timespans_id):
base_timespan = t
logger.info('base timespan = %s', timespans_id)
if base_timespan is None:
return json_error_response("Couldn't find the timespan you specified")
# iterate through to find the one of interest
focal_set = None
for fs in all_focal_sets:
if int(fs['focal_sets_id']) == int(focal_sets_id):
focal_set = fs
if focal_set is None:
return json_error_response('Invalid Focal Set Id')
# collect the sentence counts for each foci
for focus in focal_set['foci']:
# find the matching timespan within this focus
snapshot_timespans = cached_topic_timespan_list(
user_mediacloud_key(),
topics_id,
snapshots_id=snapshots_id,
foci_id=focus['foci_id'])
timespan = None
for t in snapshot_timespans:
if timespans_match(t, base_timespan):
timespan = t
logger.info('matching in focus %s, timespan = %s',
focus['foci_id'], t['timespans_id'])
if timespan is None:
return json_error_response(
'Couldn\'t find a matching timespan in the ' + focus.name +
' focus')
data = topic_sentence_counts(user_mediacloud_key(),
topics_id,
snapshots_id=snapshots_id,
timespans_id=timespan['timespans_id'],
foci_id=focus['foci_id'])
focus['sentence_counts'] = data
return jsonify(focal_set)
def topic_word_sentence_counts(topics_id, word):
return jsonify(
topic_sentence_counts(user_mediacloud_key(), topics_id, q=word))
def topic_media_sentence_count(topics_id, media_id):
return jsonify(topic_sentence_counts(user_mediacloud_key(), topics_id, fq='media_id:'+media_id))