These guides aim to understand the development and execution environment of Python. In addition, I will cover topics ranging from language fundamentals, good practices, build, deploy, distribution to advanced language programming topics.
Estes guias tem por objetivo compreender o ambiente de desenvolvimento e execucao de Python. Alem disso, vou cobrir topicos que envolvem desde os fundamentos da linguagem, boas praticas, build, deploy, distribuicao ate topicos avancados de programacao na linguagem.
How to install and set up a Python
This topic describe how to set up the environment to Python developement.
- What's is Python ?
- Zen of Python
- Types
- Interpreter and Compiler
- Complete Documentation
- Main()
- __ main __
- https://docs.python.org/3/library/index.html
- https://docs.python.org/3/reference/index.html
- https://docs.python.org/3/howto/index.html
- https://docs.python.org/3/reference/import.
- html#replacing-the-standard-import-system
- Executing modules as scripts
- Options Command
-c
command-m
module-name https://realpython.com/run-python-scripts/- Language limitations
- GIL
- Anonymous functions (lambda) -https://pt.stackoverflow.com/questions/50422/como-declarar-uma-fun%C3%A7%C3%A3o-an%C3%B4nima-no-python
- Generators
- Iterators
- Decorators
- Personal Exceptions
- Enfeites em funções
- Metaclasses
- coroutine function
- concurrent
This part of the guide focuses on sharing and deploying your Python code.
- .py
- .pyc
- .pyo
- .egg
__init__.py
- Requirements File
- Pipfile and Pipfile.lock
- Identation and Length
- Line Break After a Binary Operator
- Naming
- Encoding
- Strings
' '
and" "
- Comments
#
- Imports
- Dunders to Documentation
- Annotation Functions
- Type Hints
- String Concatenation
- String Methods
- Exception
- Return
- Type Comparisons
- Methods with numerous parameters
- Docstrings
- Class notes and exercises solved
- Teacher: Gustavo Guanabara.
Words | Themes |
---|---|
1 | Fundamentals |
2 | Control Structures |
3 | Compound Structures |
4 | Functions |
Data Engineering
Artificial Inteligence
- Computer Vision
- Machine Learning
- Deep Learning
- Network Virtualization
- Text Processing
- Natural Language Processing
- ChatOps Tools
- Image Processing
- Search
- Robotics
- Science
Databases
Security
Operation
- Date and Time
- Built-in Classes Enhancement
- Command-line Interface Development
- Command-line Tools
- Environment Management
- Files
- Networking
- Audio
- Hardware
- Video
DevOps
- Parsing
- Processes
- Concurrency and Parallelism
- Distributed Computing
- Compatibility
- Configuration
- Debugging Tools
- DevOps Tools
- Distribution
- Documentation
- Downloader
- Logging
- Job Scheduler
- Continuous Integration
Cloud
Python
- Algorithms and Design Patterns
- Code Analysis
- Code Quality
- Functional Programming
- Implementations
- Interactive Interpreter
- Package Management
- Package Repositories
- Testing
- Editor Plugins and IDEs
- Build Tools
Managemant Libraries
Web
- Admin Panels
- CMS
- Forms
- HTML Manipulation
- HTTP Clients
- News Feed
- Static Site Generator
- URL Manipulation
- Web Asset Management
- Web Content Extracting
- Web Crawling
- Web Frameworks
- WebSocket
- WSGI Servers
- Tagging
- Template Engine
Miscellaneous
Services
- How do I configure my computer to run Python code?
- How do I configure my computer to develop in Python?
- What are the best practices to prepare an environment that runs Python?
- What is a requirements.txt file ?
- How to ensure a fully reproducible (100% equal) environment ?
- How is the virtual environment Python executable able to use something different from the system site packages ?
- When use golang in place Python
On Linux, make sure you have the right version of Python pre-installed, and the basic developer toolset available. Makes sure of that:
- Install the latest version of Python.
sudo apt install python3.8
- Satisfy some system requirements
sudo apt install build-essential\
libffi-dev\
python3-pip\
python3-dev\
python3-venv \
python3-setuptools\
python3-pkg-resources
- Create and activate Python virtual environment
cd your-project
python3 -m venv venv
source venv/bin/activate
NOTE for beginners:
A Python virtual environment is a local interpreter that allows to install dependencies without polluting the global Python interpreter. There are different ways to create virtual environments (virtualenv; -m venv) and to install packages (pip install; easy_install), which may be confusing at the beginning.
- Install tools
sudo apt install git
- Vim editor (git's default editor)
sudo apt install vim
- Install Libraries used in this project
pip3 install --user od \
numpy \
pandas \
matplotlib \
virtualenv \
jupyter \
mysql-connector-python
- Check what version Python
python --version
# Python 3.6.7
If return Python2, try set a alias in file .bashrc
# Python
alias python=python3
- Check where instaled Python
which python
# /usr/bin/python
-
To individual project
PYTHONPATH
search path until module. -
To interpreter
PYTHONHOME
indicate standard libraries.
- First open profile in editor
sudo vim ~/.profile
or
sudo vim ~/.bashrc
- Insert Python PATH
export PYTHONHOME=/usr/bin/python<NUMER_VERSION>
NOTE: quit vim: ESC, :wq
- Update profile/bashrc
source ~/.bashrc
or
. ~/.bashrc
update-alternatives
symbolic links determining default commands
- Execute in terminal
sudo update-alternatives --config python
If return error: update-alternatives: error: no alternatives for python3
, following to step 2
- Install multiples Python
update-alternatives --install /usr/bin/python python /usr/bin/python<NUMER_VERSION> 1
update-alternatives --install /usr/bin/python python /usr/bin/python<OTHER_NUMER_VERSION> 2
- Change Python versions
sudo update-alternatives --config python
sudo update-alternatives --set python /usr/bin/python3.6
- Check changes
python --version
# Python 3.8
Requirements files is file containing a list of items to be installed using pip install.
- Generate file
requirements.txt
pip3 freeze > requirements.txt
or
venv/bin/pip3 freeze > requirements.txt
cat requirements # image bellow
- Visualize instaled libraries
pip3 freeze
- Install libraries in requirements
pip3 install -r requirements.txt
-r
recursive
The Python can is executed in a virtual environment with semi-isolated from system.
When Python is initiating, it analyzes the path of its binary. In a virtual environment, it's actually just a copy or Symbolic link to your system's Python binary. Next, set the sys.prefix
location which is used to locate the site-packages
(third party libraries)
Quando o Python está iniciando, ele analisa o caminho do seu binário. Em um virtual environment, na verdade, é apenas uma cópia ou Symbolic link para o binário Python do seu sistema. Em seguida, define o local sys.prefix
que é usado para localizar o site-packages
(third party libraries).
sys.prefix
points to the virtual environment directory.sys.base.prefix
points to the non-virtual environment.
Example, how keep the files in folder of virtual environment:
ll
# random.py -> /usr/lib/python3.6/random.py
# reprlib.py -> /usr/lib/python3.6/reprlib.py
# re.py -> /usr/lib/python3.6/re.py
# ...
tree
├── bin
│ ├── activate
│ ├── activate.csh
│ ├── activate.fish
│ ├── easy_install
│ ├── easy_install-3.8
│ ├── pip
│ ├── pip3
│ ├── pip3.8
│ ├── python -> python3.8
│ ├── python3 -> python3.8
│ └── python3.8 -> /Library/Frameworks/Python.framework/Versions/3.8/bin/python3.8
├── include
├── lib
│ └── python3.8
│ └── site-packages
└── pyvenv.cfg
$ virtualenv -p python3 NAME_ENVIRONMENT
(env) $
or
$ python3 -m venv NAME_ENVIRONMENT
(env) $
Execute activate script
source <DIR>/bin/activate
- Package manager:
Pipefile
- Virtual environment:
$HOME/.local/share
- Lock package:
Pipefile.lock
Using pip and requirements.txt file, have a real issue here is that the build isn’t deterministic. What I mean by that is that, given the same input (the requirements.txt file), pip doesn’t always produce the same environment.
It automatically creates and manages a virtualenv for your projects, as well as adds/removes packages from your Pipfile as you install/uninstall packages. It also generates the ever-important Pipfile.lock, which is used to produce deterministic builds.
Features:
- Deterministic builds
- Separates development and production environment libraries into a single file
Pipefile
- Automatically adds/removes packages from your
Pipfile
- Automatically create and manage a virtualenv
- Check PEP 508 requirements
- Check installed package safety
# Pipfile
[[source]]
name = "pypi"
url = "https://pypi.org/simple"
verify_ssl = true
[dev-packages]
matplotlib = "==3.1.3"
[packages]
requests = "*"
numpy = "==1.18.1"
pandas = "==1.0.1"
wget = "==3.2"
[requires]
python_version = "3.8"
platform_system = 'Linux'
# requirements.txt
requests
matplotlib==3.1.3
numpy==1.18.1
pandas==1.0.1
wget==3.2
pip3 install --user pipenv
pipenv --python 3
# Creating a virtualenv for this project…
# Pipfile: /home/campos/projects/becoming-a-expert-python/Pipfile
# Using /usr/bin/python3.8 (3.8.2) to create virtualenv…
# ⠼ Creating virtual environment...created virtual environment CPython3.8.2.final.0-64 in 256ms
# creator CPython3Posix(dest=/home/campos/.local/share/virtualenvs/becoming-a-expert-python-fmPL6zJP, clear=False, global=False)
# seeder FromAppData(download=False, pip=latest, setuptools=latest, wheel=latest, via=copy, app_data_dir=/home/campos/.local/share/virtualenv/seed-app-data/v1)
# activators BashActivator,CShellActivator,FishActivator,PowerShellActivator,PythonActivator,XonshActivator
# ✔ Successfully created virtual environment!
# Virtualenv location: /home/campos/.local/share/virtualenvs/becoming-a-expert-python-fmPL6zJP
# requirements.txt found, instead of Pipfile! Converting…
# ✔ Success!
- See where virtual environment installed
pipenv --venv
pipenv run
pipenv install flask
# or
pipenv install --dev flask
pipenv lock
# Locking [dev-packages] dependencies…
# Locking [packages] dependencies…
# ✔ Success!
- Official documentation
- Gerenciando suas dependências e ambientes python com pipenv
- How are Pipfile and Pipfile.lock used?
REFACTORING https://packaging.python.org/key_projects/#pipenv
In production ...
- distlib
- virtualenv
- eggs
- Wheel
File: Typically, a Python file is any file that contains code. Most Python files have the extension .py.
Script: A Python script is a file that you intend to execute from the command line to accomplish a task.
Module: A Python module is a file that you intend to import from within another module or a script, or from the interactive interpreter. You can read more about modules in the Python documentation.
Call unique def in file.py (python -c "import FILE_NAME; def test(requirements)"
)
sound/ Top-level package
__init__.py Initialize the sound package
formats/ Subpackage for file format conversions
__init__.py
wavread.py
wavwrite.py
aiffread.py
aiffwrite.py
auread.py
auwrite.py
...
effects/ Subpackage for sound effects
__init__.py
echo.py
surround.py
reverse.py
...
filters/ Subpackage for filters
__init__.py
equalizer.py
vocoder.py
karaoke.py
...
- The
__init__.py
files are required to make Python treat directories containing the file as packages. - File can empty
- Is good pratice
__init__
have a list with modules to import. Example:
__all__ = ["echo", "surround", "reverse"]
- So import
from sound.effects import *
call the modules: "echo", "surround", "reverse"
Import individual module:
from package import item.subitem.subsubite...
from module import name
TODO:
-
Módulos que são projetados para uso via M import * devem usar o mecanismo
__ all __
para impedir a exportação de globals -
To better support introspection Use __ all __ to switch *. E.g
__all__ = ['foo', 'Bar']
from module import *
significa que, quando você from module import *
apenas esses nomes all são importados.
EXAMPLES...
-
More details: https://stackoverflow.com/questions/44834/can-someone-explain-all-in-python and https://www.python.org/dev/peps/pep-0008/#naming-conventions
-
Examples ...
Program doesn’t run any faster when it is read from a .pyc file than when it is read from a .py file;
.pyc it's faster to loaded modules
Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!
NOTE: PEP 20
Examples:
# Converting real to integer
print 'int(3.14) =', int(3.14)
# Converting integer to real
print 'float(5) =', float(5)
# Calculation between integer and real results in real
print '5.0 / 2 + 3 = ', 5.0 / 2 + 3
# Integers in other base
print "int('20', 8) =", int('20', 8) # base 8
print "int('20', 16) =", int('20', 16) # base 16
# Operations with complex numbers
c = 3 + 4j
print 'c =', c
print 'Real Part:', c.real
print 'Imaginary Part:', c.imag
print 'Conjugate:', c.conjugate()
# int(3.14) = 3
# float(5) = 5.0
# 5.0 / 2 + 3 = 5.5
# int('20', 8) = 16
# int('20', 16) = 32
# c = (3+4j)
# Real Part: 3.0
# Imaginary Part: 4.0
# Conjugate: (3-4j)
Compiler and interpreter bytecode, write in C.
Compiler and interpreter Java bytecode, write in Java.
CPython: torna muito fácil escrever extensões C para seu código Python porque no final ele é executado por um interpretador C.
Jython:, por outro lado, torna muito fácil trabalhar com outros programas Java: você pode importar qualquer classe Java sem esforço adicional, chamando e utilizando suas classes Java de dentro de seus programas Jython.
- First, Python interpreter checks syntax (sequential)
- Compile and convert it to bytecode and directly bytecode is loaded in system memory.
- Then compiled bytecode interpreted from memory to execute it.
"Readability counts"
- 4 spaces
- Limit all line 72 characteres to docstring
- Limit all line 79 to code
- Statement of functions and flow, e.g:
# Aligned with opening delimiter.
foo = long_function_name(var_one=0.0, var_two=0.0,
var_three=0.0, var_four=0.0)
- Class Name (camelCase):
CapWords()
- Variables (snack_case):
cat_words
- Constants:
MAX_OVERFLOW
income = (gross_wages
+ taxable_interest
+ (dividends - qualified_dividends)
- ira_deduction
- student_loan_interest)
By default: UTF-8
# -*- coding: UTF-8 -*-
<code>
Single quotation marks and strings with double quotation marks are the same.
- Fisrt word need upper case.
- Comments in-line separete by 2 spaces.
x = x + 1 # Compensar borda
Following order:
- Standard library imports.
- Related third party imports. (parte de terceiros)
- Local application/library specific imports.
import argparse
import configparser
import os
import mysql.connector
import my_module
Yes:
import os
import sys
No:
import os, sys
No problems:
from subprocess import Popen, PIPE
__version__ = '0.1'
__author__ = 'Bruno Campos'
- Use
''.join()
, to concatenate 3 or more:
os.path.dirname.join(stringA + stringB + stringC + stringD)
- This optimization is fragile even in CPython. Not use:
stringA + stringB + stringC + stringD
- Use string methods instead of the string module because, String methods are always much faster.
- Use
''.startswith()
and''.endswith()
instead of string slicing to check for prefixes or suffixes.
Yes: if foo.startswith('bar'):
No: if foo[:3] == 'bar':
Limit the clausule try:
minimal code necessary.
Yes:
try:
value = collection[key]
except KeyError:
return key_not_found(key)
else:
return handle_value(value)
No:
try:
# Too broad!
return handle_value(collection[key])
except KeyError:
# Will also catch KeyError raised by handle_value()
return key_not_found(key)
- Objetivo de responder à pergunta "O que deu errado?" programaticamente, em vez de apenas afirmar que "Ocorreu um problema"
"Should explicitly state this as return None"
- Be consistent in return statements.
- Todas as instruções de retorno em uma função devem retornar uma expressão ou nenhuma delas deve.
Yes:
def foo(x):
if x >= 0:
return math.sqrt(x)
else:
return None
No:
def foo(x):
if x >= 0:
return math.sqrt(x)
- Always use
isinstance()
Yes: if isinstance(obj, int):
No: if type(obj) is type(1):
"Don’t use comments to specify a type, when you can use type annotation."
- Atua como um linter (analisador de código para mostrar erros) muito poderoso.
- O Python não atribui nenhum significado a essas anotações.
- Examples:
Method arguments and return values
def func(a: int) -> List[int]:
def hello_name(name: str) -> str:
return (f'Hello' {name}')
Declare the type of a variable (type hints)
a = SomeFunc() # type: SomeType
Isso informa que o tipo esperado do argumento de nome é str . Analogicamente, o tipo de retorno esperado é str .
def send_email(address, # type: Union[str, List[str]]
sender, # type: str
cc, # type: Optional[List[str]]
bcc, # type: Optional[List[str]]
subject='',
body=None # type: List[str]
):
"""Send an email message. Return True if successful."""
<code>
TODO
- https://medium.com/@shamir.stav_83310/the-other-great-benefit-of-python-type-annotations-896c7d077c6b
- https://www.python.org/dev/peps/pep-0484/
- https://blog.jetbrains.com/pycharm/2015/11/python-3-5-type-hinting-in-pycharm-5/
- Docstrings must have:
- Args
- Returns
- Raises
Simple Example
def say_hello(name):
"""
A simple function that says hello...
Richie style
"""
print(f"Hello {name}, is it me you're looking for?")
Example partner Google
def fetch_bigtable_rows(big_table, keys, other_silly_variable=None):
"""Fetches rows from a Bigtable.
Retrieves rows pertaining to the given keys from the Table instance
represented by big_table. Silly things may happen if
other_silly_variable is not None.
Args:
big_table: An open Bigtable Table instance.
keys: A sequence of strings representing the key of each table row
to fetch.
other_silly_variable: Another optional variable, that has a much
longer name than the other args, and which does nothing.
Returns:
A dict mapping keys to the corresponding table row data
fetched. Each row is represented as a tuple of strings. For
example:
{'Serak': ('Rigel VII', 'Preparer'),
'Zim': ('Irk', 'Invader'),
'Lrrr': ('Omicron Persei 8', 'Emperor')}
If a key from the keys argument is missing from the dictionary,
then that row was not found in the table.
Raises:
IOError: An error occurred accessing the bigtable.Table object.
"""
return None
Such a docstring becomes the __doc__
special attribute of that object.
- Simple Example
print(say_hello.__doc__)
# A simple function that says hello... Richie style
- Example partner Google
- Create manual:
man
- Is a built-in function help() that prints out the objects docstring.
>>> help(say_hello)
Help on function say_hello in module __main__:
# say_hello(name)
# A simple function that says hello... Richie style
- Docstrings must show how to use script
- Must doc:
- Usage: sintax command line
- Examples
- Arguments required and optional
"""
Example of program with many options using docopt.
Usage:
options_example.py [-hvqrf FILE PATH]
my_program tcp <host> <port> [--timeout=<seconds>]
Examples:
calculator_example.py 1 + 2 + 3 + 4 + 5
calculator_example.py 1 + 2 '*' 3 / 4 - 5 # note quotes around '*'
calculator_example.py sum 10 , 20 , 30 , 40
Arguments:
FILE input file
PATH out directory
Options:
-h --help show this help message and exit
--version show version and exit
-v --verbose print status messages
-q --quiet quiet mode
-f --force
-t, --timeout TIMEOUT set timeout TIMEOUT seconds
-a, --all List everything.
"""
from docopt import docopt
if __name__ == '__main__':
arguments = docopt(__doc__, version='1.0.0rc2')
print(arguments)
A docstring to a function or method must resume:
- behavior
- arguments required
- arguments optional
- default value of arguments
- returns
- raise Exceptions
Example
def says(self, sound=None):
"""Prints what the animals name is and what sound it makes.
If the argument `sound` isn't passed in, the default Animal
sound is used.
Parameters
----------
sound : str, optional
The sound the animal makes (default is None)
Raises
------
NotImplementedError
If no sound is set for the animal or passed in as a parameter.
"""
if self.sound is None and sound is None:
raise NotImplementedError("Silent Animals are not supported!")
out_sound = self.sound if sound is None else sound
print(self.says_str.format(name=self.name, sound=out_sound))
A docstring para uma classe deve resumir seu comportamento e listar os métodos públicos e variáveis de instância. Se a classe se destina a ser uma subclasse e possui uma interface adicional para subclasses, essa interface deve ser listada separadamente (no docstring). O construtor de classe deve ser documentado na docstring para seu método init . Os métodos individuais devem ser documentados por seus próprios docstring.
Example
class SimpleClass:
"""Class docstrings go here."""
def say_hello(self, name: str):
"""Class method docstrings go here."""
print(f'Hello {name}')
Class docstrings should contain the following information:
- A brief summary of its purpose and behavior
- Any public methods, along with a brief description
- Any class properties (attributes)
- Anything related to the interface for subclassers, if the class is intended to be subclassed
- PEP 08
- PEP 484
- PEP 257
- https://realpython.com/python-pep8/#naming-conventions
- https://pep8.org
- Style guide Google: https://github.com/google/styleguide/blob/gh-pages/pyguide.md#38-comments-and-docstrings
Methods with numerous parameters are a challenge to maintain, especially if most of them share the same datatype.
These situations usually denote the need for new objects to wrap the
numerous parameters.
- too many arguments
def add_person(birthYear: int, birthMonth: int, birthDate: int,
height: int, weight: int,
ssn: int):
'''too many arguments'''
. . .
- preferred approach
def add_person(birthdate: 'Date',
measurements: 'BodyMeasurements',
ssn: int):
'''preferred approach'''
. . .
cyclomatic complexity counts the number of decision points in a method
- Libraries
- Function print
- Types data
- Numeric systems
- libs matematics
- Conditional
- Repeatition
- Functional Programming
- Tuples
- List
- Dict
- Defining Functions
- Documentation
- Default arguments
- Packing and unpacking arguments
- Variable Scope
- Global variable
- Constants
- function recursive
- Lambda Expressions
Do global variables evil?
global variables are bad in any programming language.
However, global constants are not conceptually the same as global variables;
global constants are perfectly fine to use.
so when you need a constant you have to use a global.
- http://wiki.c2.com/?GlobalVariablesAreBad
To make code more modular, the first step is always to move all global variables into a "config" object.
I believe that a clean and (nearly) bug-free code should have functions that are as pure as possible (see pure functions). A pure function is the one that has the following conditions:
A função sempre avalia o mesmo valor de resultado, dado o (s) mesmo (s) valor (es) do argumento. O valor do resultado da função não pode depender de qualquer informação ou estado oculto que possa mudar enquanto a execução do programa prossegue ou entre diferentes execuções do programa, nem pode depender de qualquer entrada externa de dispositivos de E / S (normalmente - veja abaixo). A avaliação do resultado não causa nenhum efeito colateral observável semanticamente, como a mutação de objetos mutáveis ou a saída para dispositivos de E / S. Ter variáveis globais está violando pelo menos um dos itens acima, se não ambos, pois um código externo provavelmente pode causar resultados inesperados.
Outra definição clara de funções puras: "Função pura é uma função que toma todas as suas entradas como argumentos explícitos e produz todas as suas saídas como resultados explícitos". [1] Ter variáveis globais viola a idéia de funções puras, já que uma entrada e talvez uma das saídas (a variável global) não está sendo explicitamente dada ou retornada.
Further on that, if you consider unit-testing and the F.I.R.S.T principle (Fast tests, Independent tests, Repeatable, Self-Validating and Timely) will probably violate the Independent tests principle (which means that tests don't depend on each other).
There are ways to manage the configuration:
- Using built-in data structure
- Using external configuration file
- json
- ini
- Using environment variables
- Using dynamic loading
Use dictionary, ex:
DATABASE_CONFIG = {
'host': 'localhost',
'dbname': 'company',
'user': 'user',
'password': 'password',
'port': 3306
}
Must is file separed, how example `config.py`
The configuration values are not managed as a separate file.
- examples
- range
- Looping Techniques
- items()
- enumerate()
- zip()
- dictionaries
knights = {'gallahad': 'the pure',
'robin': 'the brave'}
for k, v in knights.items():
print(k, v)
# gallahad the pure
# robin the brave
- List
for i, v in enumerate(['tic', 'tac', 'toe']):
print(i, v)
# 0 tic
# 1 tac
# 2 toe
- Loop over two or more sequences at the same time
- Excelent tools to garant good algorith complex
questions = ['name', 'quest', 'favorite color']
answers = ['lancelot', 'the holy grail', 'blue']
for q, a in zip(questions, answers):
print('What is your {0}? It is {1}.'.format(q, a))
# What is your name? It is lancelot.
# What is your quest? It is the holy grail.
# What is your favorite color? It is blue.
TODO:
-
examples
-
Optional arguments
-
Unpacking Argument (**kwargs)
def parrot(voltage, state='a stiff', action='voom', type='Norwegian Blue'):
Accepts one required argument (voltage
) and three optional arguments (state, action, and type
)
def parrot(voltage, state='a stiff', action='voom'):
print("-- This parrot wouldn't", action, end=' ')
print("if you put", voltage, "volts through it.", end=' ')
print("E's", state, "!")
d = {"voltage": "four million",
"state": "bleedin' demised",
"action": "VOOM"}
parrot(**d)
# This parrot wouldn't VOOM if you put four million volts through it. E's bleedin' demised !
...
TODO:
+---+---+---+---+---+---+
| P | y | t | h | o | n |
+---+---+---+---+---+---+
0 1 2 3 4 5 6
-6 -5 -4 -3 -2 -1
print('The story of {0}, {1}, and {other}.'.format('Bill', 'Manfred',
other='Georg'))
# The story of Bill, Manfred, and Georg.
- o arquivo de saída padrão pode ser referenciado como
sys.stdout
- Pickle
- sqlite
- Um namespace é um mapeamento de nomes para objetos. apenas ligam nomes a objetos
- verbos para métodos e substantivos para atributos de dados
- nada no Python torna possível impor a ocultação de dados
Examples:
class MyClass:
"""A simple example class"""
i = 12345
def f(self):
return 'hello world'
- O primeiro argumento de um método é chamado self. Isso nada mais é do que uma convenção
- É útil para aumenta a legibilidade dos métodos: não há chance de confundir variáveis locais e variáveis de instância ao olhar através de um método.
class Bag:
def __init__(self):
self.data = []
def add(self, x):
self.data.append(x)
def addtwice(self, x):
self.add(x)
self.add(x)
- Each value is an object. It is stored as
object.__class__
class MyFirstClass:
"""A simple example class"""
i = 42
def func_ex(self):
print('learning Python')
if __name__ == '__main__':
object = MyFirstClass() # initialized instance
object.func_ex()
print(object.__class__)
# learning Python
# <class '__main__.MyFirstClass'>
When call for
the interpreter call iter()
The function iter()
return next object of list
sum(i*i for i in range(10)) # sum of squares
One approach for developing high quality software is to write tests for each function
The doctest module provides a tool for scanning a module and validating tests embedded in a program’s docstrings.
Isso aprimora a documentação fornecendo ao usuário um exemplo e permite que o módulo doctest verifique se o código permanece fiel à documentação:
def average(values):
"""Computes the arithmetic mean of a list of numbers.
>>> print(average([20, 30, 70]))
40.0
"""
return sum(values) / len(values)
import doctest
doctest.testmod() # automatically validate the embedded tests
...
import logging
logging.debug('Debugging information')
logging.info('Informational message')
logging.warning('Warning:config file %s not found', 'server.conf')
logging.error('Error occurred')
logging.critical('Critical error -- shutting down')
...
...
- Scrapping
- Flask (microframework)
- Django
...
...
- Numpy
- Pandas
- Matplotlib
- Skitlearn (aprendizagem supervisionada, nao supervisionada)
- TensorFlow (neural network)
A curated list of awesome Python frameworks, libraries, software and resources.
Based: https://awesome-python.com/
Libraries for administrative interfaces.
- ajenti - The admin panel your servers deserve.
- django-grappelli - A jazzy skin for the Django Admin-Interface.
- django-jet - Modern responsive template for the Django admin interface with improved functionality.
- django-suit - Alternative Django Admin-Interface (free only for Non-commercial use).
- django-xadmin - Drop-in replacement of Django admin comes with lots of goodies.
- jet-bridge - Admin panel framework for any application with nice UI (ex Jet Django)
- flask-admin - Simple and extensible administrative interface framework for Flask.
- flower - Real-time monitor and web admin for Celery.
- wooey - A Django app which creates automatic web UIs for Python scripts.
Python implementation of algorithms and design patterns.
- algorithms - Minimal examples of data structures and algorithms in Python.
- PyPattyrn - A simple yet effective library for implementing common design patterns.
- python-patterns - A collection of design patterns in Python.
- sortedcontainers - Fast, pure-Python implementation of SortedList, SortedDict, and SortedSet types.
Libraries for manipulating audio and its metadata.
- Audio
- audioread - Cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio decoding.
- dejavu - Audio fingerprinting and recognition.
- mingus - An advanced music theory and notation package with MIDI file and playback support.
- pyAudioAnalysis - Audio feature extraction, classification, segmentation and applications.
- pydub - Manipulate audio with a simple and easy high level interface.
- TimeSide - Open web audio processing framework.
- Metadata
- beets - A music library manager and MusicBrainz tagger.
- eyeD3 - A tool for working with audio files, specifically MP3 files containing ID3 metadata.
- mutagen - A Python module to handle audio metadata.
- tinytag - A library for reading music meta data of MP3, OGG, FLAC and Wave files.
Libraries for implementing authentications schemes.
- OAuth
- authlib - JavaScript Object Signing and Encryption draft implementation.
- django-allauth - Authentication app for Django that "just works."
- django-oauth-toolkit - OAuth 2 goodies for Django.
- oauthlib - A generic and thorough implementation of the OAuth request-signing logic.
- python-oauth2 - A fully tested, abstract interface to creating OAuth clients and servers.
- python-social-auth - An easy-to-setup social authentication mechanism.
- JWT
- pyjwt - JSON Web Token implementation in Python.
- python-jose - A JOSE implementation in Python.
- python-jwt - A module for generating and verifying JSON Web Tokens.
Compile software from source code.
- buildout - A build system for creating, assembling and deploying applications from multiple parts.
- PlatformIO - A console tool to build code with different development platforms.
- pybuilder - A continuous build tool written in pure Python.
- SCons - A software construction tool.
Libraries for enhancing Python built-in classes.
- dataclasses - (Python standard library) Data classes.
- attrs - Replacement for
__init__
,__eq__
,__repr__
, etc. boilerplate in class definitions. - bidict - Efficient, Pythonic bidirectional map data structures and related functionality..
- Box - Python dictionaries with advanced dot notation access.
- DottedDict - A library that provides a method of accessing lists and dicts with a dotted path notation.
Content Management Systems.
- wagtail - A Django content management system.
- django-cms - An Open source enterprise CMS based on the Django.
- feincms - One of the most advanced Content Management Systems built on Django.
- Kotti - A high-level, Pythonic web application framework built on Pyramid.
- mezzanine - A powerful, consistent, and flexible content management platform.
- plone - A CMS built on top of the open source application server Zope.
- quokka - Flexible, extensible, small CMS powered by Flask and MongoDB.
Libraries for caching data.
- beaker - A WSGI middleware for sessions and caching.
- django-cache-machine - Automatic caching and invalidation for Django models.
- django-cacheops - A slick ORM cache with automatic granular event-driven invalidation.
- dogpile.cache - dogpile.cache is next generation replacement for Beaker made by same authors.
- HermesCache - Python caching library with tag-based invalidation and dogpile effect prevention.
- pylibmc - A Python wrapper around the libmemcached interface.
- python-diskcache - SQLite and file backed cache backend with faster lookups than memcached and redis.
Libraries for chatbot development.
- errbot - The easiest and most popular chatbot to implement ChatOps.
Tools of static analysis, linters and code quality checkers. Also see awesome-static-analysis.
- Code Analysis
- coala - Language independent and easily extendable code analysis application.
- code2flow - Turn your Python and JavaScript code into DOT flowcharts.
- prospector - A tool to analyse Python code.
- pycallgraph - A library that visualises the flow (call graph) of your Python application.
- Code Linters
- flake8 - A wrapper around
pycodestyle
,pyflakes
and McCabe. - pylint - A fully customizable source code analyzer.
- pylama - A code audit tool for Python and JavaScript.
- wemake-python-styleguide - The strictest and most opinionated python linter ever.
- flake8 - A wrapper around
- Code Formatters
- Static Type Checkers, also see awesome-python-typing
- mypy - Check variable types during compile time.
- pyre-check - Performant type checking.
- Static Type Annotations Generators
- MonkeyType - A system for Python that generates static type annotations by collecting runtime types
Libraries for building command-line applications.
- Command-line Application Development
- cement - CLI Application Framework for Python.
- click - A package for creating beautiful command line interfaces in a composable way.
- cliff - A framework for creating command-line programs with multi-level commands.
- clint - Python Command-line Application Tools.
- docopt - Pythonic command line arguments parser.
- python-fire - A library for creating command line interfaces from absolutely any Python object.
- python-prompt-toolkit - A library for building powerful interactive command lines.
- Terminal Rendering
- asciimatics - A package to create full-screen text UIs (from interactive forms to ASCII animations).
- bashplotlib - Making basic plots in the terminal.
- colorama - Cross-platform colored terminal text.
- tqdm - Fast, extensible progress bar for loops and CLI.
Useful CLI-based tools for productivity.
- Productivity Tools
- cookiecutter - A command-line utility that creates projects from cookiecutters (project templates).
- doitlive - A tool for live presentations in the terminal.
- howdoi - Instant coding answers via the command line.
- PathPicker - Select files out of bash output.
- percol - Adds flavor of interactive selection to the traditional pipe concept on UNIX.
- thefuck - Correcting your previous console command.
- tmuxp - A tmux session manager.
- try - A dead simple CLI to try out python packages - it's never been easier.
- CLI Enhancements
- httpie - A command line HTTP client, a user-friendly cURL replacement.
- kube-shell - An integrated shell for working with the Kubernetes CLI.
- mycli - A Terminal Client for MySQL with AutoCompletion and Syntax Highlighting.
- pgcli - Postgres CLI with autocompletion and syntax highlighting.
- saws - A Supercharged aws-cli.
Libraries for migrating from Python 2 to 3.
- python-future - The missing compatibility layer between Python 2 and Python 3.
- python-modernize - Modernizes Python code for eventual Python 3 migration.
- six - Python 2 and 3 compatibility utilities.
Libraries for computer vision.
- OpenCV - Open Source Computer Vision Library.
- pytesseract - Another wrapper for Google Tesseract OCR.
- SimpleCV - An open source framework for building computer vision applications.
Libraries for concurrent and parallel execution. Also see awesome-asyncio.
- concurrent.futures - (Python standard library) A high-level interface for asynchronously executing callables.
- multiprocessing - (Python standard library) Process-based parallelism.
- eventlet - Asynchronous framework with WSGI support.
- gevent - A coroutine-based Python networking library that uses greenlet.
- uvloop - Ultra fast implementation of
asyncio
event loop on top oflibuv
. - scoop - Scalable Concurrent Operations in Python.
Libraries for storing and parsing configuration options.
- configobj - INI file parser with validation.
- configparser - (Python standard library) INI file parser.
- profig - Config from multiple formats with value conversion.
- python-decouple - Strict separation of settings from code.
- cryptography - A package designed to expose cryptographic primitives and recipes to Python developers.
- paramiko - The leading native Python SSHv2 protocol library.
- passlib - Secure password storage/hashing library, very high level.
- pynacl - Python binding to the Networking and Cryptography (NaCl) library.
Libraries for data analyzing.
- Blaze - NumPy and Pandas interface to Big Data.
- Open Mining - Business Intelligence (BI) in Pandas interface.
- Orange - Data mining, data visualization, analysis and machine learning through visual programming or scripts.
- Pandas - A library providing high-performance, easy-to-use data structures and data analysis tools.
- Optimus - Agile Data Science Workflows made easy with PySpark.
Libraries for validating data. Used for forms in many cases.
- Cerberus - A lightweight and extensible data validation library.
- colander - Validating and deserializing data obtained via XML, JSON, an HTML form post.
- jsonschema - An implementation of JSON Schema for Python.
- schema - A library for validating Python data structures.
- Schematics - Data Structure Validation.
- valideer - Lightweight extensible data validation and adaptation library.
- voluptuous - A Python data validation library.
Libraries for visualizing data. Also see awesome-javascript.
- Altair - Declarative statistical visualization library for Python.
- Bokeh - Interactive Web Plotting for Python.
- bqplot - Interactive Plotting Library for the Jupyter Notebook
- Dash - Built on top of Flask, React and Plotly aimed at analytical web applications.
- plotnine - A grammar of graphics for Python based on ggplot2.
- Matplotlib - A Python 2D plotting library.
- Pygal - A Python SVG Charts Creator.
- PyGraphviz - Python interface to Graphviz.
- PyQtGraph - Interactive and realtime 2D/3D/Image plotting and science/engineering widgets.
- Seaborn - Statistical data visualization using Matplotlib.
- VisPy - High-performance scientific visualization based on OpenGL.
Databases implemented in Python.
- pickleDB - A simple and lightweight key-value store for Python.
- tinydb - A tiny, document-oriented database.
- ZODB - A native object database for Python. A key-value and object graph database.
Libraries for connecting and operating databases.
- MySQL - awesome-mysql
- mysqlclient - MySQL connector with Python 3 support (mysql-python fork).
- PyMySQL - A pure Python MySQL driver compatible to mysql-python.
- PostgreSQL - awesome-postgres
- Other Relational Databases
- pymssql - A simple database interface to Microsoft SQL Server.
- SuperSQLite - A supercharged SQLite library built on top of apsw.
- NoSQL Databases
- cassandra-driver - The Python Driver for Apache Cassandra.
- happybase - A developer-friendly library for Apache HBase.
- kafka-python - The Python client for Apache Kafka.
- py2neo - A client library and toolkit for working with Neo4j.
- pymongo - The official Python client for MongoDB.
- redis-py - The Python client for Redis.
- Asynchronous Clients
- motor - The async Python driver for MongoDB.
Libraries for working with dates and times.
- Chronyk - A Python 3 library for parsing human-written times and dates.
- dateutil - Extensions to the standard Python datetime module.
- delorean - A library for clearing up the inconvenient truths that arise dealing with datetimes.
- moment - A Python library for dealing with dates/times. Inspired by Moment.js.
- Pendulum - Python datetimes made easy.
- PyTime - An easy-to-use Python module which aims to operate date/time/datetime by string.
- pytz - World timezone definitions, modern and historical. Brings the tz database into Python.
- when.py - Providing user-friendly functions to help perform common date and time actions.
- maya - Datetimes for Humans.
Libraries for debugging code.
- pdb-like Debugger
- Tracing
- lptrace - strace for Python programs.
- manhole - Debugging UNIX socket connections and present the stacktraces for all threads and an interactive prompt.
- pyringe - Debugger capable of attaching to and injecting code into Python processes.
- python-hunter - A flexible code tracing toolkit.
- Profiler
- line_profiler - Line-by-line profiling.
- memory_profiler - Monitor Memory usage of Python code.
- profiling - An interactive Python profiler.
- py-spy - A sampling profiler for Python programs. Written in Rust.
- pyflame - A ptracing profiler For Python.
- vprof - Visual Python profiler.
- Others
- icecream - Inspect variables, expressions, and program execution with a single, simple function call.
- django-debug-toolbar - Display various debug information for Django.
- django-devserver - A drop-in replacement for Django's runserver.
- flask-debugtoolbar - A port of the django-debug-toolbar to flask.
- pyelftools - Parsing and analyzing ELF files and DWARF debugging information.
Frameworks for Neural Networks and Deep Learning. Also see awesome-deep-learning.
- caffe - A fast open framework for deep learning..
- keras - A high-level neural networks library and capable of running on top of either TensorFlow or Theano.
- mxnet - A deep learning framework designed for both efficiency and flexibility.
- pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration.
- SerpentAI - Game agent framework. Use any video game as a deep learning sandbox.
- tensorflow - The most popular Deep Learning framework created by Google.
- Theano - A library for fast numerical computation.
Software and libraries for DevOps.
- ansible - A radically simple IT automation platform.
- cloudinit - A multi-distribution package that handles early initialization of a cloud instance.
- cuisine - Chef-like functionality for Fabric.
- docker-compose - Fast, isolated development environments using Docker.
- fabric - A simple, Pythonic tool for remote execution and deployment.
- fabtools - Tools for writing awesome Fabric files.
- honcho - A Python clone of Foreman, for managing Procfile-based applications.
- OpenStack - Open source software for building private and public clouds.
- pexpect - Controlling interactive programs in a pseudo-terminal like GNU expect.
- psutil - A cross-platform process and system utilities module.
- saltstack - Infrastructure automation and management system.
- supervisor - Supervisor process control system for UNIX.
Frameworks and libraries for Distributed Computing.
- Batch Processing
- PySpark - Apache Spark Python API.
- dask - A flexible parallel computing library for analytic computing.
- luigi - A module that helps you build complex pipelines of batch jobs.
- mrjob - Run MapReduce jobs on Hadoop or Amazon Web Services.
- Ray - A system for parallel and distributed Python that unifies the machine learning ecosystem.
- Stream Processing
- faust - A stream processing library, porting the ideas from Kafka Streams to Python.
- streamparse - Run Python code against real-time streams of data via Apache Storm.
Libraries to create packaged executables for release distribution.
- dh-virtualenv - Build and distribute a virtualenv as a Debian package.
- Nuitka - Compile scripts, modules, packages to an executable or extension module.
- py2app - Freezes Python scripts (Mac OS X).
- py2exe - Freezes Python scripts (Windows).
- PyInstaller - Converts Python programs into stand-alone executables (cross-platform).
- pynsist - A tool to build Windows installers, installers bundle Python itself.
Libraries for generating project documentation.
- sphinx - Python Documentation generator.
- pdoc - Epydoc replacement to auto generate API documentation for Python libraries.
- pycco - The literate-programming-style documentation generator.
Libraries for downloading.
- s3cmd - A command line tool for managing Amazon S3 and CloudFront.
- s4cmd - Super S3 command line tool, good for higher performance.
- you-get - A YouTube/Youku/Niconico video downloader written in Python 3.
- youtube-dl - A small command-line program to download videos from YouTube.
Frameworks and libraries for e-commerce and payments.
- alipay - Unofficial Alipay API for Python.
- Cartridge - A shopping cart app built using the Mezzanine.
- django-oscar - An open-source e-commerce framework for Django.
- django-shop - A Django based shop system.
- merchant - A Django app to accept payments from various payment processors.
- money -
Money
class with optional CLDR-backed locale-aware formatting and an extensible currency exchange. - python-currencies - Display money format and its filthy currencies.
- forex-python - Foreign exchange rates, Bitcoin price index and currency conversion.
- saleor - An e-commerce storefront for Django.
- shoop - An open source E-Commerce platform based on Django.
- Emacs
- elpy - Emacs Python Development Environment.
- Sublime Text
- anaconda - Anaconda turns your Sublime Text 3 in a full featured Python development IDE.
- SublimeJEDI - A Sublime Text plugin to the awesome auto-complete library Jedi.
- Vim
- jedi-vim - Vim bindings for the Jedi auto-completion library for Python.
- python-mode - An all in one plugin for turning Vim into a Python IDE.
- YouCompleteMe - Includes Jedi-based completion engine for Python.
- Visual Studio
- PTVS - Python Tools for Visual Studio.
- Visual Studio Code
- Python - The official VSCode extension with rich support for Python.
- IDE
Libraries for sending and parsing email.
- envelopes - Mailing for human beings.
- flanker - An email address and Mime parsing library.
- imbox - Python IMAP for Humans.
- inbox.py - Python SMTP Server for Humans.
- lamson - Pythonic SMTP Application Server.
- Marrow Mailer - High-performance extensible mail delivery framework.
- modoboa - A mail hosting and management platform including a modern and simplified Web UI.
- Nylas Sync Engine - Providing a RESTful API on top of a powerful email sync platform.
- yagmail - Yet another Gmail/SMTP client.
Libraries for Python version and virtual environment management.
- pyenv - Simple Python version management.
- pipenv - Python Development Workflow for Humans.
- poetry - Python dependency management and packaging made easy.
- virtualenv - A tool to create isolated Python environments.
Libraries for file manipulation and MIME type detection.
- mimetypes - (Python standard library) Map filenames to MIME types.
- path.py - A module wrapper for os.path.
- pathlib - (Python standard library) An cross-platform, object-oriented path library.
- PyFilesystem2 - Python's filesystem abstraction layer.
- python-magic - A Python interface to the libmagic file type identification library.
- Unipath - An object-oriented approach to file/directory operations.
- watchdog - API and shell utilities to monitor file system events.
Libraries for working with forms.
- Deform - Python HTML form generation library influenced by the formish form generation library.
- django-bootstrap3 - Bootstrap 3 integration with Django.
- django-bootstrap4 - Bootstrap 4 integration with Django.
- django-crispy-forms - A Django app which lets you create beautiful forms in a very elegant and DRY way.
- django-remote-forms - A platform independent Django form serializer.
- WTForms - A flexible forms validation and rendering library.
Functional Programming with Python.
- Coconut - Coconut is a variant of Python built for simple, elegant, Pythonic functional programming.
- CyToolz - Cython implementation of Toolz: High performance functional utilities.
- fn.py - Functional programming in Python: implementation of missing features to enjoy FP.
- funcy - A fancy and practical functional tools.
- Toolz - A collection of functional utilities for iterators, functions, and dictionaries.
Libraries for working with graphical user interface applications.
- curses - Built-in wrapper for ncurses used to create terminal GUI applications.
- Eel - A library for making simple Electron-like offline HTML/JS GUI apps.
- enaml - Creating beautiful user-interfaces with Declarative Syntax like QML.
- Flexx - Flexx is a pure Python toolkit for creating GUI's, that uses web technology for its rendering.
- Gooey - Turn command line programs into a full GUI application with one line.
- kivy - A library for creating NUI applications, running on Windows, Linux, Mac OS X, Android and iOS.
- pyglet - A cross-platform windowing and multimedia library for Python.
- PyGObject - Python Bindings for GLib/GObject/GIO/GTK+ (GTK+3).
- PyQt - Python bindings for the Qt cross-platform application and UI framework.
- PySimpleGUI - Wrapper for tkinter, Qt, WxPython and Remi.
- pywebview - A lightweight cross-platform native wrapper around a webview component.
- Tkinter - Tkinter is Python's de-facto standard GUI package.
- Toga - A Python native, OS native GUI toolkit.
- urwid - A library for creating terminal GUI applications with strong support for widgets, events, rich colors, etc.
- wxPython - A blending of the wxWidgets C++ class library with the Python.
Awesome game development libraries.
- Cocos2d - cocos2d is a framework for building 2D games, demos, and other graphical/interactive applications.
- Harfang3D - Python framework for 3D, VR and game development.
- Panda3D - 3D game engine developed by Disney.
- Pygame - Pygame is a set of Python modules designed for writing games.
- PyOgre - Python bindings for the Ogre 3D render engine, can be used for games, simulations, anything 3D.
- PyOpenGL - Python ctypes bindings for OpenGL and it's related APIs.
- PySDL2 - A ctypes based wrapper for the SDL2 library.
- RenPy - A Visual Novel engine.
Libraries for geocoding addresses and working with latitudes and longitudes.
- django-countries - A Django app that provides a country field for models and forms.
- GeoDjango - A world-class geographic web framework.
- GeoIP - Python API for MaxMind GeoIP Legacy Database.
- geojson - Python bindings and utilities for GeoJSON.
- geopy - Python Geocoding Toolbox.
- pygeoip - Pure Python GeoIP API.
Libraries for working with HTML and XML.
- BeautifulSoup - Providing Pythonic idioms for iterating, searching, and modifying HTML or XML.
- bleach - A whitelist-based HTML sanitization and text linkification library.
- cssutils - A CSS library for Python.
- html5lib - A standards-compliant library for parsing and serializing HTML documents and fragments.
- lxml - A very fast, easy-to-use and versatile library for handling HTML and XML.
- MarkupSafe - Implements a XML/HTML/XHTML Markup safe string for Python.
- pyquery - A jQuery-like library for parsing HTML.
- untangle - Converts XML documents to Python objects for easy access.
- WeasyPrint - A visual rendering engine for HTML and CSS that can export to PDF.
- xmldataset - Simple XML Parsing.
- xmltodict - Working with XML feel like you are working with JSON.
Libraries for working with HTTP.
- grequests - requests + gevent for asynchronous HTTP requests.
- httplib2 - Comprehensive HTTP client library.
- requests - HTTP Requests for Humans™.
- treq - Python requests like API built on top of Twisted's HTTP client.
- urllib3 - A HTTP library with thread-safe connection pooling, file post support, sanity friendly.
Libraries for programming with hardware.
- ino - Command line toolkit for working with Arduino.
- keyboard - Hook and simulate global keyboard events on Windows and Linux.
- mouse - Hook and simulate global mouse events on Windows and Linux.
- Pingo - Pingo provides a uniform API to program devices like the Raspberry Pi, pcDuino, Intel Galileo, etc.
- PyUserInput - A module for cross-platform control of the mouse and keyboard.
- scapy - A brilliant packet manipulation library.
- wifi - A Python library and command line tool for working with WiFi on Linux.
Libraries for manipulating images.
- hmap - Image histogram remapping.
- imgSeek - A project for searching a collection of images using visual similarity.
- nude.py - Nudity detection.
- pagan - Retro identicon (Avatar) generation based on input string and hash.
- pillow - Pillow is the friendly PIL fork.
- pyBarcode - Create barcodes in Python without needing PIL.
- pygram - Instagram-like image filters.
- python-qrcode - A pure Python QR Code generator.
- Quads - Computer art based on quadtrees.
- scikit-image - A Python library for (scientific) image processing.
- thumbor - A smart imaging service. It enables on-demand crop, re-sizing and flipping of images.
- wand - Python bindings for MagickWand, C API for ImageMagick.
Implementations of Python.
- CPython - Default, most widely used implementation of the Python programming language written in C.
- Cython - Optimizing Static Compiler for Python.
- CLPython - Implementation of the Python programming language written in Common Lisp.
- Grumpy - More compiler than interpreter as more powerful CPython2.7 replacement (alpha).
- IronPython - Implementation of the Python programming language written in C#.
- Jython - Implementation of Python programming language written in Java for the JVM.
- MicroPython - A lean and efficient Python programming language implementation.
- Numba - Python JIT compiler to LLVM aimed at scientific Python.
- PeachPy - x86-64 assembler embedded in Python.
- Pyjion - A JIT for Python based upon CoreCLR.
- PyPy - A very fast and compliant implementation of the Python language.
- Pyston - A Python implementation using JIT techniques.
- Stackless Python - An enhanced version of the Python programming language.
Interactive Python interpreters (REPL).
- bpython - A fancy interface to the Python interpreter.
- Jupyter Notebook (IPython) - A rich toolkit to help you make the most out of using Python interactively.
- ptpython - Advanced Python REPL built on top of the python-prompt-toolkit.
Libraries for scheduling jobs.
- APScheduler - A light but powerful in-process task scheduler that lets you schedule functions.
- django-schedule - A calendaring app for Django.
- doit - A task runner and build tool.
- gunnery - Multipurpose task execution tool for distributed systems with web-based interface.
- Joblib - A set of tools to provide lightweight pipelining in Python.
- Plan - Writing crontab file in Python like a charm.
- schedule - Python job scheduling for humans.
- Spiff - A powerful workflow engine implemented in pure Python.
- TaskFlow - A Python library that helps to make task execution easy, consistent and reliable.
- Airflow - Airflow is a platform to programmatically author, schedule and monitor workflows.
Libraries for generating and working with logs.
- Eliot - Logging for complex & distributed systems.
- logbook - Logging replacement for Python.
- logging - (Python standard library) Logging facility for Python.
- raven - Python client for Sentry, a log/error tracking, crash reporting and aggregation platform for web applications.
Libraries for Machine Learning. Also see awesome-machine-learning.
- H2O - Open Source Fast Scalable Machine Learning Platform.
- Metrics - Machine learning evaluation metrics.
- NuPIC - Numenta Platform for Intelligent Computing.
- scikit-learn - The most popular Python library for Machine Learning.
- Spark ML - Apache Spark's scalable Machine Learning library.
- vowpal_porpoise - A lightweight Python wrapper for Vowpal Wabbit.
- xgboost - A scalable, portable, and distributed gradient boosting library.
Python programming on Microsoft Windows.
- Python(x,y) - Scientific-applications-oriented Python Distribution based on Qt and Spyder.
- pythonlibs - Unofficial Windows binaries for Python extension packages.
- PythonNet - Python Integration with the .NET Common Language Runtime (CLR).
- PyWin32 - Python Extensions for Windows.
- WinPython - Portable development environment for Windows 7/8.
Useful libraries or tools that don't fit in the categories above.
- boltons - A set of pure-Python utilities.
- itsdangerous - Various helpers to pass trusted data to untrusted environments.
Libraries for working with human languages.
- General
- gensim - Topic Modeling for Humans.
- langid.py - Stand-alone language identification system.
- nltk - A leading platform for building Python programs to work with human language data.
- pattern - A web mining module for the Python.
- polyglot - Natural language pipeline supporting hundreds of languages.
- pytext - A natural language modeling framework based on PyTorch.
- PyTorch-NLP - A toolkit enabling rapid deep learning NLP prototyping for research.
- spacy - A library for industrial-strength natural language processing in Python and Cython.
- stanfordnlp - The Stanford NLP Group's official Python library, supporting 50+ languages.
- Chinese
- jieba - The most popular Chinese text segmentation library.
- pkuseg-python - A toolkit for Chinese word segmentation in various domains.
- snownlp - A library for processing Chinese text.
- funNLP - A collection of tools and datasets for Chinese NLP.
Tools and libraries for Virtual Networking and SDN (Software Defined Networking).
- mininet - A popular network emulator and API written in Python.
- pox - A Python-based SDN control applications, such as OpenFlow SDN controllers.
Libraries for networking programming.
- asyncio - (Python standard library) Asynchronous I/O, event loop, coroutines and tasks.
- pulsar - Event-driven concurrent framework for Python.
- pyzmq - A Python wrapper for the ZeroMQ message library.
- Twisted - An event-driven networking engine.
- napalm - Cross-vendor API to manipulate network devices.
Libraries for building user's activities.
- django-activity-stream - Generating generic activity streams from the actions on your site.
- Stream Framework - Building news feed and notification systems using Cassandra and Redis.
Libraries that implement Object-Relational Mapping or data mapping techniques.
- Relational Databases
- Django Models - A part of Django.
- SQLAlchemy - The Python SQL Toolkit and Object Relational Mapper.
- dataset - Store Python dicts in a database - works with SQLite, MySQL, and PostgreSQL.
- orator - The Orator ORM provides a simple yet beautiful ActiveRecord implementation.
- orm - An async ORM.
- peewee - A small, expressive ORM.
- pony - ORM that provides a generator-oriented interface to SQL.
- pydal - A pure Python Database Abstraction Layer.
- NoSQL Databases
- hot-redis - Rich Python data types for Redis.
- mongoengine - A Python Object-Document-Mapper for working with MongoDB.
- PynamoDB - A Pythonic interface for Amazon DynamoDB.
- redisco - A Python Library for Simple Models and Containers Persisted in Redis.
Libraries for package and dependency management.
- pip - The Python package and dependency manager.
- conda - Cross-platform, Python-agnostic binary package manager.
Local PyPI repository server and proxies.
- warehouse - Next generation Python Package Repository (PyPI).
- bandersnatch - PyPI mirroring tool provided by Python Packaging Authority (PyPA).
- devpi - PyPI server and packaging/testing/release tool.
- localshop - Local PyPI server (custom packages and auto-mirroring of pypi).
Libraries that allow or deny users access to data or functionality.
- django-guardian - Implementation of per object permissions for Django 1.2+
- django-rules - A tiny but powerful app providing object-level permissions to Django, without requiring a database.
Libraries for starting and communicating with OS processes.
- delegator.py - Subprocesses for Humans™ 2.0.
- sarge - Yet another wrapper for subprocess.
- sh - A full-fledged subprocess replacement for Python.
Libraries for working with event and task queues.
- celery - An asynchronous task queue/job queue based on distributed message passing.
- huey - Little multi-threaded task queue.
- mrq - Mr. Queue - A distributed worker task queue in Python using Redis & gevent.
- rq - Simple job queues for Python.
Libraries for building recommender systems.
- annoy - Approximate Nearest Neighbors in C++/Python optimized for memory usage.
- fastFM - A library for Factorization Machines.
- implicit - A fast Python implementation of collaborative filtering for implicit datasets.
- libffm - A library for Field-aware Factorization Machine (FFM).
- lightfm - A Python implementation of a number of popular recommendation algorithms.
- spotlight - Deep recommender models using PyTorch.
- Surprise - A scikit for building and analyzing recommender systems.
- tensorrec - A Recommendation Engine Framework in TensorFlow.
Libraries for developing RESTful APIs.
- Django
- django-rest-framework - A powerful and flexible toolkit to build web APIs.
- django-tastypie - Creating delicious APIs for Django apps.
- Flask
- eve - REST API framework powered by Flask, MongoDB and good intentions.
- flask-api-utils - Taking care of API representation and authentication for Flask.
- flask-api - Browsable Web APIs for Flask.
- flask-restful - Quickly building REST APIs for Flask.
- flask-restless - Generating RESTful APIs for database models defined with SQLAlchemy.
- Pyramid
- cornice - A RESTful framework for Pyramid.
- Framework agnostic
- apistar - A smart Web API framework, designed for Python 3.
- falcon - A high-performance framework for building cloud APIs and web app backends.
- hug - A Python 3 framework for cleanly exposing APIs.
- restless - Framework agnostic REST framework based on lessons learned from Tastypie.
- ripozo - Quickly creating REST/HATEOAS/Hypermedia APIs.
- sandman - Automated REST APIs for existing database-driven systems.
Libraries for robotics.
- PythonRobotics - This is a compilation of various robotics algorithms with visualizations.
- rospy - This is a library for ROS (Robot Operating System).
RPC-compatible servers.
- SimpleJSONRPCServer - This library is an implementation of the JSON-RPC specification.
- SimpleXMLRPCServer - (Python standard library) Simple XML-RPC server implementation, single-threaded.
- zeroRPC - zerorpc is a flexible RPC implementation based on ZeroMQ and MessagePack.
Libraries for scientific computing. Also see Python-for-Scientists
- astropy - A community Python library for Astronomy.
- bcbio-nextgen - Providing best-practice pipelines for fully automated high throughput sequencing analysis.
- bccb - Collection of useful code related to biological analysis.
- Biopython - Biopython is a set of freely available tools for biological computation.
- cclib - A library for parsing and interpreting the results of computational chemistry packages.
- Colour - Implementing a comprehensive number of colour theory transformations and algorithms.
- NetworkX - A high-productivity software for complex networks.
- NIPY - A collection of neuroimaging toolkits.
- NumPy - A fundamental package for scientific computing with Python.
- Open Babel - A chemical toolbox designed to speak the many languages of chemical data.
- ObsPy - A Python toolbox for seismology.
- PyDy - Short for Python Dynamics, used to assist with workflow in the modeling of dynamic motion.
- PyMC - Markov Chain Monte Carlo sampling toolkit.
- QuTiP - Quantum Toolbox in Python.
- RDKit - Cheminformatics and Machine Learning Software.
- SciPy - A Python-based ecosystem of open-source software for mathematics, science, and engineering.
- statsmodels - Statistical modeling and econometrics in Python.
- SymPy - A Python library for symbolic mathematics.
- Zipline - A Pythonic algorithmic trading library.
- SimPy - A process-based discrete-event simulation framework.
Libraries and software for indexing and performing search queries on data.
- elasticsearch-py - The official low-level Python client for Elasticsearch.
- elasticsearch-dsl-py - The official high-level Python client for Elasticsearch.
- django-haystack - Modular search for Django.
- pysolr - A lightweight Python wrapper for Apache Solr.
- whoosh - A fast, pure Python search engine library.
Libraries for serializing complex data types
- marshmallow - A lightweight library for converting complex objects to and from simple Python datatypes.
- pysimdjson - A Python bindings for simdjson.
- python-rapidjson - A Python wrapper around RapidJSON.
- ultrajson - A fast JSON decoder and encoder written in C with Python bindings.
Frameworks for developing serverless Python code.
- python-lambda - A toolkit for developing and deploying Python code in AWS Lambda.
- Zappa - A tool for deploying WSGI applications on AWS Lambda and API Gateway.
Libraries for parsing and manipulating specific text formats.
- General
- tablib - A module for Tabular Datasets in XLS, CSV, JSON, YAML.
- Office
- openpyxl - A library for reading and writing Excel 2010 xlsx/xlsm/xltx/xltm files.
- pyexcel - Providing one API for reading, manipulating and writing csv, ods, xls, xlsx and xlsm files.
- python-docx - Reads, queries and modifies Microsoft Word 2007/2008 docx files.
- python-pptx - Python library for creating and updating PowerPoint (.pptx) files.
- unoconv - Convert between any document format supported by LibreOffice/OpenOffice.
- XlsxWriter - A Python module for creating Excel .xlsx files.
- xlwings - A BSD-licensed library that makes it easy to call Python from Excel and vice versa.
- xlwt / xlrd - Writing and reading data and formatting information from Excel files.
- Markdown
- Mistune - Fastest and full featured pure Python parsers of Markdown.
- Python-Markdown - A Python implementation of John Gruber’s Markdown.
- YAML
- PyYAML - YAML implementations for Python.
- CSV
- csvkit - Utilities for converting to and working with CSV.
- Archive
- unp - A command line tool that can unpack archives easily.
Static site generator is a software that takes some text + templates as input and produces HTML files on the output.
- mkdocs - Markdown friendly documentation generator.
- pelican - Static site generator that supports Markdown and reST syntax.
- lektor - An easy to use static CMS and blog engine.
- nikola - A static website and blog generator.
Libraries for tagging items.
- django-taggit - Simple tagging for Django.
Libraries and tools for templating and lexing.
- Jinja2 - A modern and designer friendly templating language.
- Genshi - Python templating toolkit for generation of web-aware output.
- Mako - Hyperfast and lightweight templating for the Python platform.
Libraries for testing codebases and generating test data.
- Testing Frameworks
- pytest - A mature full-featured Python testing tool.
- hypothesis - Hypothesis is an advanced Quickcheck style property based testing library.
- nose2 - The successor to
nose
, based on `unittest2. - Robot Framework - A generic test automation framework.
- unittest - (Python standard library) Unit testing framework.
- Test Runners
- GUI / Web Testing
- locust - Scalable user load testing tool written in Python.
- PyAutoGUI - PyAutoGUI is a cross-platform GUI automation Python module for human beings.
- Selenium - Python bindings for Selenium WebDriver.
- sixpack - A language-agnostic A/B Testing framework.
- splinter - Open source tool for testing web applications.
- Mock
- mock - (Python standard library) A mocking and patching library.
- doublex - Powerful test doubles framework for Python.
- freezegun - Travel through time by mocking the datetime module.
- httmock - A mocking library for requests for Python 2.6+ and 3.2+.
- httpretty - HTTP request mock tool for Python.
- mocket - A socket mock framework with gevent/asyncio/SSL support.
- responses - A utility library for mocking out the requests Python library.
- VCR.py - Record and replay HTTP interactions on your tests.
- Object Factories
- factory_boy - A test fixtures replacement for Python.
- mixer - Another fixtures replacement. Supported Django, Flask, SQLAlchemy, Peewee and etc.
- model_mommy - Creating random fixtures for testing in Django.
- Code Coverage
- coverage - Code coverage measurement.
- Fake Data
Libraries for parsing and manipulating plain texts.
- General
- chardet - Python 2/3 compatible character encoding detector.
- difflib - (Python standard library) Helpers for computing deltas.
- ftfy - Makes Unicode text less broken and more consistent automagically.
- fuzzywuzzy - Fuzzy String Matching.
- Levenshtein - Fast computation of Levenshtein distance and string similarity.
- pangu.py - Paranoid text spacing.
- pyfiglet - An implementation of figlet written in Python.
- pypinyin - Convert Chinese hanzi (漢字) to pinyin (拼音).
- textdistance - Compute distance between sequences with 30+ algorithms.
- unidecode - ASCII transliterations of Unicode text.
- Slugify
- awesome-slugify - A Python slugify library that can preserve unicode.
- python-slugify - A Python slugify library that translates unicode to ASCII.
- unicode-slugify - A slugifier that generates unicode slugs with Django as a dependency.
- Unique identifiers
- Parser
- ply - Implementation of lex and yacc parsing tools for Python.
- pygments - A generic syntax highlighter.
- pyparsing - A general purpose framework for generating parsers.
- python-nameparser - Parsing human names into their individual components.
- python-phonenumbers - Parsing, formatting, storing and validating international phone numbers.
- python-user-agents - Browser user agent parser.
- sqlparse - A non-validating SQL parser.
Libraries for accessing third party services APIs. Also see List of Python API Wrappers and Libraries.
- apache-libcloud - One Python library for all clouds.
- boto3 - Python interface to Amazon Web Services.
- django-wordpress - WordPress models and views for Django.
- facebook-sdk - Facebook Platform Python SDK.
- google-api-python-client - Google APIs Client Library for Python.
- gspread - Google Spreadsheets Python API.
- twython - A Python wrapper for the Twitter API.
Libraries for parsing URLs.
- furl - A small Python library that makes parsing and manipulating URLs easy.
- purl - A simple, immutable URL class with a clean API for interrogation and manipulation.
- pyshorteners - A pure Python URL shortening lib.
- webargs - A friendly library for parsing HTTP request arguments with built-in support for popular web frameworks.
Libraries for manipulating video and GIFs.
- moviepy - A module for script-based movie editing with many formats, including animated GIFs.
- scikit-video - Video processing routines for SciPy.
WSGI-compatible web servers.
- bjoern - Asynchronous, very fast and written in C.
- gunicorn - Pre-forked, partly written in C.
- uWSGI - A project aims at developing a full stack for building hosting services, written in C.
- waitress - Multi-threaded, powers Pyramid.
- werkzeug - A WSGI utility library for Python that powers Flask and can easily be embedded into your own projects.
Tools for managing, compressing and minifying website assets.
- django-compressor - Compresses linked and inline JavaScript or CSS into a single cached file.
- django-pipeline - An asset packaging library for Django.
- django-storages - A collection of custom storage back ends for Django.
- fanstatic - Packages, optimizes, and serves static file dependencies as Python packages.
- fileconveyor - A daemon to detect and sync files to CDNs, S3 and FTP.
- flask-assets - Helps you integrate webassets into your Flask app.
- webassets - Bundles, optimizes, and manages unique cache-busting URLs for static resources.
Libraries for extracting web contents.
- html2text - Convert HTML to Markdown-formatted text.
- lassie - Web Content Retrieval for Humans.
- micawber - A small library for extracting rich content from URLs.
- newspaper - News extraction, article extraction and content curation in Python.
- python-readability - Fast Python port of arc90's readability tool.
- requests-html - Pythonic HTML Parsing for Humans.
- sumy - A module for automatic summarization of text documents and HTML pages.
- textract - Extract text from any document, Word, PowerPoint, PDFs, etc.
- toapi - Every web site provides APIs.
Libraries to automate web scraping.
- cola - A distributed crawling framework.
- feedparser - Universal feed parser.
- grab - Site scraping framework.
- MechanicalSoup - A Python library for automating interaction with websites.
- pyspider - A powerful spider system.
- robobrowser - A simple, Pythonic library for browsing the web without a standalone web browser.
- scrapy - A fast high-level screen scraping and web crawling framework.
- portia - Visual scraping for Scrapy.
Full stack web frameworks.
- Synchronous
- Asynchronous
Libraries for working with WebSocket.
- autobahn-python - WebSocket & WAMP for Python on Twisted and asyncio.
- crossbar - Open-source Unified Application Router (Websocket & WAMP for Python on Autobahn).
- django-channels - Developer-friendly asynchrony for Django.
- django-socketio - WebSockets for Django.
- WebSocket-for-Python - WebSocket client and server library for Python 2 and 3 as well as PyPy.
Online tools and APIs to simplify development.
Also see awesome-CIandCD.
- CircleCI - A CI service that can run very fast parallel testing.
- Travis CI - A popular CI service for your open source and private projects. (GitHub only)
- Vexor CI - A continuous integration tool for private apps with pay-per-minute billing model.
- Wercker - A Docker-based platform for building and deploying applications and microservices.
- Codacy - Automated Code Review to ship better code, faster.
- Codecov - Code coverage dashboard.
- CodeFactor - Automated Code Review for Git.
- Landscape - Hosted continuous Python code metrics.
- PEP 8 Speaks - GitHub integration to review code style.
- https://realpython.com/python-virtual-environments-a-primer/
- https://github.com/vinta/awesome-python/edit/master/README.md
- https://www.digitalocean.com/community/tutorials/how-to-install-python-3-and-set-up-a-programming-environment-on-ubuntu-18-04-quickstart
- https://jtemporal.com/requirements-txt/
- https://pip.pypa.io/en/stable/user_guide/
- Bruno Aurélio Rôzza de Moura Campos
This work by Bruno A. R. M. Campos is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.