def api_explorer_story_split_count_csv():
filename = 'stories-over-time'
data = request.form
if 'searchId' in data:
solr_q, solr_fq = parse_as_sample(data['searchId'], data['index'])
filename = filename # don't have this info + current_query['q']
SAMPLE_SEARCHES = load_sample_searches()
queries = SAMPLE_SEARCHES[data['searchId']]['queries']
else:
queries = json.loads(data['queries'])
label = " ".join([q['label'] for q in queries])
filename = file_name_for_download(label, filename)
# now compute total attention for all results
story_count_results = []
for q in queries:
solr_q, solr_fq = parse_query_with_keywords(q)
solr_open_query = concatenate_query_for_solr(solr_seed_query='*', media_ids=q['sources'],
tags_ids=q['collections'])
story_counts = apicache.normalized_and_story_count(solr_q, solr_fq, solr_open_query)
story_count_results.append({
'date': q['startDate'],
'query': q['label'],
'matching_stories': story_counts['total'],
'total_stories': story_counts['normalized_total'],
'ratio': float(story_counts['total']) / float(story_counts['normalized_total'])
})
props = ['date','query', 'matching_stories', 'total_stories', 'ratio']
return csv.stream_response(story_count_results, props, filename)
def _get_word_count():
search_id = int(request.args['search_id']) if 'search_id' in request.args else None
sample_size = int(request.args['sampleSize']) if 'sampleSize' in request.args else WORD_COUNT_SAMPLE_SIZE
if search_id not in [None, -1]:
solr_q, solr_fq = parse_as_sample(search_id, request.args['index'])
else:
solr_q, solr_fq = parse_query_with_keywords(request.args)
word_data = query_wordcount(solr_q, solr_fq, sample_size=sample_size)
# return combined data
return jsonify({"results": word_data, "sample_size": str(sample_size)})
def api_explorer_demo_geotag_count():
search_id = int(
request.args['search_id']) if 'search_id' in request.args else None
if search_id not in [None, -1]:
solr_q, solr_fq = parse_as_sample(search_id, request.args['index'])
else:
solr_q, solr_fq = parse_query_with_keywords(request.args)
data = apicache.top_tags_with_coverage(solr_q, solr_fq, tags.GEO_TAG_SET)
data['results'] = _filter_for_countries(data['results'])
return jsonify(data)
def demo_top_tags_with_coverage(tag_sets_id, ):
# parses the query for you
search_id = int(
request.args['search_id']) if 'search_id' in request.args else None
query_index = int(
request.args['index']) if 'index' in request.args else None
if (query_index is None) and (search_id not in [None, -1]):
solr_q, solr_fq = parse_as_sample(search_id, request.args)
else:
solr_q, solr_fq = parse_query_with_keywords(request.args)
return apicache.top_tags_with_coverage(solr_q, solr_fq, tag_sets_id)
def demo_top_tags_with_coverage(tag_sets_id,):
# parses the query for you
search_id = int(request.args['search_id']) if 'search_id' in request.args else None
query_index = int(request.args['index']) if 'index' in request.args else None
if (query_index is None )and (search_id not in [None, -1]):
sample_searches = load_sample_searches()
current_search = sample_searches[search_id]['queries']
solr_q, solr_fq = parse_as_sample(search_id, request.args)
else:
solr_q, solr_fq = parse_query_with_keywords(request.args)
return apicache.top_tags_with_coverage(solr_q, solr_fq, tag_sets_id)
def explorer_wordcount_csv():
data = request.form
ngram_size = data[
'ngramSize'] if 'ngramSize' in data else 1 # defaul to words if ngram not specified
filename = u'sampled-ngrams-{}'.format(ngram_size)
if 'searchId' in data:
solr_q, solr_fq = parse_as_sample(data['searchId'], data['index'])
else:
query_object = json.loads(data['q'])
solr_q, solr_fq = parse_query_with_keywords(query_object)
filename = file_name_for_download(query_object['label'], filename)
return stream_wordcount_csv(filename, solr_q, solr_fq, ngram_size)
def explorer_wordcount_csv():
data = request.form
ngram_size = data['ngramSize'] if 'ngramSize' in data else 1 # defaul to words if ngram not specified
sample_size = data['sample_size'] if 'sample_size' in data else WORD_COUNT_SAMPLE_SIZE
filename = 'sampled-{}-ngrams-{}'.format(sample_size, ngram_size)
if 'searchId' in data:
solr_q, solr_fq = parse_as_sample(data['searchId'], data['index'])
else:
query_object = json.loads(data['q'])
solr_q, solr_fq = parse_query_with_keywords(query_object)
filename = file_name_for_download(query_object['label'], filename)
return stream_wordcount_csv(filename, solr_q, solr_fq, ngram_size, sample_size)
def explorer_entities_csv(tag_sets_id):
tag_set = apicache.tag_set(tag_sets_id)
filename = u'sampled-{}'.format(tag_set['label'])
data = request.form
if 'searchId' in data:
solr_q, solr_fq = parse_as_sample(data['searchId'], data['index'])
else:
query_object = json.loads(data['q'])
solr_q, solr_fq = parse_query_with_keywords(query_object)
filename = file_name_for_download(query_object['label'], filename)
top_tag_counts = apicache.top_tags_with_coverage(solr_q, solr_fq, tag_sets_id, TAG_COUNT_DOWNLOAD_LENGTH)['results']
return csv.stream_response(top_tag_counts, ENTITY_DOWNLOAD_COLUMNS, filename)
def explorer_entities_csv(tag_sets_id):
tag_set = apicache.tag_set(tag_sets_id)
filename = 'sampled-{}'.format(tag_set['label'])
data = request.form
if 'searchId' in data:
solr_q, solr_fq = parse_as_sample(data['searchId'], data['index'])
else:
query_object = json.loads(data['q'])
solr_q, solr_fq = parse_query_with_keywords(query_object)
filename = file_name_for_download(query_object['label'], filename)
top_tag_counts = apicache.top_tags_with_coverage(solr_q, solr_fq, tag_sets_id, TAG_COUNT_DOWNLOAD_LENGTH)['results']
return csv.stream_response(top_tag_counts, ENTITY_DOWNLOAD_COLUMNS, filename)
def api_explorer_demo_story_sample():
search_id = int(request.args['search_id']) if 'search_id' in request.args else None
if search_id not in [None, -1]:
sample_searches = load_sample_searches()
current_search = sample_searches[search_id]['queries']
solr_q, solr_fq = parse_as_sample(search_id, request.args['index'])
else:
solr_q, solr_fq = parse_query_with_keywords(request.args)
story_sample_result = apicache.random_story_list(solr_q, solr_fq, SAMPLE_STORY_COUNT)
for story in story_sample_result:
story["media"] = server.views.apicache.media(story["media_id"])
return jsonify({"results": story_sample_result})
def _get_word_count():
search_id = int(
request.args['search_id']) if 'search_id' in request.args else None
sample_size = int(
request.args['sampleSize']
) if 'sampleSize' in request.args else WORD_COUNT_SAMPLE_SIZE
if search_id not in [None, -1]:
solr_q, solr_fq = parse_as_sample(search_id, request.args['index'])
else:
solr_q, solr_fq = parse_query_with_keywords(request.args)
word_data = query_wordcount(solr_q, solr_fq, sample_size=sample_size)
# return combined data
return jsonify({"results": word_data, "sample_size": str(sample_size)})
def explorer_geo_csv():
filename = u'sampled-geographic-coverage'
data = request.form
if 'searchId' in data:
solr_q, solr_fq = parse_as_sample(data['searchId'], data['index'])
else:
query_object = json.loads(data['q'])
solr_q, solr_fq = parse_query_with_keywords(query_object)
filename = file_name_for_download(query_object['label'], filename)
data = apicache.top_tags_with_coverage(solr_q, solr_fq, tags.GEO_TAG_SET)
data['results'] = _filter_for_countries(data['results'])
props = ['label', 'count', 'pct', 'alpha3', 'iso-a2', 'geonamesId', 'tags_id', 'tag']
return csv.stream_response(data['results'], props, filename)
def explorer_stories_csv():
filename = 'sampled-stories'
data = request.form
if 'searchId' in data:
solr_q, solr_fq = parse_as_sample(data['searchId'], data['uid'])
filename = filename # don't have this info + current_query['q']
# for demo users we only download 100 random stories (ie. not all matching stories)
return _stream_story_list_csv(filename, solr_q, solr_fq, 100, MediaCloud.SORT_RANDOM, 1)
else:
query_object = json.loads(data['q'])
solr_q, solr_fq = parse_query_with_keywords(query_object)
filename = file_name_for_download(query_object['label'], filename)
# now page through all the stories and download them
return _stream_story_list_csv(filename, solr_q, solr_fq)
def explorer_stories_csv():
filename = u'sampled-stories'
data = request.form
if 'searchId' in data:
solr_q, solr_fq = parse_as_sample(data['searchId'], data['index'])
filename = filename # don't have this info + current_query['q']
# for demo users we only download 100 random stories (ie. not all matching stories)
return _stream_story_list_csv(filename, solr_q, solr_fq, 100, MediaCloud.SORT_RANDOM, 1)
else:
query_object = json.loads(data['q'])
solr_q, solr_fq = parse_query_with_keywords(query_object)
filename = file_name_for_download(query_object['label'], filename)
# now page through all the stories and download them
return _stream_story_list_csv(filename, solr_q, solr_fq)
def api_explorer_demo_story_split_count():
search_id = int(request.args['search_id']) if 'search_id' in request.args else None
if isinstance(search_id, int) and search_id not in [None, -1]:
solr_q, solr_fq = parse_as_sample(search_id, request.args['index'])
else:
start_date, end_date = parse_query_dates(request.args)
solr_q, solr_fq = parse_query_with_keywords(request.args)
# why is this call fundamentally different than the cache call???
solr_open_query = concatenate_query_for_solr(solr_seed_query='*',
media_ids=[],
tags_ids=DEFAULT_COLLECTION_IDS)
results = apicache.normalized_and_story_split_count(solr_q, solr_open_query, start_date, end_date)
return jsonify({'results': results})
def api_explorer_demo_story_split_count():
search_id = int(request.args['search_id']) if 'search_id' in request.args else None
if isinstance(search_id, int) and search_id not in [None, -1]:
SAMPLE_SEARCHES = load_sample_searches()
current_search = SAMPLE_SEARCHES[search_id]['queries']
solr_q, solr_fq = parse_as_sample(search_id, request.args['index'])
else:
solr_q, solr_fq = parse_query_with_keywords(request.args)
# why is this call fundamentally different than the cache call???
solr_open_query = concatenate_query_for_solr(solr_seed_query='*',
media_ids=[],
tags_ids=DEFAULT_COLLECTION_IDS)
results = apicache.normalized_and_story_split_count(solr_q, solr_fq, solr_open_query)
return jsonify({'results': results})
def api_explorer_story_split_count():
search_id = int(request.args['search_id']) if 'search_id' in request.args else None
start_date, end_date = parse_query_dates(request.args)
if only_queries_reddit(request.args):
results = pushshift.reddit_submission_normalized_and_split_story_count(query=request.args['q'],
start_date=start_date, end_date=end_date,
subreddits=pushshift.NEWS_SUBREDDITS)
else:
# get specific stories by keyword
if isinstance(search_id, int) and search_id not in [None, -1]:
solr_q, solr_fq = parse_as_sample(search_id, request.args['index'])
else:
solr_q, solr_fq = parse_query_with_keywords(request.args)
# get all the stories (no keyword) so we can support normalization
solr_open_query = concatenate_query_for_solr(solr_seed_query='*',
media_ids=request.args['sources'],
tags_ids=request.args['collections'])
results = apicache.normalized_and_story_split_count(solr_q, solr_open_query, start_date, end_date)
return jsonify({'results': results})
def api_explorer_story_split_count_csv():
filename = u'stories-over-time'
data = request.form
if 'searchId' in data:
solr_q, solr_fq = parse_as_sample(data['searchId'], data['index'])
filename = filename # don't have this info + current_query['q']
# TODO solr_open_query
else:
query_object = json.loads(data['q'])
solr_q, solr_fq = parse_query_with_keywords(query_object)
filename = file_name_for_download(query_object['label'], filename)
solr_open_query = concatenate_query_for_solr(
solr_seed_query='*',
media_ids=query_object['sources'],
tags_ids=query_object['collections'])
results = apicache.normalized_and_story_split_count(
solr_q, solr_fq, solr_open_query)
props = ['date', 'count', 'total_count', 'ratio']
return csv.stream_response(results['counts'], props, filename)
def api_explorer_story_split_count():
search_id = int(request.args['search_id']) if 'search_id' in request.args else None
index = int(request.args['index']) if 'index' in request.args else None
#get specific stories by keyword
if isinstance(search_id, int) and search_id not in [None, -1]:
SAMPLE_SEARCHES = load_sample_searches()
current_search = SAMPLE_SEARCHES[search_id]['queries']
solr_q, solr_fq = parse_as_sample(search_id, request.args['index'])
else:
solr_q, solr_fq = parse_query_with_keywords(request.args)
# get all the stories (no keyword)
solr_open_query = concatenate_query_for_solr(solr_seed_query='*',
media_ids=request.args['sources'],
tags_ids=request.args['collections'])
results = apicache.normalized_and_story_split_count(solr_q, solr_fq, solr_open_query)
return jsonify({'results': results})
