dftogsheet

A Python module for writing pandas DataFrame objects directly to Google Spreadsheets
dftogsheet is maintained on GitHub and PyPI.

Install dftogsheet

$ pip install dftogsheet

Setup

1. Enable the Google Sheets API.
2. Enter a name for your project. This is the name that will be displayed when your app asks for permission to edit your spreadsheets in Google Drive later.
3. Download credentials.json into project-root-folder/.dftogsheet/credentials/ folder.

Simple usage

import pandas as pd
import dftogsheet

data_frame = pd.DataFrame()
dftogsheet.write_to_sheet(data_frame, spreadsheet_id, sheet_name)

Parameters

There are three mandatory parameters for the above function:

• data_frame is any pandas DataFrame object.
• spreadsheet_id is the part of the Google Spreadsheet URL that is between /d/ and /edit.
• sheet_name is the name of the sheet within the Google spreadsheet. E.g. Sheet1.

Advanced usage

With only the above function, this library pretty much only does one thing. But there is actually a lot more flexibility provided to you if you know what's going on. Please look into the two functions in dftogsheets/__init__.py to understand what is going on under the hood when you run the above code and to understand how you can use the Sheet class and its methods more powerfully. If you have any suggestions, you are always more than welcome to contribute ;)

Changing scopes, valueInputOption, and location of credentials file

What is the valueInputOption? Read this page

These settings are actually controlled by the Config class. A new instance of the Config class with default values is created for you in dftogsheet.write_section_to_sheet so you don't have to think about it for the sample code above. However, it is possible to fully customize these configurations by creating your own config object for your project. Please look into dftogheets/config.py to understand how you can do that.

What's new in version 0.0.7

• Add Sheet.overwrite() method.
• Include this method by default.

How can I contribute?

Thanks for asking!
I appreciate everyone who contributes, no matter how you choose to do it.
And if you feel like conforming to my workflow (which I try to stick to), that's great ;)

My workflow

• Use Gitflow Workflow.
• Include GitHub issue number in feature and hotfix branch names.
• If an issue doesn't exist on GitHub, create one.
• Include branch name in every commit message, even on develop.
• Only small "one commit" fixes done directly on develop.
• Commit style: imperitive sentences in all lower case except proper nouns.
• Merge into develop using pull requests and keeping the entire commmit history.
• Merge into production squshing commits and keeping only version number in commit message.
• At some point I would like to automatically publish every release to pushed to production on PyPy.
• If you add new dependencies, don't use pip freeze > requirements.txt. Add new dependencies manually. Packages we install can install their own dependencies.