Python Reference Outline - Learn Python Faster

Outline and Guide to Python Reference Material

Beginner

This Python reference simplifies official documentation found at python.org for beginner to intermediate programmers who have yet to memorize the language.

What makes it unique is that rather than dumping a list of things to learn, we prioritize them High, Mid and Low, so you know where to concentrate your efforts.

This repository will be supplemented over time with in-depth explorations of modules beyond those built-in to Python.

Outline: Python Reference

The Reference is broken into four sections and roughly follows a similar structure to the official Python.org documentation under The Python Standard Library but this offers a softer introduction for beginners. Some effort was made to add priorities so beginners know where to focus their energies.

General Lists - Reference lists that apply across the whole language.
Data Types - Built-in data types.
Modules - Modules included in The Standard Library that must be imported.
Third-Party Modules - Third-party modules not included in the Standard Library requiring installation through pip3 or other methods.

1. General Lists that Apply Across the Python Language

Optimized for HTML5, web pages open in the current browser window.

Resources within The Python Standard Library
Name	Link	Description
Python Help		Helpful resources to learn Python 3
Python Keywords		The 33 Python keywords and built-in constants
Python Operators		Python operators: math, assignment, Boolean, bitwise
Python Built-in Functions		The 68 functions built-in to Python
Python Importing		The structure and instructions for importing modules
Python Indexing		Instructions for indexing and slicing Python sequences
Python Symbols		The 57 character combinations with special meaning

2. Python Built-in Data Types

Every Python installation comes with a list of built-in data types. Given that some are more advanced than others, we categorize those beginners typically learn first in the column labeled Priority.

Built-in Data Types within The Python Standard Library
Name	Category	Priority	Description
Integers	Numeric	High	Integers `int()`
Floats	Numeric	High	Floating point numbers `float()`
Complex	Numeric	Low	Complex numbers `complex()`
List	Sequence	High	Lists `list()`
Tuple	Sequence	Mid	Tuples `tuple()`
Range	Sequence	High	Range `range()`
Strings	Sequence	High	Text string `str()`
Bytes	Sequence	High	Bytes `bytes()`
Byte Array	Sequence	Low	Byte Array `bytearray()`
Memory View	Sequence	Low	Memory View `memoryview()`
Set	Set	Mid	Set `set()`
Frozen set	Set	Low	Frozen set `frozenset()`
Dictionary	Map	High	Dictionary `dict()`
Function	Code block	High	Function `def`
Class	Code block	High	Class `class`
Try Except	Exceptions	Mid	Try Except `try`

Beginners are encouraged to learn the data types characterized as High first.

3. Modules Included in The Python Standard Library

There are over 100 modules in The Python Standard Library. The table below provides an abbreviated list of important ones used at the beginner and intermediate level.

Modules Included with The Standard Python Library
Name	Category	Priority	Description
String	Text	Mid	String operations `string`
Regular Expressions	Text	Mid	Regular Expressions `re`
Readline	Text	Mid	Readline `readline`
Datetime	Data Types	Mid	Dates and times `datetime`
Calendar	Data Types	Mid	Calendar `calendar`
Copy	Data Types	Mid	Copy `copy`
Pretty Print	Data Types	Mid	Pretty Print `pprint`
Math	Math	Mid	Mathematical functions `math`
Random	Math	Mid	Random number generator `random`
Statistics	Math	Mid	Statistical functions `statistics`
OS Path	Files and Directories	High	File pathname functions `os.path`
Glob	Files and Directories	Mid	Linux-style path expansion `glob`
Pickle	Data Persistence	Mid	Saving objects `pickle`
SQLite database	Data Persistence	Mid	SQLLite 3 database `sqlite3`
Gzip Files	Data Compression	Mid	File compression `gzip`
Zip Files	Data Compression	Mid	File compression `zipfile`
Tar Archive Files	Data Compression	Mid	File compression `tarfile`
CSV Fils	File Formats	Mid	Spreadsheet-like tabular data `csv`
OS	Operating System	Mid	Operating system interface `os`
Input Output	Operating System	Mid	Input / Output tools `io`
Scheduler	Concurrent Execution	Mid	Event scheduler `sched`
JSON	Internet Data Handling	Mid	Read and write JSON `json`
HTML	Structured Markup Languages	High	Replace HTML entities `html`
HTML Parser	Structured Markup Languages	Mid	Process and parse `html.parser`
HTML Entities	Structured Markup Languages	Mid	List of HTML entities `html.entities`
XML	Structured Markup Languages	Mid	Process and parse `xml`
Web browser	Internet Protocols	High	Control a web browser `webbrowser`
URL handlers	Internet Protocols	Mid	URL programming `urllib`
Pydoc documentation	Development Tools	Mid	Generate documetation `pydoc`
Virtual environment	Software Packaging and Distribution	Mid	Create virtual environments `venv`
System	Runtime Services	Mid	System parameters and functions `sys`
Builtins	Runtime Services	Mid	Built-in objects `builtins`
Main	Runtime Services	Mid	Top-level scripting `__main__`
Inspect	Runtime Services	Mid	Inspect live objects `inspect`
Importlib	Importing Modules	Mid	Importing modules `importlib`

Reach us on social media to request a reference on a specific Python module in this section.

4. Third-Party Modules

Third-party modules are found outside The Python Standard Library and are typically imported using pip3. As third-party modules, documentation is found at sites other than Python.org. Download information can be found at https://pypi.org.

The following are domain-specific modules explored elsewhere at FactorPad specific to applications of Data Analysis.

Third-Party Modules
Name	Category	Priority	Description
Jinja2	Web Development	Mid	Create HTML templates `Jinja2`
Matplotlib	Data Analytics	Mid	Plotting and graphics `matplotlib`
Numpy	Data Analytics	Mid	Numerical array processing `numpy`
Pandas	Data Analytics	Mid	Data structures `pandas`
Requests	Internet Protocols	Mid	Make HTTP calls `requests`
Scipy	Data Analytics	Mid	Scientific Library `scipy`

Python Reference Outline: A Tool for Learning Python Faster