Learn about production grade API development. This is the first of two sessions.
| Delivery Mode | Online |
| Duration | 2 hours |
| Prerequisites | None |
| Includes Hands-On Session | Yes |
Target Audience
This session is suitable for:
- Cloud/Infra Engineers
- Data Analysts
- Data Engineers
- Data Scientists
- Machine Learning Engineers
- Software Development Engineers
- University students with an interest in Data Engineering, Software Development
What Will Be Covered
In this session, you will,
- Get an overview of popular frameworks (such as Flask, FastAPI) used to develop RESTful APIs.
- Get an overview of Pydantic and how it can help with API development.
- Learn how to write unit tests to improve reliability of code developed.
- Gain experience on a few ways to identify and speed up slow (inefficient) Python code.
- Learn about various ways to deploy your API on to the cloud.
- Get an overview of alternatives to REST APIs.
What This Session Will Not Cover
As this session is for learners who may or may not have had experience deploying APIs into production, part 1 of this series of sessions aims to give a broad overview.
The topics indicated with a ❌ will not be covered, whereas topics with a 👉 will be covered in subsequent parts in this series of sessions or other sessions.
- ❌ Deploying and managing containerized applications with Kubernetes
- 👉 Details of alternatives to REST APIs (refer to Part 2)
- 👉 Authentication using JWT (refer to Part 2)
- 👉 Rate Limiting (refer to Part 2)
- 👉 Profiling Python code (refer to Part 2)
Frequently Asked Questions
A few frequently asked questions regarding what will be covered during this session.
- What are RESTful APIs? RESTful APIs allows different servers to securely exchange information over the internet. ‘REST’ is an acronym for Representational State Transfer. REST is a software architecture that defines how applications communicate with each other over the internet using resources, representations, and HTTP methods.
- What is Unit Testing? Unit Testing allows testing of individual units or components of a software. The purpose is to validate that each unit of the software code performs as expected. Unit Testing is done during the development (coding phase) of an application by the developers.
- What is Pydantic? Pydantic is a Python library for data modelling/parsing and validation. It has efficient error handling and a custom validation mechanism.
Upcoming Sessions
| When | Where | |||
|---|---|---|---|---|
| Wednesday, 07 Feb 2024 | 9 - 11 PM 🌏 | Online | Register | |
| Wednesday, 06 Mar 2024 | 9 - 11 PM 🌏 | Online | Register |
Please note:
- All times above are expressed in SGT. Click on the 🌏 icon next to sessions of interest to get your location’s corresponding date and time.
- For reference, 9 PM SGT is 6:30 PM (Bangalore), 8 PM (Jakarta), 6 PM (Lahore)
Other Dates & Times
👋 I am interested but don’t see a date or time that works for me.
You can indicate your preferred date & time when you register.
What’s Next?
What should I learn after attending this session?
Tracks
This session covers content that is part of the following tracks:
Full List
- Check out the complete list of upcoming sessions.
- Alternatively, if you are a hands-on creator, check out the upcoming Hands-On Learning Sessions.
Further Reading
- What is a REST API? (Oct, 2020) 🎥 9m 11s
- What is Unit Testing? 🎥 10m 42s
- Getting started with pytest (Jan, 2023) 🎥 13m 18s
- Pydantic Tutorial (Sep, 2023) 🎥 11m 06s
- Pydantic is all you need (Nov, 2023) 🎥 17m 54s
- Cloud Run QuickStart - Docker to Serverless (Apr, 2019) 🎥 7m 49s
- Deploy FastAPI project with Cloud Run (Apr, 2023) 🎥 5m 25s
- 11+ Ways To Speedup Python Loops (Dec, 2023) 📰 13m