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Quick guide on working with Data APIs in Python
👋 Hi there 👋 all my content is free for Medium subscribers, if you are already a subscriber I just wanted to say thank you! 🎉 If not and you are considering subscribing, you can use my membership referral link, you will be supporting this and other high quality content, Thank you! ⭐️ Subscribe to Medium! ⭐️Making API requests, parsing and filtering responses is one of those cool things one can easily do in python ( and other languages ), but it can seem inaccesible when you are starting out, so here’s my attempt at a quick overview and guide to working with data APIs in Python….
In a nutshell there is some data out there you want to get or access programmatically with a python script and this process can be divided into requesting, parsing and filtering a response...A bit on terminology :API: Application Programming Interface A specification that the data provider gives you so you can access and get their data, if they don't provide one the alternative is usually web scraping which we won't cover here.Endpoint: Where to send your request, usually some url like "https://api.dataprovider"Request: The act of you asking the data provider for some data in a programmatically way, usually with some schema as part of the url: "https://api.dataprovider/IamUserX/givemedataY"Response: What you get after requesting data from an API, usually a numerical code plus a data package in JSON or other format.Parse response: Since you usually get a packet of data with response data as well as the actual data you need, parsing is necessary to extract the data.Filter response: Great you got the data you wanted, but do you need all of it ? You might need to filter to extract a subtype or range of data.
Requesting Data.
With Requests : There are basically 2 ways of requesting API data in Python, the first one is via some endpoint and a http request (usually using the popular requests library), here’s one such example :
