https://github.com/tafara-n/alx-backend
Backend: With Python and JavaScript.
https://github.com/tafara-n/alx-backend
caching i18n pagination queuing-system-in-js
Last synced: 5 months ago
JSON representation
Backend: With Python and JavaScript.
- Host: GitHub
- URL: https://github.com/tafara-n/alx-backend
- Owner: Tafara-N
- Created: 2024-07-19T10:18:31.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-08-31T13:41:33.000Z (about 1 year ago)
- Last Synced: 2025-04-01T03:51:14.535Z (6 months ago)
- Topics: caching, i18n, pagination, queuing-system-in-js
- Language: Python
- Homepage:
- Size: 1020 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Backend: With Python.
## Table of Content
- [Author](#author)
- [Description](#description)
___
- [i18n](0x02-i18n/README.md)
- [Caching](0x01-caching/README.md)
- [Pagination](0x00-pagination/README.md)
- [Queuing System In JS](0x03-queuing_system_in_js/README.md)
___
# Description
1. # Pagination
# Resources
**Read or watch:**
- [REST API Design: Pagination](https://www.moesif.com/blog/technical/api-design/REST-API-Design-Filtering-Sorting-and-Pagination/#pagination)
- [HATEOAS](https://en.wikipedia.org/wiki/HATEOAS)
# Learning Objectives
At the end of this project, you are expected to be able to [explain to anyone](https://fs.blog/feynman-learning-technique/), **without the help of Google:**
How to paginate a dataset with simple page and page_size parameters
How to paginate a dataset with hypermedia metadata
How to paginate in a deletion-resilient manner
# Requirements
- All your files will be interpreted/compiled on Ubuntu 18.04 LTS using `python3` (version `3.7`)
- All your files should end with a new line
- The first line of all your files should be exactly `#!/usr/bin/env python3`
- A `README.md` file, at the root of the folder of the project, is mandatory
- Your code should use the `pycodestyle` style (version `2.5.*`)
- The length of your files will be tested using `wc`
- All your modules should have a documentation (`python3 -c 'print(__import__("my_module").__doc__)'`)
- All your functions should have a documentation (`python3 -c 'print(__import__("my_module").my_function.__doc__)'`)
- A documentation is not a simple word, it's a real sentence explaining what’s the purpose of the module, class or method (the length of it will be verified)
- All your functions and coroutines must be type-annotated.
## Setup: `Popular_Baby_Names.csv`
[use this data file](https://s3.amazonaws.com/alx-intranet.hbtn.io/uploads/misc/2020/5/7d3576d97e7560ae85135cc214ffe2b3412c51d7.csv?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIARDDGGGOUSBVO6H7D%2F20240831%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20240831T132422Z&X-Amz-Expires=86400&X-Amz-SignedHeaders=host&X-Amz-Signature=39c1481188d55cf230c19d102c107cb1e86ff30d57825eb87ea012904d226de4) for your project
___
2. # Caching
# Background Context
In this project, you learn different caching algorithms.
## Resources
**Read or watch:**
- [Cache replacement policies - FIFO](https://en.wikipedia.org/wiki/Cache_replacement_policies#First_In_First_Out_%28FIFO%29)
- [Cache replacement policies - LIFO](https://en.wikipedia.org/wiki/Cache_replacement_policies#Last_In_First_Out_%28LIFO%29)
- [Cache replacement policies - LRU](https://en.wikipedia.org/wiki/Cache_replacement_policies#Least_Recently_Used_%28LRU%29)
- [Cache replacement policies - MRU](https://en.wikipedia.org/wiki/Cache_replacement_policies#Most_Recently_Used_%28MRU%29)
- [Cache replacement policies - LFU](https://en.wikipedia.org/wiki/Cache_replacement_policies#Least-Frequently_Used_%28LFU%29)
# Learning Objectives
At the end of this project, you are expected to be able to [explain to anyone](https://fs.blog/feynman-learning-technique/), **without the help of Google:**
## General
- What a caching system is
- What FIFO means
- What LIFO means
- What LRU means
- What MRU means
- What LFU means
- What the purpose of a caching system
- What limits a caching system have
# More Info
**Parent class BaseCaching**
All your classes must inherit from `BaseCaching` defined below
```bash
$ cat base_caching.py
#!/usr/bin/python3
"""
BaseCaching module
"""
class BaseCaching():
""" BaseCaching defines:
- constants of your caching system
- where your data are stored (in a dictionary)
"""
MAX_ITEMS = 4
def __init__(self):
""" Initiliaze
"""
self.cache_data = {}
def print_cache(self):
""" Print the cache
"""
print("Current cache:")
for key in sorted(self.cache_data.keys()):
print("{}: {}".format(key, self.cache_data.get(key)))
def put(self, key, item):
""" Add an item in the cache
"""
raise NotImplementedError("put must be implemented in your cache class")
def get(self, key):
""" Get an item by key
"""
raise NotImplementedError("get must be implemented in your cache class")
```
___
3. # i18n
# Resources
**Read or watch:**
- [Flask-Babel](https://web.archive.org/web/20201111174034/https://flask-babel.tkte.ch/)
- [Flask i18n tutorial](https://blog.miguelgrinberg.com/post/the-flask-mega-tutorial-part-xiii-i18n-and-l10n)
- [pytz](https://pypi.org/project/pytz/)
# Learning Objectives
- Learn how to parametrize Flask templates to display different languages
- Learn how to infer the correct locale based on URL parameters, user settings or request headers
- Learn how to localize timestamps
# Requirements
- All your files will be interpreted/compiled on Ubuntu 18.04 LTS using `python3` (version `3.7`)
- All your files should end with a new line
- A `README.md` file, at the root of the folder of the project, is mandatory
- Your code should use the `pycodestyle` style (version `2.5`)
- The first line of all your files should be exactly `#!/usr/bin/env python3`
- All your `*.py` files should be executable
- All your modules should have a documentation (`python3 -c 'print(__import__("my_module").__doc__)'`)
- All your classes should have a documentation (`python3 -c 'print(__import__("my_module").MyClass.__doc__)'`)
- All your functions and methods should have a documentation (`python3 -c 'print(__import__("my_module").my_function.__doc__)'` and `python3 -c 'print(__import__("my_module").MyClass.my_function.__doc__)'`)
- A documentation is not a simple word, it’s a real sentence explaining what’s the purpose of the module, class or method (the length of it will be verified)
- All your functions and coroutines must be type-annotated.
## Author
**Tafara Nyamhunga - [Github](https://github.com/tafara-n) / [Twitter](https://twitter.com/tafaranyamhunga)**