Read on Twitter
Love using Jupyter notebooks, but after a while, they look like a total mess? ๐ตโ๐ซ
What if I told you there is a quick, simple, and efficient way to make them tidy and shiny?
These 3 tips will help you keep your notebooks clean and boost your productivity ๐โ
What if I told you there is a quick, simple, and efficient way to make them tidy and shiny?
These 3 tips will help you keep your notebooks clean and boost your productivity ๐โ
Jupyter notebooks are the most popular environment to develop Machine Learning models.
They are the faster way to
โ add code
โ fix code
โ re-run code
for your Machine Learning project.
However, they quickly turn into a mess...
... unless you follow these 3 tips.
They are the faster way to
โ add code
โ fix code
โ re-run code
for your Machine Learning project.
However, they quickly turn into a mess...
... unless you follow these 3 tips.
Tip #1. Encapsulate common code as functions.
If you do not encapsulate your code, you are doomed to duplicate it.
And code duplication is both a productivity killer and an endless source of bugs.
The solution:
โ Define functionality ONCE.
โ Call it as many times as you need
If you do not encapsulate your code, you are doomed to duplicate it.
And code duplication is both a productivity killer and an endless source of bugs.
The solution:
โ Define functionality ONCE.
โ Call it as many times as you need
Tip #2. Extract common functions into a separate src/ folder
Often you have the same function defined in several notebooks. Which is, again, code duplication.
To solve this create a source code folder (aka src/) at the same level where your notebooks are...
Often you have the same function defined in several notebooks. Which is, again, code duplication.
To solve this create a source code folder (aka src/) at the same level where your notebooks are...
...and extract your functions as code in .py files.
You can group these functions into separate .py files, depending on their main functionality:
โ Plotting
โ Data transformation
โ Model training
โ Utils
Your project structure will look like this โ
You can group these functions into separate .py files, depending on their main functionality:
โ Plotting
โ Data transformation
โ Model training
โ Utils
Your project structure will look like this โ
Tip #3: Add `autoreload` magic to your Jupyter notebook.
To use your functions inside Jupyter, you need to import them.
For example:
To use your functions inside Jupyter, you need to import them.
For example:
By default, Jupyter caches all library imports, and only loads them once, unless you restart the kernel.
So when you update the .py files in src/, the changes are not picked up by Jupyter.
To solve this, you just add these 2 lines at the beginning of your notebook.
So when you update the .py files in src/, the changes are not picked up by Jupyter.
To solve this, you just add these 2 lines at the beginning of your notebook.
To sum up:
โ Reduce code duplication, by encapsulating and extracting common functionality into separate functions under src/.
โ Add autorelaod magic to your notebook, to keep it in sync with your src/ code.
And Voila!
โ Reduce code duplication, by encapsulating and extracting common functionality into separate functions under src/.
โ Add autorelaod magic to your notebook, to keep it in sync with your src/ code.
And Voila!
Wanna get more tweets like this?
โ Follow me @paulabartabajo_
Wanna help me spread the word?
โ Like/Retweet the first tweet below โโโ
โ Follow me @paulabartabajo_
Wanna help me spread the word?
โ Like/Retweet the first tweet below โโโ
https://twitter.com/1408789941040058369/status/1716515138927259926
Join 2k members to the ๐ฆ๐ฒ๐ฟ๐๐ฒ๐ฟ๐น๐ฒ๐๐ ๐ ๐ ๐๐ผ๐บ๐บ๐๐ป๐ถ๐๐ ๐ค
A Discord community of ML builders ๐ฉโ๐ป๐จ๐ฝโ๐ป focused on building ๐ฟ๐ฒ๐ฎ๐น-๐๐ผ๐ฟ๐น๐ฑ ๐ ๐ ๐ฎ๐ฝ๐ฝ๐
โโโ
serverless-ml.carrd.co
A Discord community of ML builders ๐ฉโ๐ป๐จ๐ฝโ๐ป focused on building ๐ฟ๐ฒ๐ฎ๐น-๐๐ผ๐ฟ๐น๐ฑ ๐ ๐ ๐ฎ๐ฝ๐ฝ๐
โโโ
serverless-ml.carrd.co
โข โข โข
Missing some Tweet in this thread? You can try to
force a refresh
ใ
