df2

df2gspread

Manage Google Spreadsheets in Pandas DataFrame with Python

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Readme

==================

df2gspread

==================

Transfer data between Google Spreadsheets and Pandas DataFrame.

Description


Python library that provides possibility to transport table-data
between Google Spreadsheets and Pandas DataFrame for further
management or processing.
Can be useful in all cases, when you need to handle the data
located in Google Drive.


Status

.. list-table:: :widths: 5 6 :stub-columns: 1 :header-rows: 0

Install

Example install, using VirtualEnv:

.. code:: bash

   # install/use python virtual environment
   virtualenv ~/virtenv_scratch --no-site-packages

   # activate the virtual environment
   source ~/virtenv_scratch/bin/activate

   # upgrade pip in the new virtenv
   pip install -U pip setuptools

   # install this package in DEVELOPMENT mode
   # python setup.py develop

   # simply install
   # python setup.py install

   # or install via pip
   pip install df2gspread


Access Credentials

To allow a script to use Google Drive API we need to authenticate our self towards Google. To do so, we need to create a project, describing the tool and generate credentials. Please use your web browser and go to Google console <https://console.developers.google.com>_ and :

  • Choose "Create Project" in popup menu on the top.

  • A dialog box appears, so give your project a name and click on "Create" button.

  • On the left-side menu click on "API Manager".

  • A table of available APIs is shown. Switch "Drive API" and click on "Enable API" button. Other APIs might be switched off, for our purpose.

  • On the left-side menu click on "Credentials".

  • In section "OAuth consent screen" select your email address and give your product a name. Then click on "Save" button.

  • In section "Credentials" click on "Add credentials" and switch "OAuth 2.0 client ID".

  • A dialog box "Create Cliend ID" appears. Select "Application type" item as "Other".

  • Click on "Create" button.

  • Click on "Download JSON" icon on the right side of created "OAuth 2.0 client IDs" and store the downloaded file on your file system. Please be aware, the file contains your private credentials, so take care of the file in the same way you care of your private SSH key; i.e. move downloaded JSON file to ~/.gdrive_private.

  • Then, the first time you run it your browser window will open a google authorization request page. Approve authorization and then the credentials will work as expected.

Usage

Run df2gspread like:

.. code:: python

    from df2gspread import df2gspread as d2g
    import pandas as pd
    d = [pd.Series([1., 2., 3.], index=['a', 'b', 'c']),
        pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd'])]
    df = pd.DataFrame(d)

    # use full path to spreadsheet file
    spreadsheet = '/some/folder/New Spreadsheet'
    # or spreadsheet file id
    # spreadsheet = '1cIOgi90...'

    wks_name = 'New Sheet'

    d2g.upload(df, spreadsheet, wks_name)
    # if spreadsheet already exists, all data of provided worksheet(or first as default)
    # will be replaced with data of given DataFrame, make sure that this is what you need!

Run gspread2df like:

.. code:: python

    from df2gspread import gspread2df as g2d

    # use full path to spreadsheet file
    spreadsheet = '/some/folder/New Spreadsheet'
    # or spreadsheet file id
    # spreadsheet = '1cIOgi90...'
    wks_name = 'New Sheet'

    df = g2d.download(spreadsheet, wks_name, col_names = True, row_names = True)


Documentation

Documentation is available here <http://df2gspread.readthedocs.org/>_.

Testing

Testing is py.test based. Run with:

.. code:: bash

    py.test tests/ -v
    
Or with `coverage <https://pypi.python.org/pypi/coverage>`_:

.. code:: bash

    coverage run --source df2gspread -m py.test
    coverage report


Development

Install the supplied githooks; eg::

ln -s ~/repos/df2gspread/_githooks/commit-msg ~/repos/df2gspread/.git/hooks/commit-msg
ln -s ~/repos/df2gspread/_githooks/pre-commit ~/repos/df2gspread/.git/hooks/pre-commit

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