colouring-montreal/etl/planning_data/obtain_livestream_data.py
2022-10-05 19:52:45 +02:00

88 lines
2.6 KiB
Python

import json
import jsbeautifier
import make_query
def main():
output = make_query.obtain_data(get_query())
# print(json.dumps(output))
opts = jsbeautifier.default_options()
opts.indent_size = 2
print(jsbeautifier.beautify(json.dumps(output), opts))
def get_query():
true = True # makes possible to copy JSON into Python code
return {
"params": {
"ignoreThrottled": true,
"index": "applications",
"body": {
"version": true,
"size": 500,
"sort": [
{
"last_updated": {
"order": "desc",
"unmapped_type": "boolean"
}
}
],
"aggs": {
"2": {
"date_histogram": {
"field": "last_updated",
"calendar_interval": "1d",
"time_zone": "Europe/London",
"min_doc_count": 1
}
}
},
"stored_fields": [
"*"
],
"script_fields": {},
"docvalue_fields": [],
"_source": {
"excludes": []
},
"query": {
"bool": {
"must": [],
"filter": [
{
"range": {
"decision_date": {
"gte": "1922-01-01T00:00:00.000Z",
"format": "strict_date_optional_time"
}
}
}
],
"should": [],
"must_not": []
}
},
"highlight": {
"pre_tags": [
"@kibana-highlighted-field@"
],
"post_tags": [
"@/kibana-highlighted-field@"
],
"fields": {
"*": {}
},
"fragment_size": 2147483647
}
},
"rest_total_hits_as_int": true,
"ignore_unavailable": true,
"ignore_throttled": true,
"timeout": "30000ms"
}
}
if __name__ == '__main__':
main()