test.py

import pandas
import pandas as pd
from elasticsearch.helpers import bulk
from numpy import int64
from pymongo import MongoClient
from sqlalchemy import create_engine

from clients.elastic_client import ElasticClient
from clients.mongo_connector import MongoDBConnector
from utils import map_dtype_to_elk_type, df_lookup

# engine = create_engine("postgresql://admin:admin@qualichain.epu.ntua.gr:5432/api_db")
# table_df = pd.read_sql_table('job_post', engine)
#
# print(table_df.shape)
#
# new_table = table_df.drop_duplicates(subset="job_url")
# print(new_table.shape)
#
#
# # documents = table_df.to_dict(orient='records')
# # ELK = ElasticClient()
# # es = ELK.es_obj
# # bulk(es, documents, index='my_index', raise_on_error=True)
#
# # print(table_df.name)
# # print(df_lookup(table_df))
# part = 'empDetails'
#
# mongo_uri = 'mongodb://my_user:password123@localhost:27017/my_database'
#
# m = MongoDBConnector(part)
# res = m.check_if_uri_is_valid(uri=mongo_uri)
# if res:
#
#     data = pandas.DataFrame(list(m.collection.find()))
#     print(data.head())

upscript = {
        "script": {
            "source": "ctx._source.skills.add(params.tag)",
            "lang": "painless",
            "params": {
                "tag": "elixir"
            }
        }
}

client = ElasticClient()
client.es_obj.update(index="qc_index_temp", id='oXN4e3MBFv3_0b1IBNte', body="upscript")

# should = [
#     {"multi_match": {
#         "query": "backend engineer",
#         "fields": ["title", "requirements"],
#         "type": "phrase",
#         "slop": 2}
#     },
#     {"multi_match": {
#         "query": "backend developer",
#         "fields": ["title", "requirements"],
#         "type": "phrase",
#         "slop": 2}
#     }
# ]
# params = {'index': 'my_index', 'min_score': 4, '_source': ["id"], "should":should}
#
# results = client.bool_queries(index='my_index', min_score=4, _source=["id"], should=should)
# print(results)