Metadata-Version: 2.1
Name: pyplatform-reporting
Version: 2020.8.1
Summary: Pyplatform-reporting package provides function for managing  hyper datasources on Tableau server.
Home-page: https://github.com/mhadi813/pyplatform
Author: Muhammad Hadi
Author-email: mhadi813@gmail.com
License: BSD
Keywords: google bigquery cloud functions storage jupyterlab python SQL
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Office/Business
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
Requires-Dist: tableauhyperapi (>=0.0.10622)
Requires-Dist: tableauserverclient (>=0.10)
Requires-Dist: pantab (>=1.1.0)
Requires-Dist: xlrd
Requires-Dist: XlsxWriter
Requires-Dist: openpyxl
Requires-Dist: pyplatform-common

### Pyplatform-reporting package provides function for managing  hyper datasources on Tableau server.

## Installation
```python
pip install pyplatform-reporting
```

## Authentication and environment variables
Refer to [main page](https://github.com/mhadi813/pyplatform) for documentation on authentication

## Exploring the modules
```python

from pyplatform.reporting import *
show_me()
```

## Usage
### listing Tableau server datasources and reading hyper datasource into pandas dataframe
```python
from pyplatform.reporting import *

tableau_server_list_resources(resource='datasources',output_option='DICT')
datasource_name = 'sample superstore'
hyper_filepath = tableau_server_download_hyper(datasource_name)
df= hyper_to_df(hyper_filepath)

```

### uploading pandas dataframe as hyper datasource on Tableau server
```python
from pyplatform.reporting import *
# df #TODO create dataframe as source
hyper_filepath = df_to_hyper(df,filepath='Sample superstore.hyper')
datasource_name = tableau_server_upload_hyper(hyper_filepath)

```

