Can Python integrate with Google Sheets?

This guide shows how to build data-driven web applications by building upon Google Sheets and Python.

Why Python? There are plenty of programming languages you could use to write an API and a website, so why did I choose Python and how might that play into this guide? The answer is simple: it takes less time to implement and I can't wait for my clients to find out I wrote Python! This is also a project about writing something more than your average website or web app. There are so many features in Python 3. If you are reading this today, you may already be working with Python, and Python is one of the most used languages on the web.

Why Google Sheets? Google Sheets is an incredibly useful piece of software. I've written more than a few scripts with it in the past and have had many conversations with it. It's a simple and powerful tool for getting data from a range of websites and storing it to suit our needs, so let's build with that in mind.

The Script. So now we have a choice. Go old school, like me, and use XML, but I'm really into making things easy and want to stick with a more popular approach; I've built my own APIs before so I decided to make the script and API use a modern database management system like SQLite. SQLite makes it easy for APIs and websites to use and store data. Here is the full script and API script included.

If you are feeling more comfortable using MySQL or PostgreSQL (or any other database with Python), you will need to figure it out yourself; this example uses SQLite as SQLite makes it easy to run scripts and programs in the command line on whatever computer you wish to use. You could also just change the SQLite import to include your chosen database. You do not need to understand how to code APIs; once you have a database in place you only need to call the functions of the script. The API code should work with a wide range of APIs.

I also highly recommend you spend some time learning about APIs and read documentation so you can become familiar with the language syntax and terminology.

How do I convert JSON to Google Sheets?

JSON to Google Sheets is pretty straight forward: Open a new sheet in your Google Docs.

Click "Insert", then "From other sources". Select "Import from URL" and put the following URL into the "URL box". Click "Send URL". You'll get back a list of the fields in the JSON. Click "Import JSON". In the popup you should have a spreadsheet with a few rows with "Id", "Name" and "URL" data. How do I convert CSV to Google Sheets? Converting CSV files to Google Sheets is similar: In the popup you should have a list of the fields in the CSV. Click "Import CSV". Select your CSV file in the popup and click "Import". You'll get back a spreadsheet with the columns from the CSV file. What do I use to convert JSON or CSV to Google Sheets? Google Sheets provides a couple of ways to get the data from your JSON or CSV files: Using Spreadsheet Import. Use Spreadsheet Import to import data from a file that matches a format recognized by Google Sheets.

How do I export data from Python to Google Sheets?

Is it best to import/write data, then export?

Import pandas as pd. Df = pd.readexcel(r"path/file.xlsx") # Import the file containing your data.
# write result to .csv/.xls

Does this seem sensible/doable? If so, what is the best way of doing it - from an academic standpoint (ie what is the 'best' practice)? I've tried both options in the following script (where: A1 contains a list of strings, A2 some text data): df = pd.readexcel(r"path/file.xlsx")
# Write to .csv df.tocsv("test.csv", encoding="utf-8", index=False)
# Write to Google Sheets. Df.toexcel(writer=None, index=False) # df.toexcel(None, "test.xlsx") # Not working here (tried in vain)
.and, based on the comments: # Export to .tocsv("test.csv", encoding="utf-8", index=False)
# Export to Google Sheets. Df.toexcel(writer=None, index=False) It will be possible in PyCharm 2023.1 EAP due to Project IntelliJ's integration with SpreadsheetApp. You can see their progress report here.