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Pydantic Introduction - Models, Fields, Constrained Types, Validator Functions and Model Exports
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- čas přidán 5. 08. 2024
- In this video, we dive into the Pydantic library in Python. This is based on the following blog post:
www.bugbytes.io/posts/introdu...
We'll learn a number of things, including:
1. How to define Pydantic model classes and fields with type-annotations.
2. How to define Optional fields and constrained fields
3. How to work with complex Python types such as UUID, Enum and date objects
4. How to define a custom validator function for a field on the model
5. How to export models to JSON and Python dictionaries
Github data: github.com/bugbytes-io/datasets
📌 𝗖𝗵𝗮𝗽𝘁𝗲𝗿𝘀:
00:00 Intro
01:13 Analysis of the structure of the data to model
02:47 Installing Pydantic and Requests packages
04:02 Defining Pydantic model class
06:22 Creating Optional fields on the Pydantic model
11:09 Constrained fields in Pydantic
15:23 Using custom validator functions in Pydantic
19:54 Using Enums as types in Pydantic models
22:22 Exporting Pydantic models to dictionaries and JSON
☕️ 𝗕𝘂𝘆 𝗺𝗲 𝗮 𝗰𝗼𝗳𝗳𝗲𝗲:
To support the channel and encourage new videos, please consider buying me a coffee here:
ko-fi.com/bugbytes
▶️ Full Playlist:
• Pydantic
𝗦𝗼𝗰𝗶𝗮𝗹 𝗠𝗲𝗱𝗶𝗮:
📖 Blog: www.bugbytes.io/posts/introdu...
👾 Github: github.com/bugbytes-io/datasets
🐦 Twitter: / bugbytesio
📚 𝗙𝘂𝗿𝘁𝗵𝗲𝗿 𝗿𝗲𝗮𝗱𝗶𝗻𝗴 𝗮𝗻𝗱 𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻:
Pydantic Blog post: www.bugbytes.io/posts/introdu...
Github Dataset: github.com/bugbytes-io/datasets
Pydantic Models: docs.pydantic.dev/usage/models/
Pydantic Validators: docs.pydantic.dev/usage/valid...
#python #pydantic #datascience
Awesome introduction to Pydantic. Will be grateful if you plan a video for Pydantic V2
Btw, a way to display the JSON response in a much more readable way is to use the 'pprint()' function from the pprint module. Simply using pprint(response.json()) rather than print(response.json()) will give you a more legible rendering of your json response.
I find it super helpful when parsing through deeply nested JSON.
Great video, perfect timing, working on a Django-Ninja project. Really look forward to your content.
Thanks a lot Rob, and thanks for your support.
Pydantic underpins a lot of good up-and-coming Python stuff - good to get to grips with the fundamentals! Thanks again
My new favorite Python channel. Job well done !
I really look forward to your videos. Thanks a lot
Thanks very much! Appreciate it!
You are an absolute legend. Truly, between this and your playlists on Django/HTMX, you have saved me from many a headache. Cheers, man.
Thanks very much! Greatly appreciated - cheers :)
@@bugbytes3923can we use pydanric with django?
This is a great video. Thank you very much. Im working on a project using pydantic library.
Thank you! All the best with your project, hope this helped.
great pacing and completeness - thx!
Thanks a lot!
That's a great video. I code with javascript and I wanna learn python for web. 👍
Thanks a lot!
Thank you. Subscribed!
Thanks a lot!
Great content!! Thank you!!
Thank you very much! Much appreciated.
Great tutorial. Thank you very much
Thanks for watching!
Your tutorial save me from several headaches. Thanks for this I appreciate it 😎
Thanks a lot, glad it was helpful!
This is awesome. You make me love Python more than usual. Much obliged.
Thanks a lot!
Big bro we need on Pydantic V2
When BaseModel is implemented in the same file, it works. But, if you define BaseModel in different file and import it, it raises Redundant Cyclic UHE
Excellent, thanks !
Please, could you show how use websockets with HTMX and FastAPI ???
Thanks for watching! WebSockets and FastAPI would be an interesting one (with some HTMX too). Will definitely add to the list.
@@bugbytes3923 One basic video on using it in isolation, then a second layering it into Django.
👍
Thank you!
Do you think it's a good idea to use Models, Fields and Constrained Types for an ETL (extract, transform and load) process in Data Engineering?
Interesting question. I can definitely imagine Pydantic helping with the transform part of the ETL process. After extracting your data from various sources, you could define validation and transformations with Pydantic - that would be a cool example. That could even be hooked up with something like Apache Airflow.
@@bugbytes3923what is apache airflow 😂
A lot of this functionality is already in Django, which you have videos on. Why use Pydantic when Django has this built in?
Pydantic is used with other frameworks such as FastAPI. It can be used in any Python context where you are validating data from an external source, which is very useful.
You would not, for example, create a Django app just to validate data. There are different tools that are good for different contexts!
The channel has a focus on Django at the moment, and that will be the main thing, but there are other tools that I'd like to explore on here, too.
Sir make a video on django sub query please
I have an ORM series I'm working on now, hoping to start releasing videos soon. Subqueries will be part of this series.
@@bugbytes3923 thnx Sir i am waiting