Metadata-Version: 2.1
Name: datadistillr
Version: 0.1.2
Summary: A Python SDK for interacting with datasets created on DataDistillr
Home-page: https://github.com/datadistillr/datadistillr-python-sdk
Author: Charles Givre
Author-email: charles@datadistillr.com
License: Apache
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: System Administrators
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: SQL
Classifier: Operating System :: OS Independent
Classifier: Topic :: Database
Description-Content-Type: text/markdown
License-File: LICENSE

# DataDistillr Python SDK

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This library allows you to programmatically interact with DataDistillr.  It is quite simple to programmatically pull data 
from DataDistillr for use in machine learning. 

## Methods
* `get_dataframe(url, auth_token)`: Pulls your data and returns it in a Pandas DataFrame.
* `get_csv_from_api(url, auth_token, filename)`:  Pulls your data and returns it in a CSV file.
* `get_json_from_api(url, auth_token, filename)`:  Pulls your data and returns it in a JSON file.
* `get_parquet_from_api(url, auth_token, filename)`:  Pulls your data and returns it in a parquet file.
* `get_excel_from_api(url, auth_token, filename)`:  Pulls your data and returns it in an Excel file.
* `get_dict_from_api(url, auth_token, filename)`:  Pulls your data and returns it in a Python dictionary.

### Getting your Endpoint URL and Authorization Token
See https://docs.datadistillr.com/ddr/ for complete documentation on obtaining the URL and Auth Token.

### Usage 
Using the SDK in Python code is quite simple.  See the snippet below:
```python
import datadistillr.datadistillr as ddr
url = <Your URL From DataDistillr>
auth_token = <AUTH TOKEN>
dataframe = ddr.datadistillr.get_dataframe(url, auth_token)
```

