def api_explorer_demo_compare_words():
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()
compared_sample_queries = sample_searches[search_id]['queries']
results = []
for cq in compared_sample_queries:
solr_q, solr_fq = parse_query_with_keywords(cq)
word_count_result = query_wordcount(solr_q, solr_fq)
results.append(word_count_result)
else:
compared_queries = request.args['compared_queries[]'].split(',')
results = []
for cq in compared_queries:
dictq = {
x[0]: x[1]
for x in [x.split("=") for x in cq[1:].split("&")]
}
solr_q, solr_fq = parse_query_with_keywords(dictq)
word_count_result = query_wordcount(solr_q, solr_fq)
results.append(word_count_result)
return jsonify({"results": results})
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 api_explorer_story_sample():
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 api_explorer_story_sample():
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"] = apicache.media(story["media_id"])
return jsonify(story_sample_result)
def api_explorer_sentences_list():
around_word = 'word' in request.form
if only_queries_reddit(request.form):
start_date, end_date = parse_query_dates(request.form)
provider = RedditPushshiftProvider()
results = provider.samples(query=request.args['q'],
start_date=start_date,
end_date=end_date,
subreddits=NEWS_SUBREDDITS)
results = [{
'sentence': r['title'],
'publish_date': r['publish_date'],
'story': r,
} for r in results]
else:
solr_q, solr_fq = parse_query_with_keywords(request.form)
# so we can support large samples or just a few to show
rows = int(request.form['rows']) if 'rows' in request.form else 10
results = apicache.sentence_list(solr_q,
solr_fq,
rows=rows,
include_stories=(not around_word))
if around_word:
word = request.form['word']
results = [
_sentence_fragment_around(word, s['sentence']) for s in results
if s['sentence'] is not None
]
results = [s for s in results if s is not None]
return jsonify({'results': results})
def api_explorer_demo_sentences_count():
two_weeks_before_now = datetime.datetime.now() - datetime.timedelta(
days=14)
start_date = two_weeks_before_now.strftime("%Y-%m-%d")
end_date = datetime.datetime.now().strftime("%Y-%m-%d")
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
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_query = parse_query_with_args_and_sample_search(
request.args, current_search)
if index < len(current_search):
start_date = current_search[index]['startDate']
end_date = current_search[index]['endDate']
else:
solr_query = parse_query_with_keywords(request.args)
# why is this call fundamentally different than the cache call???
sentence_count_result = mc.sentenceCount(solr_query=solr_query,
split_start_date=start_date,
split_end_date=end_date,
split=True)
results = cached_by_query_sentence_counts(solr_query, start_date, end_date)
return jsonify(results)
def explorer_story_count_csv():
filename = u'total-story-count'
data = request.form
if 'searchId' in data:
# TODO: don't load this query twice because that is kind of dumb
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({
'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 = ['query', 'matching_stories', 'total_stories', 'ratio']
return csv.stream_response(story_count_results, props, filename)
def explorer_story_count_csv():
filename = 'total-story-count'
data = request.form
if 'searchId' in data:
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:
if (len(q['collections']) == 0) and only_queries_reddit(q['sources']):
start_date, end_date = parse_query_dates(q)
story_counts = pushshift.reddit_submission_normalized_and_split_story_count(query=q['q'],
start_date=start_date,
end_date=end_date,
subreddits=pushshift.NEWS_SUBREDDITS)
else:
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({
'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 = ['query', 'matching_stories', 'total_stories', 'ratio']
return csv.stream_response(story_count_results, props, filename)
def explorer_story_count_csv():
filename = 'total-story-count'
data = request.form
if 'searchId' in data:
# TODO: don't load this query twice because that is kind of dumb
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({
'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 = ['query', 'matching_stories', 'total_stories', 'ratio']
return csv.stream_response(story_count_results, props, filename)
def stream_story_count_csv(fn, search_id_or_query_list):
'''
Helper method to stream a list of stories back to the client as a csv. Any args you pass in will be
simply be passed on to a call to topicStoryList.
'''
# if we have a search id, we load the samples from our sample searches file
filename = ''
story_count_results = []
SAMPLE_SEARCHES = load_sample_searches()
try:
search_id = int(search_id_or_query_list)
if search_id >= 0:
SAMPLE_SEARCHES = load_sample_searches()
sample_queries = SAMPLE_SEARCHES[search_id]['queries']
for query in sample_queries:
solr_query = prep_simple_solr_query(query)
storyList = cached_story_count(solr_query)
query_and_story_count = {'query' : query['label'], 'count' : storyList['count']}
story_count_results.append(query_and_story_count)
except Exception as e:
custom_queries = json.loads(search_id_or_query_list)
for query in custom_queries:
solr_query = parse_query_with_keywords(query)
filename = fn + query['q']
storyList = cached_story_count(solr_query)
query_and_story_count = {'query' : query['label'], 'count' : storyList['count']}
story_count_results.append(query_and_story_count)
props = ['query','count']
return csv.stream_response(story_count_results, props, filename)
def _get_word_count():
sample_size = int(
request.form['sampleSize']
) if 'sampleSize' in request.form else WORD_COUNT_SAMPLE_SIZE
solr_q, solr_fq = parse_query_with_keywords(request.form)
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_compare_words():
compared_queries = request.args['compared_queries[]'].split(',')
results = []
for cq in compared_queries:
dictq = {x[0]: x[1] for x in [x.split("=") for x in cq[1:].split("&")]}
solr_q, solr_fq = parse_query_with_keywords(dictq)
word_count_result = query_wordcount(solr_q, solr_fq)
results.append(word_count_result)
return jsonify({"list": results})
def api_explorer_compare_words():
compared_queries = request.args['compared_queries[]'].split(',')
results = []
for cq in compared_queries:
dictq = {x[0]: x[1] for x in [x.split("=") for x in cq[1:].split("&")]}
solr_q, solr_fq = parse_query_with_keywords(dictq)
word_count_result = query_wordcount(solr_q, solr_fq)
results.append(word_count_result)
return jsonify({"list": results})
def explorer_geo_csv():
filename = 'sampled-geographic-coverage'
data = request.form
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)
props = ['tags_id', 'label', 'count', 'pct']
return csv.stream_response(data['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 api_explorer_sentences_list():
solr_q, solr_fq = parse_query_with_keywords(request.args)
rows = int(request.args['rows']) if 'rows' in request.args else 10 # so we can support large samples or just a few to show
around_word = 'word' in request.args
results = apicache.sentence_list(solr_q, solr_fq, rows=rows, include_stories=(not around_word))
if around_word:
word = request.args['word']
results = [_sentence_fragment_around(word, s['sentence']) for s in results if s['sentence'] is not None]
results = [s for s in results if s is not None]
return jsonify({'results': results})
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
if search_id not in [None, -1]:
sample_searches = load_sample_searches()
current_search = sample_searches[search_id]['queries']
solr_q, solr_fq = parse_query_with_args_and_sample_search(request.args, current_search)
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]):
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_entities_csv(tag_sets_id):
tag_set = base_apicache.tag_set(tag_sets_id)
filename = 'sampled-{}'.format(tag_set['label'])
data = request.form
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_geotag_count():
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_query_with_args_and_sample_search(request.args, current_search)
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]):
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 api_explorer_demo_compare_words():
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()
compared_sample_queries = sample_searches[search_id]['queries']
results = []
for cq in compared_sample_queries:
solr_q, solr_fq = parse_query_with_keywords(cq)
word_count_result = query_wordcount(solr_q, solr_fq)
results.append(word_count_result)
else:
compared_queries = request.args['compared_queries[]'].split(',')
results = []
for cq in compared_queries:
dictq = {x[0]:x[1] for x in [x.split("=") for x in cq[1:].split("&")]}
solr_q, solr_fq = parse_query_with_keywords(dictq)
word_count_result = query_wordcount(solr_q, solr_fq)
results.append(word_count_result)
return jsonify({"results": results})
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 = '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_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)
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 api_explorer_demo_story_count():
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_query = parse_query_with_args_and_sample_search(request.args, current_search)
else:
solr_query = parse_query_with_keywords(request.args)
story_count_result = cached_story_count(solr_query)
# maybe check admin role before we run this?
return jsonify(story_count_result) # give them back new data, so they can update the client
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_query = parse_query_with_args_and_sample_search(request.args, current_search)
else:
solr_query = parse_query_with_keywords(request.args)
story_count_result = cached_story_samples(solr_query)
return jsonify(story_count_result)
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 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
if search_id not in [None, -1]:
sample_searches = load_sample_searches()
current_search = sample_searches[search_id]['queries']
solr_q, solr_fq = parse_query_with_args_and_sample_search(
request.args, current_search)
else:
solr_q, solr_fq = parse_query_with_keywords(request.args)
word_data = query_wordcount(solr_q, solr_fq)
# return combined data
return jsonify({"list": word_data})
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 _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_wordcount_csv():
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_query = parse_query_with_args_and_sample_search(request.args, current_search)
else:
solr_query = parse_query_with_keywords(request.args)
# TODO what about other params: date etc for demo..
return stream_wordcount_csv(mc, 'wordcounts-Explorer', solr_query)
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_query_with_args_and_sample_search(request.args, current_search)
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"] = apicache.media(story["media_id"])
return jsonify(story_sample_result)
def api_explorer_story_sample():
if only_queries_reddit(request.form):
start_date, end_date = parse_query_dates(request.form)
provider = RedditPushshiftProvider()
results = provider.sample(query=request.form['q'],
start_date=start_date, end_date=end_date,
subreddits=NEWS_SUBREDDITS)
else:
solr_q, solr_fq = parse_query_with_keywords(request.form)
results = base_cache.story_list(None, solr_q, solr_fq, rows=SAMPLE_STORY_COUNT,
sort=MediaCloud.SORT_RANDOM)
for story in results: # add in media info so we can show it to user if they click into the drill-down
story["media"] = base_cache.media(story["media_id"])
return jsonify({"results": results})
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 _get_word_count():
search_id = int(
request.args['search_id']) if 'search_id' in request.args else None
sample_size = int(
request.args['sample_size']
) if 'sample_size' in request.args else WORD_COUNT_SAMPLE_SIZE
if search_id not in [None, -1]:
sample_searches = load_sample_searches()
current_search = sample_searches[search_id]['queries']
solr_q, solr_fq = parse_query_with_args_and_sample_search(
request.args, current_search)
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({"list": word_data, "sample_size": str(sample_size)})
def stream_geo_csv(fn, search_id_or_query, index):
filename = ''
# TODO: there is duplicate code here...
SAMPLE_SEARCHES = load_sample_searches()
try:
search_id = int(search_id_or_query)
if search_id >= 0:
SAMPLE_SEARCHES = load_sample_searches()
current_search = SAMPLE_SEARCHES[search_id]['queries']
solr_query = parse_query_with_args_and_sample_search(
search_id, current_search)
if int(index) < len(current_search):
start_date = current_search[int(index)]['startDate']
end_date = current_search[int(index)]['endDate']
filename = fn + current_search[int(index)]['q']
except Exception as e:
# so far, we will only be fielding one keyword csv query at a time, so we can use index of 0
query = json.loads(search_id_or_query)
current_query = query[0]
solr_query = parse_query_with_keywords(current_query)
filename = fn + current_query['q']
res = cached_geotags(solr_query)
res = [
r for r in res
if int(r['tag'].split('_')[1]) in COUNTRY_GEONAMES_ID_TO_APLHA3.keys()
]
for r in res:
geonamesId = int(r['tag'].split('_')[1])
if geonamesId not in COUNTRY_GEONAMES_ID_TO_APLHA3.keys(
): # only include countries
continue
r['geonamesId'] = geonamesId
r['alpha3'] = COUNTRY_GEONAMES_ID_TO_APLHA3[geonamesId]
r['count'] = (
float(r['count']) / float(tag_utl.GEO_SAMPLE_SIZE)
) # WTF: why is the API returning this as a string and not a number?
for hq in HIGHCHARTS_KEYS:
if hq['properties']['iso-a3'] == r['alpha3']:
r['iso-a2'] = hq['properties']['iso-a2']
r['value'] = r['count']
props = ['label', 'count']
return csv.stream_response(res, props, filename)
def api_explorer_story_split_count():
start_date, end_date = parse_query_dates(request.form)
if only_queries_reddit(request.form):
provider = RedditPushshiftProvider()
results = provider.normalized_count_over_time(query=request.form['q'],
start_date=start_date, end_date=end_date,
subreddits=NEWS_SUBREDDITS)
else:
# get specific stories by keyword
solr_q, _solr_fq = parse_query_with_keywords(request.form)
# get all the stories (no keyword) so we can support normalization
solr_open_query = concatenate_query_for_solr(solr_seed_query='*',
media_ids=request.form['sources'],
tags_ids=request.form['collections'],
custom_ids=request.form['searches'])
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():
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})
def top_entities_people():
solr_q, solr_fq = parse_query_with_keywords(request.args)
results = apicache.top_tags_with_coverage(solr_q, solr_fq, CLIFF_PEOPLE)
return jsonify(results)
def top_entities_organizations():
solr_q, solr_fq = parse_query_with_keywords(request.args)
results = apicache.top_tags_with_coverage(solr_q, solr_fq, CLIFF_ORGS)
return jsonify(results)
def top_themes():
solr_q, solr_fq = parse_query_with_keywords(request.args)
results = apicache.top_tags_with_coverage(solr_q, solr_fq, NYT_LABELS_TAG_SET_ID)
return jsonify(results)
