• Installation and Setup
• Emacs Setting up and configure your favourite text editor for development.
• General Concepts
• Jupyter Notebooks
• Codebraid
• Virtual Environments
• Exception Handling
• Configuration
• Logging
• Debugging
• Recursion
• Testing
• Linting
• OS Paths and Files
• Testing & Linting
• Continuous Integration
• Courses
• Packages
• Sphinx Documentation
• GUI

There are a lot of packages for Python, what you install will depend highly on what you wish to do. As I mainly do data science, statistics, automated reporting and attempt to do so in a computer science framework these are the packages that I use regularly.

My requirements.txt file can be found here. When creating a new virtual environment install all packages with…

snippet.bash

pip install -r requirements.txt

Packages can be given aliases when they are imported, some common packages have common abbreviations…

snippet.python

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

Pip doesn't have a flag to automatically upgrade everything (at least according to this thread) but a suggested solution is to…

snippet.bash

 ❱ pip list --outdated --format=json | jq -r '.[] | .name'  | xargs -n1 pip install -U

• Attributes
• Data Manipulations
• Databases
• Design Patterns
• *args and **kwargs
• Lists and Dictionaries
• I/O
• Pickling
• Profiling
• Parallel Processing
• String Manipulations
• Graphics
• GIS
• Summarising Data
• Programming
• Regular Expressions
• Dependency Injection
• Patterns
• Miscellaneous
• Requests

• Seagull a library for simulating Conways Game of Life.
• PDF to MP3 using Python
• How to Convert Speech to Text in Python - Python Code

• pathlib

• splink a tool for Fuzzy Matching and Deduplicating Hundreds of Millions of Records using Apache Spark

• altair a grammar of graphics like declarative plotting package in Python.
• bokeh for interactive plots (zooming etc.)
• cufflinks for adding sparkle to Plotly graphs.
• folium for embedding maps.
• Matplotlib base plotting.
• Plotly Making graphs fancy interactive graphs.
• plotnine a grammar of graphics for Python (viz. ggplot2 for Python)
• Seaborn preconfigured plots/themes for matplotlib

• OSRM Python interface to the Open Source Routing Machine

• jupyter_contrib_extensions.
• jupyterthemes

• dask for “big data.
• h2o for lots of statistics.
• NumPy numerical calculations.
• Pandas data frames and other such fun.
• Python-markdown
• Python Google Client
• Patsy
• Scikit-learn
• Terality
• Shapash makes Machine Learning models transparent and understandable by everyone
• Statsmodels
• Tabulate
• TensorFlow

• PyLint
• Pytest
• Flake8
• Mimesis
• Pint for standardising units and conversions thereof.
• Typical

• Codebraid Pandoc Markdown reports.
• Pweave Python equivalent of RMarkdown for producing slides/PDF/HTML output from Markdown with embedded code chunks.

• Pelican static website generator that parses Markdown.

I decided to write a library/program for managing Bandcamp.

I needed to convert GPS traces recorded by Endonmondo which exports as Garmin TPX files to the more generic GPX format for importing into OpenTrack (I'd decided I wanted more privacy whilst recording my running and cycling). I therefore wrote tpx2gpx to do this and took the opportunity to learn a bit about CD/CI (Continuous Development/Continuous Integration) on GitLab and how to release packages to PyPi.

• GitLab Repo : tpx2gpx
• PyPi : tcx2gpx

Scraping data on weather from @WPWeather a weather station in Weston Park, Sheffield.

• GitLab Repo : WPWeather
• GitLab Wiki : Weather at Weston Park

I have an Air Quality monitor outside of my house and wanted to play around with the data myself, to which end I started (but haven't yet finished) writing a package to grab the data from Luftdaten and store it in a MongoDB in their Atlas Cloud service.

• GitLab Repo : airqual

• Python
• Reticulate an R interface to Python.
• [PEP8 – Style Guide for Python Code]www.python.org/dev/peps/pep-0008/)
• PyData
• Pandas
• scikit-learn
• matplotlib
• seaborn
• ggplot2
• Python-markdown
• Best Python Resources - Full Stack Python

• NumPy
• NumPy Universal Functions
• NumPy Illustrated: The Visual Guide to NumPy

• Receiver Operating Characteristic Curves Demystified (in Python)

• Asterisks in Python: what they are and how to use them - Trey Hunner
• Hidden Features of Python
• The 35 Words You Need to Python | yawpitchroll
• Introduction to Computer Science and Programming Using Python
• Udemy : Python for Data Science and Machine Learning
• Chris Albon - Python - A lot of useful examples for Python and many other statistics/machine learning/data science topics.
• Data Analysis resources for Python
• Corey Schafer : YouTube Tutorials
• What the f*ck Python? 😱
• Courses & Articles
• Clean Architectures in Python

• Teaching a kid to code with Pygame Zero · Matt Layman

• pythonbooks.org
• Python Data Science Handbook
• The Django Book
• Hitchikers Guide to Python
• Python Tips
• Automate the Boring Stuff with Python
• Problem Solving with Algorithms and Data Structures using Python
• Legally Free Python Books List - Python kitchen

• Talk Python
• Python Podcast

• list.sort() vs. sorted(list)
• Things you're probably not using in Python 3 - but should - Data, what now? turns
• Python alternative to Docker

• Production-ready Docker images
• Python alternative to Docker · Matt Layman

• Let’s talk about data structures in Python
• Composing Programs
• Python Bindings: Calling C or C++ From Python
• Stop Using datetime.now! | Haki Benita and exposition of Dependency Injection which allows decoupling of methods/functions.

• Martin Fowler - Refactoring
• Refactoring Guru
• Refactoring with tests in Python: a practical example - The Digital Cat
• Supercharge your Python code with Factory Functions

• SOLID Principles made easy – Hacker Noon
• Enforcing Single Responsibility Principle in Python
• Clean Architecture in Python
• Clean Code concepts adapted for Python

• How accurate is scikit-learn?

• Python is eating the world: How one developer's side project became the hottest programming language on the planet

python:python programming datascience computerscience