Tips Tricks 17 - All you need to know about decorators in python
Code generated in the video can be downloaded from here:
https://github.com/bnsreenu/python_for_microscopists
Dataset:
https://www.kaggle.com/uciml/pima-indians-diabetes-database
A decorator in python allows us to add new functionality to an existing
object (function or class) by not requiring us to modify the object's structure.
Decorators allow us to wrap another function to extend the behavior of the wrapped function, without permanently modifying it. They are typically called before defining another function that we'd like to decorate.
Functions are first-class objects in python. This means they support
the following operations.
- Stored in a variable.
- Passed as an argument to another function.
- Defined inside another function.
- Returned from another function.
- Store in data structures such as lists.
Decorators leverage this behavior of functions.
Видео Tips Tricks 17 - All you need to know about decorators in python канала DigitalSreeni
https://github.com/bnsreenu/python_for_microscopists
Dataset:
https://www.kaggle.com/uciml/pima-indians-diabetes-database
A decorator in python allows us to add new functionality to an existing
object (function or class) by not requiring us to modify the object's structure.
Decorators allow us to wrap another function to extend the behavior of the wrapped function, without permanently modifying it. They are typically called before defining another function that we'd like to decorate.
Functions are first-class objects in python. This means they support
the following operations.
- Stored in a variable.
- Passed as an argument to another function.
- Defined inside another function.
- Returned from another function.
- Store in data structures such as lists.
Decorators leverage this behavior of functions.
Видео Tips Tricks 17 - All you need to know about decorators in python канала DigitalSreeni
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
170 - AutoKeras for structured data classification using the Wisconsin breast cancer data set83 - Running your Docker in the cloudPython tips and tricks - 3: Be conservative with image augmentationWhat I am reading this week about Machine Learning and AI - 23 July 2021233 - Semantic Segmentation of BraTS2020 - Part 2 - Defining your custom data generator84 - How to build a Docker (module) with your code and run it on APEER?327 - An introduction to Single Molecule Fluorescence In Situ Hybridization (smFISH)Book Review - Deep Learning with fastai CookbookWhat I am reading this week about Machine Learning and AI - 13 August 2021326 - Cell type annotation for single cell RNA seq data65 - Image Segmentation using traditional machine learning - Part3 Feature Ranking39 - Introduction to Pandas - Grouping DataAMT1 - Extracting required information from your Outlook inbox108 - Analysis of COVID-19 data using Python - Part 2151 Warning about JPG files when working with categorical labelsGenerating borders around objects for use in semantic segmentation7 (+2) AI-powered fun and useful web applicationsMy review of the 'Automated Machine Learning with AutoKeras' book282 - IHC color separation followed by nuclei segmentation using StarDist in pythonA review of COVID19 situation in India using Python data analysis and plotting