Metadata-Version: 2.4
Name: connectron
Version: 0.1.2
Summary: Unified ETL Connector for All Sources and Sink
Author-email: Metta Jagadeesh Reddy <Jagadeeshjai334869@gmail.com>
License: MIT
Keywords: ETL,API,Data,Connector,Integration
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: requests==2.32.5
Requires-Dist: pandas==2.3.3
Requires-Dist: pyarrow
Requires-Dist: rich
Requires-Dist: msal==1.34.0
Dynamic: license-file

![CONNECTRON](image.png)

Connectron is Unified ETL connector for all sources and sink.

It is used to avoid regular boilerplate code.

Currently Supported:

        Sources: Microsoft Dataverse

        Sink: ADLS Gen2


Working:
        Works on 3 Objects Principle:

        1.Authenticator Object.
            * Create an Authenticator Object to Connect to Source or Sink.

        2.Source Object:
            * Connect to Source with Authentication object and Query Source.
            * You can Query Sources with different endpoints (API),Tables(Database),Files(Object Storage) with different parameters (Interval,Last x days,Filters,Select columns).
            * By Default it will provide converted object to Pandas Dataframe with Serilization(You can pass parameters as raw to get raw data fetched from Source)
            * You can use sample function available for Source to see Schema,Data without before downloading full Data.(You will get 100 records as Default).

        3.Sink Object:
            * Create Sink object to place objects at Sink.

Future Scope:

        Log Object: For Auditing connectron will store logs of all processes within connectron with:
                1. csv/json/parquet Files.
                2. Delta support in any cloud (Azure,AWS,GCP).
