Photo by Joshua Reddekopp on Unsplash

Posting to Instagram using Python is really simple, and opens so many doors for automation

The two best ways to organically grow your Instagram account are engaging with the community, and frequently posting. The latter can be hard to keep up with — but thankfully, we can automate this with Python.

Step 1

Install instabot — this is a fantastic Python library for doing pretty much everything a human can do on Instagram.

pip install instabot

Step 2

Define your function

from instabot import Botdef post_to_ig(image, caption):
bot = Bot()
bot.login(username = 'your_username',
password = 'your_password')
bot.upload_photo(image, caption)

Replace the placeholders in the script above with your username and password — it goes without saying that you should…


Photo by Rajeshwar Bachu on Unsplash

Google BigQuery is a fantastic tool for SQL based analysis of data — it has powerful integration with other Google Cloud services, and even better, processing anything under 1tb a month is free. In this article, we’ll look at one approach to loading API data into your Google Cloud Project ready for analysis, visualization, or simply archiving — as well as scheduling the task, so your data is always as up to date as it can be.

The prerequisites for this are that you have a Google account and you’ve created a Google Cloud Project to organise your data. If you don’t, this is very simple to do — a quick Google search will help. We’ll also assume that you have some knowledge of Python or another coding language for extracting the API data — although this step will be very simple, and example code will be provided.

Phil Hather

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