In this repo , i put some simple codes which are useful in day to day life of a developer .

The repo will be having code base of python codes .

####################### 1st .py file In this my first try is to put some basic's of connecting python(3.6) with mongodb secoundary db in server , many people face serious problem's in configuration .

This configuration.py file also contains basic mongo query operation , to pull data in various ways .

#################### 2nd .py file
In python_elastic_search.py file , i tried to do the below task ,

--> create index in server side elastic search one index using pyelasticsearch package .

--> tried to make a mapping for our index , before pushing data .

--> tried pushing data into elasticsearch index type by restful API's (GET & POST requests)

--> pull data from elastic search into local python console .

################### 3rd .py file

In Date_parser.py file , i had tried to include a awesome library from natty called as dateparser to parse textual dates like , yesterday , tomorrow , or any other format . It can extract dates from a string contain a date like below .

" my birthday was tomorrow " = It will extract tomorrow and give tomorrows date in datetime format
datetime.datetime(2018, 3, 14, 17, 9, 56)

I created two functions in this file , first(DateParsing(inp2)) to identify dates , secound is to compare is the asked date ispresent or past or future date (which_date() ) .

########## data_update_elastic.py

1.In this file , i have demonstrated a way how you can define your own schema

for your database in elastic , and push some data according to that .

2. Defined a function called provider_value_insert(provider_name,sensor_1,sensor_2,sensor_3), which allows any users to create

a index/database in elasticSearch ,along with 3 tables .

The dates are defined for today , previous and day before yesterday .

I hard coded the data inside , but users are free to change and manipulate as per there choices .

Then i used standard CURL requests to push data into elastic search .

###########multiple_db_query.py

1. I created a function called ,provider_details(providers_name,single_sensor_retrievel,data_inserted_in_sensor) , which basically gives users

flexibility to decide which DB user want to access , along with , define a single table/type value whose data user wants to see .

third if after manipulation user wants to push changes to a selected table he can describe it here .

In this i tried to pull data from multiple index/dbs from elasticsearch .