This is my python playground which is going to serve as my portfolio.
My plan is to to add following stuff:
1. Notes for topics which i'll revise or topics which i'll be learning from scratch
2. Random code
3. Portfolio projects
4. Random Projects
5. Educational Projects
6. Conceptual Practice
Frameworks & Libraries
Python GUI / CLI Framework
- [x] Tkinter
- [ ] PyQt5
- [x] Kivy
- [ ] Beeware
- [ ] PyInstaller
- [ ] PySimpleGUI
- [ ] Typer (CLI Project)
- [ ] Rich (Terminal Output Modifier)
- [ ] Dear PyGUI
- [ ] Diagrams (System Architecture Design tool from code)
- [ ] pywin32
- [ ] wxPython
- [ ] Click
- [ ] Gooey
Web Scrapping
- [x] Scrappy
- [ ] Beautiful Soap
- [ ] Selenium
- [ ] Fabric
- [ ] PyGTK
Web Development Framework
- [x] Flask
- [x] Flask-Restful
- [x] Django
- [ ] Django-Restful
- [ ] Pyramid
- [ ] Bottle
- [ ] CherryPy
- [ ] FastAPI
- [ ] TurboGears
- [ ] Web2Py
- [ ] Dash
- [ ] Zappa
Database Manipulation and ORM Wrappers
- [ ] SqlAlchemy
- [ ] Pyscopg2 for Postgres
- [ ] Pyodbc for SQL Server
- [ ] Pymysql for MariaDB/MySQL
- [ ] fdb for Firebird
- [ ] Peewee
Game Development
- [ ] PyGame
- [ ] Pyglet
Hardware / IOT
- [ ] Robot Framework
- [ ] Pyro
- [ ] DART
- [ ] PyRobot
- [ ] PyDy
- [ ] Simulation Open Framework Architecture
- [ ] Klamp’t
- [ ] Pybotics
- [ ] Siconos
- [ ] iDynTree
- [ ] mraa
- [ ] sockets
- [ ] mysqldb
- [ ] paho-mqtt
- [ ] DeviceHive
- [ ] SiteWhere
- [ ] DAS
- [ ] MicroPython
- [ ] Azure
- [ ] AWS
- [ ] PyFirmata
- [ ] Python Twisted
File Handling and Documentation with Python
- [ ] PyFileSystem
- [ ] Python Docx
- [ ] Behold
- [ ] Black
- [ ] Invoke
- [ ] Openpyxl
- [ ] pandas
- [ ] Arrow
- [ ] poetry
- [ ] pendulum
- [ ] Nuitka
- [ ] Numba
Hands on Python Libraries
- [ ] fasttext
- [ ] core Audio
- [ ] Random
- [ ] OS
- [ ] Sys
- [ ] NLTK
- [ ] PyBorn
- [ ] NuPIC
- [ ] Pipenv
- [ ] Sympy
- [ ] Gensim
- [ ] Pillow
- [ ] iPython
- [ ] Imbalanced-learn
- [ ] loguru
- [ ] Appache libcloud
- [ ] EbookLib
- [ ] sh
Maths With Python
- [ ] Basics Maths
- [ ] Arithmetic
- [ ] Algebra
- [ ] Graphing
- [ ] Trigonometry
- [ ] Calculus
- [ ] Linear Algebra
- [ ] Equation in Markdown and LaTex
- [ ] SciPy
- [ ] Pandas
- [ ] Numpy
- [ ] Theano
- [ ] PyOD
- [ ] Stats Model
Automation with Python
- [ ] Automating Boring Stuff With Python
Testing with Python
- [ ] Pretty Errors
- [ ] Scalene (CPU and memory profiler)
- [ ] Unit Testing
- [ ] Integration Testing
- [ ] Pytest
- [ ] Nose or nose2
- [ ] tox
- [ ] Jenkins and Dockers
- [ ] OLID, KISS, DRY, YAGNI design patterns
- [ ] Doc Testing
- [ ] Selenium
- [ ] Splinter
Networking with Python
- [ ] Request
- [ ] Python Twisted
Data Science
- [ ] Pytorch Lightning
Data Visualization
- [ ] Seaborn
- [ ] D3j
- [ ] Hiplot
- [ ] Pydot
- [ ] Ploty
- [ ] Matplotlib
Machine Learning
- [ ] Hydra
- [ ] OmegaConf
- [ ] Pytorch
- [ ] Scikit-Learn
- [ ] XGBoost
- [ ] Gradio
- [ ] SciPy
- [ ] Eli5
- [ ] Light GBM
- [ ] Tensor Flow
- [ ] MILK
- [ ] Bob
- [ ] PyBrain
- [ ] SparkML
Deep Learning
- [ ] HummingBird
- [ ] Keras
- [ ] Caffe2
- [ ] Hebel
- [ ] ChainerBokeh
Computer Vision
- [ ] Norfair
- [ ] OpenCV
- [ ] SimpleCV
- [ ] Azure Cognitive Science
Other Libraries
- [ ] quart — an async web framework with Flask-compatible API. Some of the existing Flask extensions will even work!
- [ ] alibi-detect — monitor outliers and distribution drift in your production models, for tabular data, text, images and time series.
- [ ] einops — popularized in 2020, einops lets you write tensor operations for readable and reliable code, supporting numpy, PyTorch, TensorFlow, and others. Recommended by Karpathy, do you need anything else?
- [ ] stanza — accurate natural language processing tools on 60+ languages, from Stanford. Multiple available pre-trained models for different tasks.
- [ ] datasets — from HuggingFace, lightweight and extensible library to easily share and access datasets and evaluation metrics for Natural Language Processing (NLP) and more
- [ ] pytorch-forecasting — eases timeseries forecasting with neural networks for real-world cases and research alike.
- [ ] sktime — provides dedicated time series algorithms and scikit-learn compatible tools for building, tuning, and evaluating composite models. Also check their companion sktime-dl package for deep learning based models.
- [ ] netron — a visualizer for neural network, deep learning and machine learning models. Supports more formats than I even knew existed.
- [ ] pycaret — wraps several common ML libraries and makes you vastly more productive, saving you hundreds of lines of code.
- [ ] tensor-sensor — helps you get the dimensions of your tensor math right, by improving error messages and providing visualizations.
Projects
This repository will contains every chunk of code that i'll be practicing and coding for these 100 days challenge. It doesn't matter if the code was for understanding, practice or project.content for this 100 days challenge is as follows:
Beginner Python Concepts & Challenges
Content for section this is as following:
- [x] 01 Variables in Python
- [x] 02 String Manipulation
- [x] 03 Input and Print Function
- [x] 04 Variable Naming Rules
- [x] 05 Mathematical Operations
- [x] 06 DataTypes
- [x] 07 Converting Types (Type Casting)
- [x] 08 Conditional Statements (Nested)
- [x] 09 Logical Operators
- [x] 10 Randomization
- [x] 11 Error Handling (Exception Handling)
- [x] 12 Custom and Builtin Functions
- [x] 13 Iterative Statements (For loop)
- [x] 14 Code Blocks and Indentation
- [x] 15 Conditional Iteration (While Loop)
- [x] 16 Flowchart Programming
- [x] 17 Positional and Keyword Arguments
- [x] 18 Python Dictionaries and List
- [x] 19 Nested Collections
- [x] 20 Returning Functions
- [x] 21 Return vs Print
- [x] 22 Doc Strings vs Comments
- [x] 23 Scope and Local / Global Scope Variable
- [ ] 24 Debugging Techniques
Intermediate Python Concepts & Challenges
Content for this section is as follows:
- [x] 01 Local Development Environment Setup
- [x] 02 PyCharm Tips & Tricks
- [x] 03 Python Object Oriented Programming
- [x] 04 Creating Classes in Programming
- [x] 05 Using External Python Modules / importing
- [x] 06 Getting / Setting Attributes
- [x] 07 Python Methods
- [x] 08 Class Initializers
- [x] 09 Module Aliasing
- [x] 10 Optional, Required and Default Parameters
- [ ] 11 Event Listeners
- [ ] 12 Python Instances and State
- [x] 13 Python Turtle
- [ ] 14 Game Development with Python and OOP
- [x] 15 Python Inheritance
- [ ] 16 Python Slice Function
- [ ] 17 File I/O Reading and Writing to Local FIles
- [ ] 18 File Directories
- [ ] 19 Reading and Writing to CSV
- [ ] 20 Introduction to pandas framework
- [ ] 21 List Comprehensions
- [ ] 22 Dictionary Comprehensions
- [ ] 23 Packing and Unpacking Functions in Python
- [ ] 24 Creating Desktop GUI Apps with Tkinter
- [ ] 25 Strongly Dynamic Typing
- [ ] 26 Error Handling and Exceptions in Depth
- [x] 27 Try / Except / Raise
- [ ] 28 Working with JSONs
- [ ] 29 Local Persistence
- [ ] 30 Sending Email with Python SMTP
- [ ] 31 Working with date and Time
- [ ] 32 Hosting Python Code Online with PythonAnywhere
Content for this section is as follows:
- [ ] 01 APIs
- [ ] 02 Making HTTP Request with Request Module
- [ ] 03 Sending Parameters with Request Module
- [ ] 04 APIs with Authentication
- [ ] 05 Sending SMS with Python
- [ ] 06 Web Scrapping with Beautiful Soup
- [ ] 07 Browser Automation with Selenium Web Driver
- [ ] 08 Automating Tinder
- [ ] 09 Automating Twitter
- [ ] 10 Automating LinkedIn
- [ ] 11 Automating Instagram
- [ ] 12 Web Development with Flask
- [ ] 13 Command Line
- [ ] 14 Python Decorators
- [ ] 15 Templating with Jinja2
- [ ] 16 WTForms
Advance Python Concepts & Challenges
Content for this section is as follows:
- [x] 01 Build Your Own Rest API with Python
- [x] 02 Build Your Own Blog
- [x] 03 Databases with SQLite
- [ ] 04 Dataframes inspection
- [ ] 05 Data Cleaning
- [ ] 06 Sorting Values in Dataframes
- [ ] 07 Arithmetic Operations with Pandas
- [ ] 08 Creating Pivot Tables
- [ ] 09 Chaining Functions
- [ ] 10 Smoothing Time Series Data
- [ ] 11 Creating Line Charts with Matplotlib
- [ ] 12 Relational Database Schemas
- [ ] 13 Descriptive Statistics
- [ ] 14 Creating Bar Charts, Pie Charts, Donut Chart, Bo Plots with Plotly
- [ ] 15 Creating Numpy NDarrays
- [ ] 16 Array Slicing and Subsetting
- [ ] 17 Matrix Multiplication
- [ ] 18 Bitwise and Operators in Pandas
- [ ] 19 Creating Bubble Charts with Seaborne
- [ ] 20 Running Regressions with Scikit-Learn
- [ ] 21 Non-parametric Regression
- [ ] 22 Students T-Tests and Histograms with Scikit-Learn
- [ ] 23 Multi-Variable Regression
- [ ] 24 Log Transformation
- [ ] 25 Residuals Analysis
Professional Portfolio Ideas
Content for this section is as follows:
- [ ] 01 Text to Morse Code Converter
- [ ] 02 Portfolio Website
- [ ] 03 Tic Tac Toe Game
- [ ] 04 Image Watermarking App
- [ ] 05 Typing Speed Test
- [ ] 06 Breakout Game
- [ ] 07 Cafe and Wi-fi Website
- [ ] 08 Todo List Website
- [ ] 09 Disappearing Text Writing App
- [ ] 10 Image Color Palette Generator
- [ ] 11 Custom Web Scrapper
- [ ] 12 Automating the Google Dinosaur Game
- [ ] 13 Space Invader Game
- [ ] 14 Custom API Driven Website
- [ ] 15 An Online Shop
- [ ] 16 Custom Browser Automation
- [ ] 17 Analyse and Visualize the Space Race
- [ ] 18 Analyse Deaths Involving the Police in the US
- [ ] 19 Predict Earnings using Multi-variable Regression
Conceptual Practice
Content for this section is as follows:- [x] Basics
- [x] Control Structures
- [ ] Functional Programming
- [ ] Enumerators, Generators and Iterators
- [ ] File Handling
- [ ] Object Oriented programming
- [ ] Data Structures
- [ ] Algorithms
- [ ] Pickling / Unpickling
- [ ] Lambda Functions
- [x] Database