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- 파이참, 파이썬 강좌가 필요없는 튜토리얼 활용법!
- 상대경로와 PyCharm 그리고 명령행
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- heatmap.py
- Python script for generating high quality heatmaps based on any coordinate data (GPS tracks, eye tracking, etc). http://www.sethoscope.net/heatmap
- Example python to perform GeoIP lookups for a list of IP addresses and then generate heatmap using http://www.sethoscope.net/heatmap
- GeoIP를 이용한 IP정보 활용(GeoIP + Matploitlib)
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- Basic method chaining
- bit manipulation
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'{0:b}'.format(num)==bin(num)[2:]to make binary number string
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- 파이썬과 양자 컴퓨팅 — 제 2장에서 원리 파악이 시작된다
- 파이썬과 양자 컴퓨팅 — 제 3장에서 자료 수집과 실전 테스트에 힘쓴다
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- How to Make Histograms in Pure Python
- Super quick Python automation ideas
- 15 Python Projects in Under 15 Minutes (Code Included)
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- Minimizing context switching between shell and Python
- keystroke practice
- 한글깨기.py
- 한글깨기.py & Enyg.py (은는이가.py)
- 한글과 관련된 여러가지 기능을 포함한 Python 라이브러리
- 파이썬으로 한/글 문서비교 툴 구현해보기(1/2)
- awesome-hangul#python
- hangul-toolkit - 한글 자모 분해, 조합(오토마타), 조사 붙이기, 초/중/종 분해조합, 한글/한자/영문 여부 체크 등을 지원
- hangul-utils - An integrated library for Korean language preprocessing
- jamos_separator.py 한글 자모 분리
- jamotools
- langdetect - Port of Google's language-detection library (version from 03/03/2014) to Python
- py-hanspell - 파이썬 한글 맞춤법 검사 라이브러리. (네이버 맞춤법 검사기 사용)
- Python for Android Tutorial #1 - Using the Accelerometer
- Kivy
- kivy.org/planet
- Python on Android
- Introduction to Kivy
- Developing Python based Android Apps Using Kivy
- Kivy with Python tutorial for Mobile Application Development Part 1
- Kivy - Mobile and Desktop App Dev w/ Python
- KivyAndroidClassification
- Running NumPy in Android Devices using the Kivy Python Framework
- NumPyCNNAndroid - This project builds Convolutional Neural Network (CNN) for Android using Kivy and NumPy
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Advanced Python Features generator, collections, itertools, (un)packing, decorator, lru_cache, context manager
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Records, Structs, and Data Transfer Objects in Python
dict,tuple, custom class,collections.namedtuple,typing.NamedTuple,struct.Struct,types.SimpleNamespace
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Experienced python programmers: are there any standard features of the language that you still don't regularly use? 파이썬의 다양한 언어적 기능
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What Is Elegant Code? (aka Elegant Solutions For Everyday Python Problems) dunder, custom iterator, functool.partial, contextmanager, closure, wraps/wrapt
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Solve Your Problem With Sloppy Python os, subprocess, ...
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7 More Tricks to Write Better Python Code
- Inline if-else statements, Sequence comparisons, Extended unpacking (Python-3 only), Dict comprehensions, collections.OrderedDict, collections.defaultdict, collections.Counter
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I Thought I Was Mastering Python Until I Discovered These Tricks
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Road to become a Python Ninja — Data Structures 기본 data structure
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Iterables vs. Iterators vs. Generators 서로의 관계를 그림과 함께 잘 설명
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Python — From Intermediate to Superhero list comprehension, lambda, map, filter, reduce, locals, globals, context manager, decorator, generator
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Performant Python tuple, generator, slotted class, namedtuple, map, filter, comprehension에 대한 테스트
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3 easy and noninvasive Ways to instantly boost your Python Code Performance
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- pymotw.com/3/argparse
- Comparing Python Command-Line Parsing Libraries - Argparse, Docopt, and Click
- Get selected subcommand with argparse
set_defaults를 사용해 어떤 sub command를 사용한지 구분 - 파이썬으로 만드는 나만의 커맨드라인 프로그램 #1 - argparse setup.py로 설치까지
- 파이썬으로 만드는 나만의 커맨드라인 프로그램 #2 - click setup.py로 설치까지
- Learn Enough Python to be Useful: argparse
-
argument
-
ast
-
asterisk
-
byte
-
cgitb
- cgitb로 자세한 오류를 찍어 봅니다 debugging
-
class
- practice -
RecursionError: maximum recursion depth exceeded while calling a Python object - Python’s objects and classes — a visual guide
- 클래스 구조 이해하기
- Run-time method patching in Python
- Python - 잘못된 클래스 변수의 사용
- Enriching Your Python Classes With Dunder (Magic, Special) Methods
- What’s in a (Python’s) name?
- Python 과 Mixin
- Start Writing More Classes
- Stop Writing Classes
- The controller pattern is awful (and other OO heresy)
- Raymond Hettinger - Super considered super! - PyCon 2015
__exit__must accept 3 arguments: type, value, traceback- A brief tour of Python 3.7 data classes
- Dynamically create a type with Python
- PYTHON Special methods - Customizing class creation
- Python's Instance, Class, and Static Methods Demystified
- Let’s get classy: how to create modules and classes with Python
- 파이썬 매직 메소드 (Python's Magic Methods)
- practice -
-
closure
-
collections
-
configparser
-
copy
-
coroutine
- A Curious Course on Coroutines and Concurrency
- Łukasz Langa - Thinking In Coroutines - PyCon 2016
- Curious Course on Coroutines and Concurrency
- Python coroutines with async and await
- practice - coroutine
- A brief introduction to concurrency and coroutines (Tutorial)
- Coroutines in Python with examples
- How Do Python Coroutines Work?
- PyconKR 2018 Deep dive into Coroutine
-
csv
- Reading and Writing to CSVs in Python Playing with tabular data the native Python way
- How to combine multiple CSV files with 8 lines of code
- Reading and Writing CSV Files in Python
- csvkit - A suite of utilities for converting to and working with CSV, the king of tabular file formats. http://csvkit.rtfd.org
- csvsort - Sort large CSV files on disk rather than in memory
- csvsql - Query CSV files using SQL
-
dataclass 파이썬 dataclasses가 뭘까?
-
datetime
- practice
- 파이썬 Datetime 이해하기
datetime.datetime.strptime([DATE IN STRING], '%Y-%m-%d %H:%M:%S').strftime('%s')string time to epoch time(datetime.datetime.today() - datetime.timedelta(days=[# of DAYS])).strftime("%Y%m%d000000")python-get-datetime-for-3-years-ago-todaydatetime.datetime.strftime(datetime.datetime.now() - datetime.timedelta(1), '%Y%m%d')yesterday as YYYYMMDD formatdatetime.datetime.now().date().isoformat()insert into MySQL date type- 주차를 알고 싶을 땐 isocalendar
- elapsed time in milliseconds
- Arrow: better dates and times for Python
- 파이썬의 시간대(datetime.timezone)에 대해 알아보기
- Python UTC -6 to KST (UTC +9)
- Parsing and Formatting Dates in Python With Datetime
- 파이썬 날짜 다루기 date, datetime, yyyymmdd
- 파이썬(Python) datetime 클래스 치트시트
-
decimal
-
decorator
- Understanding Python Decorators in 12 Easy Steps!
- Decorator to expose local variables of a function after execution (Python recipe)
- 파이썬 - 데코레이터 (Decorator)
- 서울대 경영대, 2016 벤처창업웹프로그래밍1 (이하 벤1), 파이썬 기말고사 시험문제 3, 4번
- 시간재기
- timer
- @decorators in Python
- Antonio Verardi - Write more decorators (and fewer classes)
- Write More Decorators And Fewer Classes
- Luciano Ramalho - Decorators and descriptors decoded - PyCon 2017
- Colton Myers: Decorators: A Powerful Weapon in your Python Arsenal - PyCon 2014
- Class Decorators: Radically Simple
- The Basics of Python Decorators
- Python Tutorial: Decorators - Dynamically Alter The Functionality Of Your Functions
- Decorators and Context Managers
- Python Decorators as Classes
- Decorators in Python (Mike Burns)
- Python Decorators
- Implementing Decorators in Python
- Python Tutorial: Decorators With Arguments
- Python OOP Tutorial 6: Property Decorators - Getters, Setters, and Deleters
- Decorators 101: A Gentle Introduction to Functional Programming - Jillian Munson
- 클래스에 메서드를 추가하는 decorator monkeypatch와 같이 기존 클래스에 새로운 메소드 추가하는 decorator
- decorator를 이용한 함수의 doc string 구하기
- Function Decorators in Python - Add extra functionality to your Python functions
- 파이썬 데코레이터(Decorator)에 파라미터 넣기
-
descriptor
-
dict
- dict <=> str 변환 시 eval 또는 cPickle
- Replacements for switch statement in Python?
- Pythonic switch statement
- 두 파이썬 딕셔너리를 병합하는 법
z = {**x, **y}How can I merge two Python dictionaries in a single expression?- How to Merge two or more Dictionaries in Python ?
- Raymond Hettinger Modern Python Dictionaries A confluence of a dozen great ideas PyCon 2017
- dict()의 in의 의미
- Dictionaries compare equal if and only if they have the same (key, value) pairs
- Raymond Hettinger Modern Python Dictionaries A confluence of a dozen great ideas PyCon 2017
- Modern Dictionaries by Raymond Hettinger
- Raymond takes us back in time to the 70s and how technologies pioneered then in the field of database research are finding their way back into the modern era
- PyCon 2010: The Mighty Dictionary
- Brandon Rhodes The Dictionary Even Mightier PyCon 2017
- the internals of how dictionaries are implemented in Python
- 2014 PyCon KR: 위대한 dict 이해하고 사용하기
- 구종만 위대한 dict 이해하고 사용하기 PYCON KOREA 2014
- Python Dictionary 순서 보장 원리
- 사전 자료형, 불린 조합 표현식
- David Beazley | Keynote: Built in Super Heroes
- Python3에서 NestedDict 내의 특정 키값을 이용해서 Value를 가져오기
- Dicts are now ordered, get used to it
-
dis
-
double/float
- practice - float sum
- round() in Python doesn't seem to be rounding properly
float(format(num, '.2f')) - 파이썬에서 부동 소수점 오차 해결하기
- Making floating point math highly efficient for AI hardware python 관련 내용은 아니지만 참고
- 파이썬 내부 동작 원리: 임의 정밀도의 정수 구현
-
encoding
- practice
- distinguish letter type by unicodedata, regex
- weird case from pyspark-hbase (utf8 & unicode mixed)
- print unicode character in window
locale.setlocale(locale.LC_CTYPE, 'kor')UnicodeEncodeError: locale codec can't encode character '\ub...'가 windows에서 발생하는 경우- string & bytes
- Python unicode cheatsheet encode decode ord normalize
- 파일명 깨짐 - 한글 자모 분리 현상 normalize
- How to convert string to byte arrays?
- Python bytearray ignoring encoding?
- python: how to convert a string to utf-8
- Python 2.x 한글 인코딩 관련 정리
- 파이썬 셸과 IDLE의 입출력 인코딩에 대해
- Python Unicode: Encode and Decode Strings (in Python 2.x)
- Encoding and Decoding Strings (in Python 3.x)
- 파이썬 2와 유니코드
- Python string formatting and UTF-8 problems workaround
- USING DHARMA TO REDISCOVER NODE.JS OUT-OF-BAND WRITE IN UTF8 DECODER
- 한상곤: 문자열? 그런 달달한 것이 남아있긴 한가? - PyCon APAC 2016 unicode는 문자셋, encoding은 문자셋을 메모리에 쓰는 것
- 파이썬 유니코드 이해하기
- 크롤링 데이터의 한글이 깨져요
- cChardet - universal character encoding detector
- The Updated Guide to Unicode on Python
- Everything you did not want to know about Unicode in Python 3
- 파이썬의 문자열 인코딩
- Processing Text Files in Python 3
- Common migration problems
- Strings, Bytes, and Unicode in Python 2 and 3
- python 3 의 string 정리
- Strings in 3.0: Unicode and Binary Data
- How to declare a byte array contains non-ascii characters without escape in python 3
- dotnetperls.com/bytes-python
- The only problem with Python 3's str is that you don't grok it
- Character Encoding in python
- practice
-
exception
-
ftplib
-
function
-
functools
-
gc
- Visualizing Garbage Collection in Ruby and Python
- Dismissing Python Garbage Collection at Instagram
- 강성일: GC없는 Python을 추구하면 안 되는 걸까
- Copy-on-write friendly Python garbage collection
- COW(Copy-on-write)가 발생하는 Python garbage collection python3.7에 추가된 gc.freeze
- Python GC가 작동하는 원리
- 자동 Garbage Collection 주기
- Garbage collection in Python: things you need to know
-
generator
- Extending Python’s generators to support mainloops
- 파이썬 - 제너레이터 (Generator)
- 파이썬의 제너레이터와 이터레이터
- 파이썬 iterator generator 이해하기
- Sieve daisy chain
- 이터레이터와 제너레이터
- Using Python Generator to Monitor Data
- Data Processing using Python Generators
- python - db stored procedure 호출에 generator 활용하기
- Threaded Generator in Python
- How — and why — you should use Python Generators
- Generators: The Final Frontier - Screencast
- David Beazley: Generators: The Final Frontier - PyCon 2014
- Python의 Generator 알아보기
- Python Generators Explained! (Sort of)
-
hash
-
idle
-
import
-
__init__.py -
intern
-
isinstance
-
itertools
-
- Python: Lambda Functions
- Yet Another Lambda Tutorial
- Python Functions - lambda 2015
- A tale of two lambdas: The joys of working in a polyglot team
- 파이썬+Lambda+이해하기 20160315
- Anjana Vakil - Mary had a little lambda
- funcional programming in scala에서 하던 것과 비슷하게 lambda를 이용해 숫자를 정의하고 int로 변환하고 arithmetic operation등을 만듦
-
json
-
list
- Python List Comprehensions: Explained Visually
- Python List Tutorial With Simple Python Projects For Beginners
- Understanding nested list comprehension syntax in Python
- 3 Python list comprehension tricks you might not know yet
- 9 Things to Know to Master List Comprehensions in Python
- 파이썬의 Comprehension 소개
- 파이썬에서 2중 리스트를 flatten하게 만들기
- Python - 리스트 순회중 수정하는 문제
- Printing Lists as Tabular Data
- [{...}] * 10 주의점
- Python: copying a list the right way
- Python 의 Filter / Map / Reduce 그리고 Comprehension
- A quick yet complete tour of lists in Python3 in just seven minutes
-
- DEBUG < INFO < WARNING < ERROR < CRITICAL, 기본 설정은 WARNING
- practice - experiences
- practice - basic logging with yaml configuration
- Exceptional Logging of Exceptions in Python
- log.lpy
- example TimedRotatingFileHandler
- 주의; 로그를 쓰지 않으면 해당 시간이 되도 log file이 rotate되지 않는다. 예를 들어 서버에서 TimeRotatingFileHandler를 사용하는 경우, 서버에 request가 없어서 log를 기록하려는 시도가 없으면, 해당 주기가 되어도 log file이 rotate되지 않으므로 주의. 위의 예제에서
logger.info("This is a test!")를 제거하고 실행해보면 알 수 있음 - 로그를 쓰기 시작한 시간으로부터가 아니라 매일 정시에 log rotate를 하려면
d가 아니라midnight을 사용
- 주의; 로그를 쓰지 않으면 해당 시간이 되도 log file이 rotate되지 않는다. 예를 들어 서버에서 TimeRotatingFileHandler를 사용하는 경우, 서버에 request가 없어서 log를 기록하려는 시도가 없으면, 해당 주기가 되어도 log file이 rotate되지 않으므로 주의. 위의 예제에서
- Python logging best practices with JSON steroids
- Making Python loggers output all messages to stdout in addition to log
- Python Logging (function name, file name, line number) using a single file
- 파이썬 로깅의 모든것
- Python logging causing latencies?
- logging 관련 몇몇 정리
- logging - propagation
- Python's Built-In 'logging' Module
- pycon kr 2018.12 파이썬 로깅, 끝까지 파보면서 내가 배운 것 - 황현태
-
loop
-
map
-
metaclass
- Python metaclasses
- python data model 이해하기
- Python data model
- Intro to the Python Data Model and Pythonic Programming
- It's metaclasses all the way down
- Metaclasses in Python
- The Fun of Reinvention (Screencast)
- The Fun Of Reinvention 파이썬3.6으로 흑마법을 부려보자
- Saving 9 GB of RAM with Python’s
__slots__ - A quick dive into Python’s “slots”
- CLASS ATTRIBUTE 와 INSTANCE ATTRIBUTE 의 구분과 구현
- 내부 동작을 이해하는 측면에서는 좋으나, 실제로는 전혀 쓸모없어 보임
- Underscore(_)로 시작하는 파이썬 클래스명
- PyCon Korea 2019 리얼월드 메타클래스 매우 좋은 발표 내용
- 리얼월드 메타클래스
-
method
-
mmap
-
monkey patch
-
multiprocessing multithreading threading parallel
-
practice
-
logging
-
starmapmap은 multiprocessing으로 호출할 function argument로 하나만 줄 수 있어서 여러 개를 줘야 할 때는 starmap 사용 -
for ident, stack in sys._current_frames().items(): logger.info(("%d" % ident) + "".join(traceback.format_list(traceback.extract_stack(stack)))) -
파이썬 동시성 프로그래밍 - (9) Concurrent.Futures & ProcessPoolExecutor
-
Michal Wysokinski - Running Python code in parallel and asynchronously
-
Multithreading in Python with Global Interpreter Lock (GIL) Example
-
Functional Programming in Python: Parallel Processing with "multiprocessing"
-
Functional Programming in Python: Parallel Processing with "concurrent.futures"
-
Amber Brown Implementing Concurrency and Parallelism From The Ground Up PyCon 2017
-
An introduction to parallel programming using Python's multiprocessing module
-
Get a 2–6x speed-up on your pre-processing with these 3 lines of code! concurrent.futures
-
CUDA In Your Python: Effective Parallel Programming on the GPU
-
Parallel Computing in Python: Current State and Recent Advances
-
threading
- practice
- thread dump
- Vinicius Pacheco - Green threads in Python
- Python Multithreading Tutorial: Concurrency and Parallelism
- Running a method as a background thread in Python
- An Intro to Threading in Python
- How to Create a Thread in Python
- Using a global variable with a thread
- Thread Synchronization Mechanisms in Python
- Multithreading in Python | Set 2 (Synchronization)
- Python 3 - Multithreaded Programming
- Running a method as a background process in Python
-
-
namedtuple
-
namespace
-
os
-
partial
>>> from functools import partial >>> foo = partial(lambda a, b: a + b, b=3) >>> foo(2) 5 -
patch
-
pathlib
-
pep
-
pickle
pickle_file = '<filename>' with open(pickle_file, 'rb') as f: u = pickle._Unpickler(f) u.encoding = 'latin1' save = u.load() dataset = save['<key>'] -
pprint
-
profile
- PROFILING IN PYTHON
cPickle.PicklingError: Can't pickle <type 'function'>: attribute lookup __builtin__.function failed- happens when multiprocessing + cProfile
python -m cProfile some_multiprocessing.py
- happens when multiprocessing + cProfile
- How can you profile a Python script?
- Accurate Time Measurements Python
- memory_profiler
defaultdict(list), key는 (str, str), value는 list of (str, int)의 경우- 1,000,000개 memory 약 440MB, 입력 4m정도 소요
- 10,000,000개 memory 약 4.1GB, 입력 41m정도 소요
- Profiling Python in Production
- PUDB 콘솔 디버거
- profiling - An interactive continuous Python profiler
- Profiling CPython at Instagram
- Profiling and optimizing Python code
- Pympler - a development tool to measure, monitor and analyze the memory behavior of Python objects in a running Python application
- Py-Spy: A sampling profiler for Python programs
- StackImpact Python Agent - Production Profiler: CPU, memory allocations, blocking calls, exceptions, metrics, and more https://stackimpact.com
- tracemalloc — Trace memory allocations
- VMprof Python client profiler
-
property
-
random
- shuffle 사용자 데이터셋 셔플
-
re
-
self
-
serialization
-
sets
-
setup.py, distutils, packaging
- setup.py와 requirements.txt의 차이점과 사용 방법
- 파이썬 프로젝트 시작하기 - Distutils
- 파이썬 프로젝트 시작하기 - Setuptools
- 파이썬 package 배포 하기
- Packaging and Distributing Projects
- pypi 패키지 만들어보기
- 파이썬 패키지 Pypi에 오픈소스 등록하는 방법
- 로컬 PYPI 서버 설정하기
- 파이썬 패키지를 공유하는 법
- How We Deploy Python Code (hint: not using Git)
- The problem with packaging in Python
- From a python project to an open source package: an A to Z guide
- devpi - Python PyPi staging server and packaging, testing, release tool http://doc.devpi.net
-
smtplib
-
socket
- Python Network Programming
- High-performance Networking with Python
- Finding local IP addresses using Python's stdlib
- 처음 만드는 온라인 게임 03-01 : Python HTTP server 개발
- 처음 만드는 온라인 게임 03-02 : Python HTTP server 개발
- 처음 만드는 온라인 게임 04-01 : Python web socket server 개발
- 처음 만드는 온라인 게임 04-02 : Python web socket server 개발
- How to Do Socket Programming in Python
- Python으로 채팅 구현하기
- 2017 파이컨 튜토리얼 - 네트워크 프로그래밍 개념 맛보기
- python을 이용한 다중 채팅 구현하기
- Sockets Tutorial with Python 3
- 남의 컴퓨터를 내 마음대로 다룬다? - Python Reverse Shell
-
sort
-
ssl
-
__str__ -
string
-
0 padding for multi variables; Nicest way to pad zeroes to string
from datetime import datetime _today = datetime.today() '{0:04d}{1:02d}{2:02d}'.format(_today.year, _today.month, _today.day) -
replace
-
import string [string].translate(None, string.whitespace)
-
- pymotw.com/3/subprocess
- asyncio-subprocess
- pymotw.com/3/asyncio/subprocesses.html
- python, subprocess: reading output from subprocess
- 파이썬에서 bash 명령어 실행 subprocess, pexpect
- subprocess를 사용한 병렬 프로그래밍 - (1)
- python-daemon test해본 결과 daemon으로는 잘 동작하지만 크게 쓸모가 있는지는 모르겠음
subprocess.run([...], stdin=subprocess.DEVNULL, stdout=subprocess.DEVNULL, stderr=subprocess.STDOUT)- Popen처럼 docker flask app에서 api를 호출해 시간이 오래 걸리는 작업을 별도 process로 실행하는 경우를 위해 사용
- 공식 문서에 따르면 3.5부터 추가되었으며 모든 경우 run 사용을 추천한다고 함
- Popen과 달리 똑같은 형식으로 호출해도 blocking되고 모든 작업이 끝나야 caller로 돌아옴
subprocess.Popen([...], stdin=subprocess.DEVNULL, stdout=subprocess.DEVNULL, stderr=subprocess.STDOUT)- docker flask app에서 api를 호출해 시간이 오래 걸리는 작업을 별도 process로 실행하는 경우를 위해 사용
- async처럼 별도로 실행하고 바로 caller로 돌아옴
- pipe로 한글이 포함되는 경우
encoding=[utf8|euc-kr|cp949|...]oruniversal_newlines=True설정이 필요할 수도 있음
- Python trick: asynchronously reading subprocess pipes
- Streaming subprocess stdin and stdout with asyncio in Python
- Subprocess 모듈 사용법 – 파이썬에서 서브 프로세스를 생성하기
- Subprocess timeout failure
-
sys
-
timeit -
TypeError
TypeError: file() argument 1 must be encoded string without NULL bytes, not str- Common Mistakes as Python Web Developer
-
unicodedata
-
urllib
-
urlparse
-
uuid
-
with, context manager
-
xml
-
yield
- Python의 yield 키워드 알아보기
- [Python의 Generator와 yield 키워드](Python의 Generator와 yield 키워드)
- Python의 yield from 키워드는 무엇일까
- docs.python.org/3/library/asyncio.html
- github.com/python/asyncio/wiki/ThirdParty
- A curated list of awesome Python asyncio frameworks, libraries, software and resources
- The new Python asyncio module aka “tulip”
- github.com/python/asyncio/wiki/Benchmarks
- Python tricks: Demystifying async, await, and asyncio
- Understanding Asynchronous IO With Python 3.4's Asyncio And Node.js
- Miguel Grinberg Asynchronous Python for the Complete Beginner PyCon 2017
- AsyncIO for the Working Python Developer
- Asyncio Coroutine Patterns: Beyond await
- Asyncio Coroutine Patterns: Errors and cancellation
- Asynchronous Python Await the Future
- 비동기 파이썬 gevent, tornado
- Async I/O and Python
- blocking, non blocking, eventlet, twisted, GLib, Tulip, Coroutines, Generators, and Subgenerators
- 배준현 Python 3 4; AsyncIO PYCON KOREA 2014
- A Weekend with Asyncio
- Python async/await Tutorial aiohttp
- Python 3, asyncio와 놀아보기
- A Web Crawler With asyncio Coroutines
- Concurrency in Python threading, multiprocessing, aiohttp
- asyncio 공부 echo server
- python async URL요청 aiohttp
- asyncio
- asyncio : 단일 스레드 기반의 Nonblocking 비동기 코루틴 완전 정복
- async with : 비동기 컨텍스트 매니저
- How the heck does async/await work in Python 3.5?
- 파이썬의 await vs return vs return await
- How to Scrape and Parse 600 ETF Options in 10 mins with Python and Asyncio
- Understanding Asynchronous Programming in Python
- Exploring Python 3’s Asyncio by Example
- ASYNC EXECUTION IN PYTHON USING MULTIPROCESSING POOL
- Playing with asyncio comparison with twisted & gevent
- 어릴 적 할머니가 들려주신 옛 wsgi wsgi & gevent
- asyncio.readthedocs.io
- Python 3 asyncio basic producer / consumer example
- Threaded Asynchronous Magic and How to Wield It
- Some Python 3 asyncio snippets
- Controlling Python Async Creep
- async_await_help.py
- Using asynchronous for loops in Python
- 파이썬과 비동기 프로그래밍
- Advanced asyncio: Solving Real-world Production Problems
- asyncio: We Did It Wrong
- 왜 asyncio에 뮤텍스 락이 필요할까? asyncio.Lock()
- An Introduction to ASGI, Asynchronous Server Gateway Interface
- youtube
- Fear and Awaiting in Async (Screencast)
- Common asynchronous patterns in Python
- Tulip: Async I/O for Python 3
- Python 3.5+ Async: An Easier Way to do Concurrency
- Yury Selivanov - async/await in Python 3.5 and why it is awesome
- Yury Selivanov asyncawait and asyncio in Python 3.6 and beyond PyCon 2017
- Yury Selivanov - Asyncio in Python 3 7 and 3 8 Trio
- Barry Warsaw aiosmtpd A better asyncio based SMTP server PyCon 2017
- Practical Python Async for Dummies
- Get to grips with asyncio in Python 3 - Robert Smallshire
- Coroutine Concurrency in Python 3 with asyncio - Robert Smallshire
- The Other Async (Threads + Async = ❤️)
- Jonas Obrist - Why you might want to go async
- Anton Caceres - Using the right Async tool, present day
- Amit Nabarro - Asynchronous I/O and the real-time web
- Asynchronous Python For The Complete Beginner
- ASYNCHRONOUS PROGRAMMING WITH PYTHON
- Get To Grips With Asyncio In Python 3
- Building real-world applications with
asyncio - Keynote David Beazley - Topics of Interest (Python Asyncio)
- Why should I care about asyncio
- Getting Started with asyncio and Python
- Asyncio Tasks in Python Tutorial
- A Really Gentle Introduction to Asyncio
- What Is Async, How Does It Work, and When Should I Use It? (PyCon APAC 2014)
- What in the World is Asyncio? by Josh Bartlett
- Asyncio - Asynchronous programming with coroutines - Intermediate Python Programming p.26
- Async / Await and Asyncio In Python
- Webscraping With Asyncio - Jose Manuel Ortega
- James Kirk Cropcho - Asynchronous Python A Gentle Introduction
- Hrafn Eiriksson - Asyncio in production asyncio migration에 대한 실용적인 안내
- Async & Await Tutorial
- Asyncio, websockets, and BTC sitting in a tree - Giovanni Lanzani
- John Reese - Thinking Outside the GIL with AsyncIO and Multiprocessing - PyCon 2018
- Async/Awaiting Production
- Dmitry Nazarov: "Future Pythonic Web: ASGI & Daphne"
- Build Your Own Async
- aiofiles: file support for asyncio
- aiohttp: Asynchronous HTTP Client/Server
- practice - aiohttp
- aiohttp server deployment
- Aiohttp로 대량의 requests 처리하기
- Making 1 million requests with python-aiohttp
- Macro-benchmark with Django, Flask and AsyncIO (aiohttp.web+API-Hour)
- 황성현: aiohttp in Production
- Building the Real-time Web with Python and aiohttp (Steven Seguin)
- Building The Real Time Web With Python
- Day 2: Pau Freixes Alió - Running Aiohttp at scale
- aiohttp로 하는 비동기 HTTP 요청
- aio-libs - The set of asyncio-based libraries built with high quality
- aiomysql - a library for accessing a MySQL database from the asyncio http://aiomysql.readthedocs.io
- aiotools - Idiomatic asyncio utilties
- Curio - a modern library for performing reliable concurrent I/O using Python coroutines and the explicit async/await syntax introduced in Python 3.5
- Quart - a Python asyncio web microframework with the same API as Flask
- Sanic - a Flask-like Python 3.5+ web server that's written to go fast
- 한동안 top 10 contributor였던 개발자 Jeong YunWon님의 경고
- flask와 비슷하다 = 사기. 이제 그런 소개도 빼버린것 같은데, 개발자들은 호환성 맞출 생각 없음. url path도, blueprint도, 사실은 아무것도 안맞으므로, flask와 비슷해 보여서 쓰기로 결심했다면 사용하면 안됨. decorator 씌워서 route하는거 딱 하나만 비슷
- 전반적으로 소프트웨어 디자인 자체에 대해 별 생각이 없음. 참고: sanic-org/sanic#37
- 품질 관리보다 벤치마크에 집착. 벤치마크에 큰 향상이 있으면 쉽게 릴리즈. 심각한 소프트웨어 버그는 때로는 몇달씩 릴리즈되지 않을 수 있음. http 헤더 fragment를 잘못 파싱해 헤더가 누락되는 버그는 master에 머지된 후 릴리즈되기 까지 6개월
- 프로파일링 기반으로 성능을 측정함에도 불구하고 합리적인 reasoning 없이 성능미신에 의해 최적화. 이 코드는 현재 사라졌으니 이 정도만 코멘트.
- 위와 같은 문제와 여러 변주 이후로 토론에 지친 "정상적인 설계"를 원하는 초기 기여자들은 대부분 떠남. Contributors에 들어가서 기여자들이 얼마나 빨리 떠나는지 보고, 그들이 어떤 이슈에 참여했나 보면 어떤 일이 일어나는지 알 수 있음
- sanic.readthedocs.io
- Dougal Matthews - Async Web Apps with Sanic
- Python Sanic Tutorial
- Introducing Myself to Sanic, a Python Web Server
- More Sanic/Python Fun. Submitting a Form via Ajax Post Request with Vuejs
- postit-sanic - An REST API and Single Page App with Sanic; A Python Webserver/Microframework
- programcreek.com/python/index/9697/sanic
- Pycon Korea 2018-Sanic을 활용하여 Microservice 구축하기-이재면
- 한동안 top 10 contributor였던 개발자 Jeong YunWon님의 경고
- Starlette - a lightweight ASGI framework/toolkit, which is ideal for building high performance asyncio services
- tokio - Asyncio event loop based on tokio-rs (WIP)
- Trio – Pythonic async I/O for humans and snake people 🐍
- Nathaniel J. Smith - Trio: Async concurrency for mere mortals - PyCon 2018
- 구조적 동시성에 대한 소고, 또는 Go 문의 해로움
- 정말 좋은 글. 특히 놀라운 건 Donald Knuth같은 사람도 한 때 goto를 옹호했다는 점
- Nathaniel J Smith - Python Concurrency for Mere Mortals - Pyninsula #10
- vibora - Fast, asynchronous and elegant Python web framework. https://vibora.io
- Baseball Analytics: An Introduction to Sabermetrics using Python
- Parses, Analyzes and Predicts for the Korean Baseball League
- 데이콘 야구대회 튜토리얼 2-1 판다스 기본 문법
- Linear Regression: Moneyball — Part 1 A statistical case study of the popular sports story
- 5 Python books for beginners
- 20 Best Free Tutorials to Learn Python: PDFs, eBooks, Online
- The Little Book of Python Anti-Patterns
- Collection Of 51 Free eBooks On Python Programming
- Python 101
- Jupyter Notebooks with Fluent Python examples https://github.com/AllenDowney/fluent-python-notebooks
- Books by Agiliq
- Django Admin Cookbook, Django ORM Cookbook, Building APIs with Django and Django Rest Framework, Building Multi Tenant Applications with Django, Django Projects Cookbook, Django Design Patterns, Django Gotchas
- Journeyman Python, Essential Python Tools, Tweetable Python, Software consulting Howto, Visual Arts with Python
- 정보교육을 위한 파이썬 Python for Informatics: Exploring Information
- 파이썬으로 풀어보는 수학
- 해커의 언어, 치명적 파이썬
- 시스템 트레이딩을 위한 데이터 사이언스 (파이썬 활용편)
- 파이썬 괴식 레시피 - 긱(Geek)스럽게 파이썬 활용하기
- 파이썬 책 추천 목록 정리
- 중급 파이썬: 파이썬 팁들
- 마야 파이썬 (Maya Python)
- byte of python-korean
- Clean Architectures in Python
- Dive Into Python 3
- Django 자습
- Effective Pandas
- FIND THE BEST PYTHON BOOKS
- Full Stack Python
- Python 3.4 공부 좀 해볼까?
- Python으로 배우는 BBC micro:bit
- Python Data Science Handbook Essential Tools for Working with Data
- Python for Scientists and Engineers
- Python for Signal Processing Featuring IPython Notebooks
- SICP in Python
- Think DSP
- Think Python: How to Think Like a Computer Scientist 2판
- Think Stats 2e python + statistics, free download
- Understanding Python bytecode by implementing tail call optimization
- Python bytecode is quite heavily trusted by CPython
- Understanding Python Bytecode
- Blip, a bytecode compiler and interpreter for Python 3
- David Beazley - Python Concurrency From the Ground Up: LIVE! - PyCon 2015
- Thinking about Concurrency, Raymond Hettinger, Python core developer
- Brett Slatkin: Fan-in and Fan-out: The crucial components of concurrency - PyCon 2014
- David Beazley - Python Concurrency From the Ground Up: LIVE! - PyCon 2015
- Thinking about Concurrency, Raymond Hettinger, Python core developer
- 파이썬에서 디버깅하기
- PyCharm as the Ultimate Python Debugger
- Python debugging tools
- HOW TO DEBUG (DEADLOCKED) MULTI THREADED PROGRAMS (PYTHON RECIPE)
- Python Debugging Tips 20160814-1800 PyCon Asia Pacific
- Using Docker and Pycharm for Remote Django Debugging
- Segmentation Fault 발생 시 gdb로 stack trace 해 보기
- Connect AWS EC2 Instance with PyCharm Professional
- 파이썬 코드에서 중간에 콘솔 띄우는 디버깅
import code; a = 3; code.interact(local=locals()) - LA오빠 즐거운 Data Science - 코딩효율 2x 늘리기 팁 1탄 PDB, VS Code, Jupyter
- Elizaveta Shashkova - Debugging in Python 3.6: Better, Faster, Stronger
- PyConKr 2018 GDB와 strace로 Hang 걸린 Python Process 원격 디버깅
- bugbuzz - Fall in love with debugging
- PDB
- PySnooper - Never use print for debugging again
- continuous-docs - Tutorial and example package for continuous documentation generation in Python
- portray - a Python3 command line tool and library that helps you create great documentation websites for your Python projects with as little effort as possible
- drf-yasg drf-yasg에 예제값 달기
- pydoc
- sphinx
- Django 문서
- www.askcompany.kr/r
- (번역) Django 공식문서 - Introduction to models
- Django resources
- Learn Django: Payment Processing
- Digging Into Django
- Pirates use Flask, the Navy uses Django
- TaskBuster Django Tutorial
- 날로 먹는 Django 웹프레임워크 강좌
- 시나브로 Django 발표
- Category: start-with-django-webframework
- Django를 배우다, Django로 배우다
- Using Gabbi and Hypothesis to Test Django APIs
- The Django Test Driven Development Cookbook - Singapore Djangonauts
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- Django 에서 pytest 사용하기 - 'pytest와 pytest-django 시작하기' 번역
- 테스트 초보의 테스트 삽질기 with Django
- 한종원: Django API Server Unit Test and Remote Debugging
- Model Mommy: Smart fixtures for better tests
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- Deploying a Django App with No Downtime
- Django, 저는 이렇게 씁니다
- Python Web Development: Understanding Django for Beginners
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- Finally, Real-Time Django Is Here: Get Started with Django Channels
- pycon kr 2018.12 Django Channels 삽질기 - 방신우
- Add2paper printing system using Django-channels
- (엑셀만큼 쉬운) Django Annotation/Aggregation
- Djangogo!!! Building a Blog Application 총정리
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- Django - 라이브 코딩쇼 #1 - 천천히 40분 만에 심플 사진 블로그 만들기
- AskDjango 여러분의 서비스 개발. 그 시작을 도와드리겠습니다
- Django Web Development with Python
- Dango에서 간단한 REST API 만들기
- Create a Django API in Under 20 Minutes
- Web Service Efficiency at Instagram with Python
- lazy_django
- Why Django Sucks - PyCon SE 2015
- Andrew Godwin - Reinventing Django for the Real-Time Web - PyCon 2016
- schoolofweb.net/blog/posts/tag/django
- State of the Real-time Web with Django
- Realtime Example app Tutorial - Using Django, django-realtime, iShout.js,Node.js & Redis
- 파이썬과 Node.js를 같이 쓰다가 망했던 경험
- Gnuboard to Django Series #01
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- PyCon KR 2018 Effective Tips for Django ORM in Practice
- DjangoORM에서 SQL Driver 지정해 Query & Pandas DataFrame 얻어내기
- 장고 ORM 요리책
- 장고 ORM 요리책
- Django ORM cookbook 번역 후기 read the docs, sphinx
- Django ORM Relationships Cheat Sheet
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- 반드시 알아야 할 5가지ORM 쿼리
- 장고 모델 행동(Django Model Behaviors) By Kevin Stone
- 김도현 : Django vs Flask, 까봅시다! - PyCon APAC 2016
- 박현우: Django in Production - PyCon Korea 2015
- 장고 페어코딩 후
- 도서 — 파이썬 웹프로그래밍 실전편 (요약)
- Django migration 궁금증
- How to migrate Django from SQLite to PostgreSQL
- ElasticSearch with Django the easy way
- 장고(Django)와 함께하는 Celery 첫걸음
- Django에 Custom인증 붙이기
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- 배포한 Django 서비스 Exception Sentry로 받아보기
- AWS Elastic Beanstalk + CI 를 이용한 Django 배포 자동화
- CS50: Web Programming with Python
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- Django로 웹 서비스 개발하기 (2. Class, Object)
- Django로 웹 서비스 개발하기 (3. Object 실습)
- Django로 웹 서비스 개발하기 (4. MTV, 프로젝트 생성)
- Django로 웹 서비스 개발하기 (5. View — urls.py와 views 수정)
- Django로 웹 서비스 개발하기 (6. Model — 생성, admin 등록)
- Django로 웹 서비스 개발하기 (7. test code, template, css)
- 장고, 빠르고 탄탄하게 웹사이트 개발하기
- Django initial data | fixture 또는 RunPython 이용하기
- Django에서 fixture사용하기
- Djangoでfixtureを使う
- modern-django - Modern Django: A Guide on How to Deploy Django-based Web Applications in 2017
- 테스트 코드의 여러가지 유형
- Django 나만의 Command 만들어보기
- django-allauth 소셜로그인 후의 redirect에 대해
- Learn Django
- Mistakes I Made Writing a Django App (and How I Fixed Them)
- Handling webhooks using Django and ngrok
- Django 1.11 릴리스와 주요 변경 사항
- masnun.com/category/django
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- docker-with-django.md
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- 5 ways to make Django Admin safer
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- select_related, prefetch_related 그리고 debug toolbar
- DjangoTDDStudy
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- coding-night-live - a Web-Based Communication Application for codelabs
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- (번역) How to Create Django Data Migrations
- (번역) Django Tips #8 Blank or Null?
- simple is better than complex
- SQLのSELECT文を、DjangoのQuerySet APIで書いてみた
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- 9 Django Tips for Working with Databases
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- code.djangoproject.com/wiki/DjangoAndPyPy
- Faster Django Sites with PyPy
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- Django - tweetme 소셜서비스 구현해보기 (1) - Django Setup
- Django Builder
- Django get_or_create() 함수에서 발생한 MySQL Deadlock 이슈 해결하기
- Django 2 by Example, published by Packt
- Django Mini Project 부트스트랩 랜딩페이지 구름IDE
- Django, 공공데이터포털, Google Map으로 전기차 충전소 위치찍기
- Django 3.0 릴리스와 주요 변경 사항 - MariaDB 지원, ASGI 지원, 필터 표현식 등
- django-annoying - A django application that tries to eliminate annoying things in the Django framework
- gmail 로 이메일 보내기
- Sending an Email in Python via Gmail
- Gmail API How To Send Email with Attachments Using GMAIL API For Beginners 2018
- Python - Sending Email With Gmail SMTP Server
- Send Email in Python using SMTP Server using Outlook and Gmail
- How to send email/gmail using python script step by step
- How To Send an Email in Python With Attachments Easy for Beginners
- Python Basics: Sending E-mails
- How to send an email with Python
- How to Read Emails using IMAP Download Attachments Python 3 for Beginners 2018
- Using Markdown to Create Responsive HTML Emails
- 파이썬을 이용하여 이메일(email) 전송 - 파일첨부, HTML 양식 사용
- elven.io - Email us to get any Python programming task completed
- Envelopes - Mailing for human beings email
- exchangelib - Python client for Microsoft Exchange Web Services (EWS)
- How To Use Excel VBA In Python
- Python Basic - 파이썬 엑셀(Excel, CSV) 읽기 및 쓰기 (1)
- Python Basic - 파이썬 엑셀(Excel, CSV) 읽기 및 쓰기 (2)
- Excel vs Python: How to Do Common Data Analysis Tasks
- DOTXCEL - Paint Your Image To Excel!
- **Grid studio - a web-based spreadsheet application with full integration of the Python programming language. https://gridstudio.io **
- img2xls - Convert images to colored cells in an Excel table
- LibXL excel library for developers
- openpyxl How to create, read, update and search through Excel files using Python
- pandas
- practice - test_pandas.py key가 자동으로 정해지므로 필요하면 customize해야 함
- Combine Multiple Excel Worksheets Into a Single Pandas Dataframe
- Pycel - a small python library that can translate an Excel spreadsheet into executable python code
- PyXLL - The Python Excel Add-In
- xlrd practice - test_xlrd.py
- xls2sql - excel to sql script
- xlsx pandas Excel File Data Analysis(엑셀 파일 Pandas 분석)
- XlsxWriter - Creating Excel files with Python and XlsxWriter
-
practice; encoding 문제로 저장한 csv를 excel에서 열었더니 글자가 깨져 보일 때
$ pip install xlwt xlsxwriter import pandas as pd df = pd.read_csv('some_file.csv', encoding='utf-8') writer = pd.ExcelWriter('some_file-r.xlsx', engine='xlsxwriter',options={'encoding':'utf-8'}) df.to_excel(writer, sheet_name='Sheet1') writer.save()
-
- practice
- logging
- pytest
- Flask resources
- Flask의 세계에 오신것을 환영합니다
- Flask 웹어플리케이션 구축하기
- 파이썬 플라스크 로 배우는 웹프로그래밍
- Setuptools 을 이용한 디플로이
- Flask Book
- Flask 애플리케이션 개발 환경 구성
- Flask 공식 튜토리얼 따라하기
- The Flask Mega-Tutorial
- Part I: Hello, World!
- Part II: Templates
- Part III: Web Forms
- Part IV: Database
- Part V: User Logins
- Part VI: Profile Page and Avatars
- Part VII: Error Handling
- Part VIII: Followers
- Part IX: Pagination
- Part X: Email Support
- Part XI: Facelift
- Part XII: Dates and Times
- Part XIII: I18n and L10n
- Part XIV: Ajax
- Part XV: A Better Application Structure
- Part XVI: Full-Text Search
- Part XVII: Deployment on Linux
- Part XVIII: Deployment on Heroku
- Part XIX: Deployment on Docker Containers
- Flask Tutorials
- Secure Flask REST API Server Template
- Docker image with uWSGI and Nginx for Flask applications in Python running in a single container
- Flask앱을 uWSGI와 Nginx를 사용하여 배포하기
- How To Serve Flask Applications with Gunicorn and Nginx on Ubuntu 16.04
- How To Serve Flask Applications with uWSGI and Nginx on Ubuntu 18.04
- 구글 애널리틱스 API를 사용한 Flask 앱을 uWSGI와 nginx로 배포한 과정
- Dockerize Simple Flask App
- How to make a Flask blog in one hour or less
- Flask is a microframework for Python based on Werkzeug, Jinja 2 and good intentions. And before you ask: It’s BSD licensed!
- Pirates use Flask, the Navy uses Django
- Django vs Flask - A practitioner’s perspective
- What is Flask-Admin
- A recipe for App Engine – Target – How does it work
- How To Structure Large Flask Applications
- Weird thing to understand from mongoengine in Flask
- Implementing a RESTful Web API with Python & Flask
- Python, Flask, WSGI, Apache 설정 삽질 ㅠ on CentOS 6
- Flask에서 예외(Exception)를 이용하여 HTTP 에러 응답에 사용자 정의 메세지 추가하기
- Flask 웹 앱과 Flask-OAuthlib를 이용하여 구현한 OAuth 2.0 서버 연동 및 토큰 갱신 방법
- 카카오톡 자동응답 API + FLASK 를 활용해서 카톡봇만들기
- Simple Flask Blog That I made
- Testing file upload handling in Flask
- HTTP Methods in Flask
- Flask-Login 예제
- Login authentication with Flask
- (flask) JSON 데이터 받기 및 예외처리
- flask - jinja2 tojson 필터
- flask - json_encoder 지정하기
- render_template 어떻게 사용할까?
- flask - request.script_root 이용하기
- flask-mqtt : subscribe 시 qos 설정 이슈 수정하기
- FLASK TDD with TESTING GOAT
- On-demand image server with Python
- Flask,VueJS,RethinkDB 로 파일 저장 서비스 만들기 - (1)
- Flask Python Web Framework Installation and Routing Rule | Deep Learning
- 한글이 보이는 Flask CSV Response 만들기
- Flask Response Encoding 문제 make_response 사용
- Flask 블루프린트(blueprint) 사용하기
- Using the url_for Function in Flask Blueprints
- Intro to Flask Blueprints
- Intermediate Flask - Structuring Larger Flask Applications w/Blueprints
- Asynchronous Task in Flask Using Celery
- Flask, Celery & SQLAlchemy Example
- Using Celery in Flask to Email Dynamic PDFs
- Build MVP With Python Flask and ReactJS
- How I Reverse Engineered A Chrome Extension To Write My Own Flask App
- Flask 1.0 Changelog 우리말 번역
- Flask 1.0에서 달라진 점
- FLASK vs DJANGO
- Python Backends: Flask Versus Django
- 기술블로그 구독서비스 개발 후기
- Python Flask에서 페이지 Redirect 이동하는 방법
- Flask: redirect vs redirect(url_for)
- Creating a Weather App in Flask Using Python Requests
- Stub API Maker Served by Flask - It makes stub API based on under static folder structure and a setting file
- pycon kr 2018.12 파이썬 웹 배포 삽질!! 이제 그만 - 이새로찬
- 파이썬 웹 배포 삽질!! 이제 그만 gunicorn, nginx
- Flask-Large-Application-Example
- Flask Routing & Sessions: A Subtle Symphony - With great flexibility comes great responsibility
- Flask for Beginners Tutorial - Learn Flask in 40 Minutes (2019)
- Flask TodoMVC Tutorial
- Model-View-Controller (MVC) Explained – With Legos
- Generating HTML Pages from MongoDB with MongoEngine and Jinja2 (Flask Part 1)
- Building a Flask Web Application (Flask Part 2)
- Flask Movie API Example
- How to build a cryptobot in Python and connect it to Facebook messenger
- Building a URL Shortener in Flask
- Get Form Checkbox Data in Flask With .getlist
- Organizing a Flask Project Beyond Single File
- CORS in Flask
- 3 Quick Tips to Make Your Flask Apps Better
- Codelog Record all of url that you want to remind http://codelog.kr pocket하고 비슷해보임
- Full-stack single page application with Vue.js and Flask
- Developing a Single Page App with Flask and Vue.js
- Advanced Flask Patterns
- Bread pan 기본적인 웹서비스를 간단하게 만드는 프로젝트 틀 구조 참고
- Flask-aiohttp — Asynchronous Flask application with aiohttp
- Flask-AppBuilder - Simple and rapid application development framework, built on top of Flask. Includes detailed security, auto CRUD generation for your models, google charts and much more
- Flask-APScheduler is a Flask extension which adds support for the APScheduler
- Flask-Assets 사용 방법 (1)
- Flask-Assets 사용 방법 (2)
- Flask-babel을 통한 i18n(Internationalization)
- flask-babel 로 다국어 대응하기
- Flask-Bcrypt - a Flask extension that provides bcrypt hashing utilities for your application
- Flask-Cache
- Flask-Login
- Flask-MongoEngine - a Flask extension that provides integration with MongoEngine
- Flask-MySQLdb provides MySQL connection for Flask
- Flask-Potion - a RESTful API framework for Flask and SQLAlchemy http://potion.readthedocs.org
- Flask-Praetorian Flask-Praetorian Walkthrough: A Library for API Security With JSON Web Tokens (JWT)
- flask-pytest - Runs pytest in a background process when DEBUG is True
- Flask-RESTPlus
- Flask & flask-restplus && swagger ui
- Flask-RestPlus 모듈 제대로 사용해 보기
- Structuring a Flask-RESTPlus Web Service for Production Builds
- Working with APIs using Flask, Flask-RESTPlus and Swagger UI
- How to structure a Flask-RESTPlus web service for production builds
- flask-restplus-boilerplate - A boilerplate for flask restful web service
- Flask로 API 서버 만들기 (1) - 개발 환경 준비
- Flask로 API 서버 만들기 (2) - config 와 실행 확인
- Flask로 API 서버 만들기 (3) - User 테이블 만들기
- Flask로 API 서버 만들기 (4) - Testing
- Flask로 API 서버 만들기 (5) - User Operations
- Flask로 API 서버 만들기 (6) - Security and Authentication
- Flask로 API 서버 만들기 (7) - Route protection and Authorization
- Flask로 API 서버 만들기 (8) - Extra tips (Makefiles)
- flask-security Intro to Flask-Security
- Flask-SQLAlchemy
- SQLAlchemy Query를 Pandas DataFrame로 만들기
- flask-sqlalchemy 외래키 구현
- Understanding the Lazy Parameter in Flask-SQLAlchemy Relationships
- Creating a RESTFul API in Flask With JSON Web Token Authentication and Flask-SQLAlchemy
- Manage Database Models with Flask-SQLAlchemy
- Getting Started With Flask-SQLAlchemy 2019
- Use Flask-SQLAlchemy With Existing Database With Reflect and Automap
- How to build a JSON API with Python
- flask-sqlacodegen - 기존 DB를 Flask-SQLAlchemy ORM Model로 사용하기
- Flask-Validation
- Frest - the frame of the restful api server created with pallets/flask
- Quart - a Python ASGI web microframework
- Yellowid-Flask
- GraphQL Python
- graphene-python.org
- GraphQL server up and running with 50 lines of python
- Playing With GraphQL + Python Flask
- GraphQL in the Python World
- The Fullstack Tutorial for GraphQL
- GraphQL in Python and Django
- Awesome-GraphQL GraphQL server with Flask + Graphene
- GraphQL in Python
- 사용할 Python GUI 비교 및 선택하기
- Python GUI Frameworks (Guide)
- Electron as GUI of Python Applications
- github.com/soma0sd/python-study/GUI
- Gooey (Beta) - Turn (almost) any Python Console Program into a GUI application with one line
- PyAutoGUI - Cross-platform GUI automation for human beings
- PyQT
- 예제로 배우는 PyQt 예제 중심으로 배우는 PyQt 프로그래밍
- QTBook - Qt Korea Developer Community
- PyQT Python GUI Application Development with Python
- PyCon 2015 - 업무에서 빠르게 활용하는 PyQt
- PyQT Basic Tutorial
- PyQT의 소개와 특징
- 파이썬 GUI - PyQt
- Detecting Keyboard Events in PyQt4
- Python, pyqt4 스톱워치 만들기
- Creating a web-browser with Python and PyQT
- PyCon 2017 예제로 살펴보는 PyQt
- mac에서 pyqt5 시작해 보기
- pyqt5 GUI unittest 수행 간단한 툴
- PyCon2018 PyQt로 만드는 웹 기반 어플리케이션 만들기
- Qt 입문자 및 Qt for Python을 위한 작은 소개
- 헬로우 큐트 포 파이썬 (Hello Qt for Python)
- make-a-story
- fbs - build-system.fman.io
- Python and Qt: 3,000 hours of developer insight
- PyQt5 Tutorial : 파이썬으로 만드는 나만의 GUI 프로그램
- PyQt5 및 Qt Designer 설치
- PyQt5 Tutorial - Setup and a Basic GUI Application
- PyQtGraph - Scientific Graphics and GUI Library for Python
- tkinter
Python GUI Development with Tkinter- 076923.github.io/posts/#Python-Tkinter
- 1. tkinter 모듈 시작하기
- GUI with Python's Tkinter, by Robert Jomar Malate
- Learn Tkinter in 20 Minutes
- Learn to Program 20 : TkInter Tutorial
- Learn to Program 21 : TkInter Tutorial 2
- Craft your own GUIs with Python and Tkinter
- How to Program a GUI Application (with Python Tkinter)!
IPython & Jupyter
-
IPython and Jupyter in Depth: High productivity, interactive Python - PyCon 2017
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IPython: An Interactive Computing and Development Environment
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(Window) Jupyter 에서 파이썬 2 & 파이썬 3 동시에 사용하기
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How To Implement These 5 Powerful Probability Distributions In Python
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주피터(Jupyter, IPython >= 3)의 다중 커널 개념 이해하기 - 파이썬2와 파이썬3 동시에 사용하기
-
launchctl을 사용한 맥 OSX에서 서비스 등록하기 - 주피터(Jupyter, IPython >= 3) 노트북 서비스 등록 예제
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How to Scrape Data From Facebook Page Posts for Statistical Analysis
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A Collaborative Real-time iPython Jupyter Client for Self-hosted Jupyter Servers
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How did we serve more than 20,000 IPython notebooks for Nature readers?
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Run Python 2 and Python 3.5 kernels in IPython Jupyter Notebook
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Top 10 IPython Tutorials for Data Science and Machine Learning
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Cython can improve the speed with 1d numpy array in a IPython notebook
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remote access
# server to start jupyter $ jupyter notebook --no-browser --port=7987 # terminal in another server $ ssh -N -f -L localhost:7987:localhost:7987 [user id]@[server] # open browser then type localhost:7987 -
How do I add python3 kernel to jupyter (IPython)
$ sudo /path/to/anaconda3/bin/ipython3 kernel install Installed kernelspec python3 in /usr/local/share/jupyter/kernels/python3 -
!jupyter nbconvert --to python file_name.ipynbwrite at the end of the notebook to save jupyter notebook codes as python file -
conda upgrade notebook동작하지 않음pip install --upgrade notebook- 오류 발생
Cannot remove entries from nonexistent file /path/to/anaconda/lib/python2.7/site-packages/easy-install.pth pip install --ignore-installed --upgrade pip setuptools실행 후 재실행하니 성공
- 오류 발생
-
Top 10 IPython Notebook Tutorials for Data Science and Machine Learning
-
Create Isolated Jupyter Ipython Kernels With Pyenv And Virtualenv
-
Multi-user server for Jupyter notebooks https://jupyterhub.readthedocs.io
-
JupyterHub Tutorial: Set up your Lab, Classroom, or Business
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webia.lip6.fr/~pajot/dataviz.html pandas, matplotlib, numpy, seaborn example
-
Jupyter Notebook Tricks for Data Science that Enhance your efficiency
-
IPython & Jupyter in depth: high productivity interactive and parallel python PyCon 2015
-
A very simple demo of interactive controls on Jupyter notebook
-
How to Automatically Import Your Favorite Libraries into IPython or a Jupyter Notebook
-
Building a Repeatable Data Analysis Process with Jupyter Notebooks
-
PyData Ann Arbor: Madicken Munk | Widgyts: yt Jupyter Widgets for Volumetric Data Exploration
- Binder - Turn a Git repo into a collection of interactive notebooks
- Emacs IPython Notebook
- Hydrogen - an interactive coding environment that supports Python, R, JavaScript and other Jupyter kernels
- ipytracer 알고리즘 시각화 라이브러리 ipytracer 개발기
- jovian.ml - Make Jupyter notebooks commentable collaborative sharable
-
- 주피터 노트북 버전관리 (diff 도 가능)
-
- 주피터 노트북의 버전별, 코드/마크다운 셀별 Comment 기능 (댓글의 댓글도 가능)
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- 프레젠테이션 모드
-
- Colab, Kaggle, Binder 로 원클릭 포팅 및 실행
-
- 다른 사람이 만든 주피터 노트북 탐색
-
- 주피터 노트북 clone시, 필요한 패키지 자동 탐색 및 environment.yml 파일 자동 생성
-
- JupyShare lets you release your notebook to the cloud and gives you a public endpoint for it through ngrok
- JupyterLab - An extensible environment for interactive and reproducible computing, based on the Jupyter Notebook and Architecture
- jupyterlab.readthedocs.io
- JupyterLab: the next generation of the Jupyter Notebook
- JupyterLab: The Next-Generation Jupyter Frontend
- JupyterLab is Ready for Users
pip install jupyterlabconda install -c conda-forge jupyterlab
- 주피터 노트북의 진화!
- A Diagram Editor for JupyterLab
- How to change JupyterLab Theme(Easy Method)
- JupyterLab first impressions
- Jupyter Notebook보다 쉽고 편리하다, Jupyter Lab!
- github jupyterlab-extension
- Jupyter Lab: Evolution of the Jupyter Notebook
- jupyterthemes
- jupyter-vim-binding
- nteract and create with data, words, and visuals jupyter notebook을 web이 아니라 local에서 실행
- Oasis - Data system opens its doors to all Liners
- ob-ipython - org-babel integration with IPython for evaluation
- Papermill is a tool for parameterizing and executing Jupyter Notebooks
- Pineapple - The next generation of scientific notebook. A standalone frontend to IPython for Mac
- polynote - The polyglot notebook with first-class Scala support
- ReviewNB - Code Reviews for Jupyter Notebooks Say Goodbye to messy JSON diffs!
- 주피터 노트북을 깃헙에 올리고, raw 한 환경에서 리뷰하면 JSON 파일. 따라서, 실질적인 리뷰를 하려면 로컬환경이나 Colab 등에 포팅한 다음 validation 체크를 하고, PR을 처리해 줘야 함
- ReviewNB는 깃헙에서 노트북 코드의 리뷰를 실제 노트북이 렌더링 된 상태에서, 직관적으로 할 수 있도록 도와주는 툴
- Public 저장소는 개수 상관없이 무료로 무제한 사용 가능
- "Install GitHub App" 버튼을 누르시고 Free 버전을 마켓플레이스에서 설치하면 ok. 현재 진행중인 PR에 대해 comment, 과거의 PR을 선택하여 노트북이 사이드-바이-사이드로 렌더링된 상태로 diff 확인 가능
- RISE: Live Reveal.js Jupyter/IPython Slideshow Extension
- Rodeo: A data science IDE for Python
- Saturn: Web IDE for Machine Learning http://saturn.proinlab.com
- scikit
- Dive into Machine Learning with ipython notebook and scikit-learn
- Scikit Flow: Easy Deep Learning with TensorFlow and Scikit-learn
- Machine Learning with Scikit Learn | SciPy 2015 Tutorial | Andreas Mueller & Kyle Kastner Part I
- Machine Learning with Scikit Learn | SciPy 2015 Tutorial | Andreas Mueller & Kyle Kastner Part II
- Data science in Python: pandas, seaborn, scikit-learn
- 김도형: 파이썬 데이터 분석 3종 세트 - statsmodels, scikit-learn, theano - PyCon APAC 2016
- 사이킷런 해부학
- Traitlets
- Voila Voila를 사용해 Jupyter Notebook Dashboard 만들기
- Six easy ways to run your Jupyter Notebook in the cloud
- colab.research.google.com 설치 후 keras 사용 가능
- Hello, Colaboratory
- Google Colaboratory를 아시나요?
- Google Cloud Codelabs and Challenges
- Google Colab Free GPU Tutorial
- Neural Networks with Google CoLaboratory | Artificial Intelligence Getting started
- Colaboratory GPU
- Google Colab Free GPU Tutorial
- Fast.ai Lesson 1 on Google Colab (Free GPU)
- Train Your Machine Learning Models on Google’s GPUs for Free — Forever
- EN-FR Machine Translation with Various RNN Models in Google CoLab (1)
- Colab에서 PyTorch 사용하기
- Google Colab의 GPU 정보를 확인해 봤습니다
- 무료 GPU로 파이썬 노트북을 사용할 수 있는 google Drive Colaboratory 소개
- 텐서플로우 백엔드를 사용해서 케라스 상에서 무료 GPU를 사용하는 방법을 알아봅니다
- 구글 드라이브의 Colabortory를 통해 파이썬 데이터 시각화툴(Matplotlib, Seaborn, Altair, Plotly, bokeh) 사용하기
- colab-tf-utils - Simple GDrive-Based model checkpointing from within Google's Colab service
- Google Colab - 구글 드라이브 연동하기
- 구글 콜래보래토리 소개 (revised)
- Colaboratory 에서 pandas.read_csv 시에 한글내용 깨짐
- Google Colab 사용하기
- Colaboratory 사용하기
- google Colaboratory 에서 구글 드라이브에 있는 파일 쉽게 이용하기
- Deep_Learning_3: Importing Kaggle's dataset in Google Colaboratory
- Getting Started With Google Colab - A Simple Tutorial for the Frustrated and Confused
- 코랩 시작하기 file upload, google drive 연동 방법
- Google Colab: how to read data from my google drive?
- Usage TPU in Google Colaboratory
- Object Detection in Google Colab with Fizyr Retinanet
- 구글 Colaboratory에서 Drive 연동
- Google_Colab_tutorial
- DeepLab Demo.ipynb
- The speed of your input pipeline counts .cache를 이용한 속도 향상. ipynb
- 구글 코랩으로 데이터 클리닝, 시각화, 분석 - 가장 인기 있는 지하철 호선은?
- Mecab-ko-for-GoogleColab
- Jupyter Enterprise Gateway
- jupyter.nims.re.kr github api 연동, keras 사용 가능
- notebooks.azure.com 계정에 따라 다른데 login이 자꾸 풀리는 경우가 있음
- Java class를 Python에서 사용하기 결국 subprocess 이야기
- JPype - an effort to allow python programs full access to java class libraries. http://www.jpype.org
- Jython
- VOC - A transpiler that converts Python bytecode into Java bytecode
- Awesome Python - A curated list of awesome Python frameworks, packages, software and resources
- Top 5 Useful Python Libraries Web Developers Can't Live Without
- Scrapy, Zappa, Boto, Requests, Tensorflow
- Command Line
- How to Write Perfect Python Command-line Interfaces — Learn by Example
- Build your own Command Line with ANSI escape codes
- 한종원 : Daily Continuous Deployment를 위한 custom CLI 개발 및 AWS Elastic Beanstalk에 적용하기
- 4 Python libraries for building great command-line user interfaces
- Tools for Writing Python CLI Applications
- simm.py - announcing command line file similarity tool
- soccer-cli - Football scores for hackers. A command line interface for all the football scores
- Python Development: 7 Libraries to Look For in 2017
- My top 5 ‘new’ Python modules of 2015 tqdm, joblib, folium, tinydb, dill
- 10 Python Machine Learning Projects on GitHub
- 9 Python Analytics Libraries
- Machine Learning Exercises In Python, Part 1 python exercises of Andrew Ng's maching learning class on Coursera
- Three Useful Python Libraries for Startups
- Like builtins, but boltons. Constructs/recipes/snippets that would be handy in the standard library. Nothing like Michael Bolton
- 50 Popular Python open-source projects on GitHub in 2018
- Top 10 Python Web Frameworks to Learn in 2018
- A Beginner’s Introduction to Python Web Frameworks
- 11 new Python web frameworks
- Learning A New Data Science Language Pandas, Framequery, SciKit-Learn, Pandas-gbq
- 모든 파이썬 프로그래머를 위한 20가지 실용적인 파이썬 라이브러리
- 아파치 Libcloud, 애로우(Arrow), 비홀드(Behold), 보틀(Bottle), EbookLib, 구이(Gooey), 인보크(Invoke), 누이트카(Nuitka), 눔바(Numba), 피위(Peewee), 필로우(Pillow), 파이파일시스템(PyFilesystem), 파이게임(Pygame), 파이글릿(Pyglet), 파이인스톨러(PyInstaller), 파이심플GUI(PySimpleGUI), 파이썬-docx, 스크래피(Scrapy), Sh, 스플린터(Splinter)
- Let’s Build A Web Server
- The Python3 Package Creator
- Magnificent app which corrects your previous console command
- PROBABILISTIC M2M RELATIONSHIPS USING BLOOM FILTERS pyhash, bitstring
- Top 20 Python Machine Learning Open Source Projects
- Top 10 Python libraries of 2016
- Don’t Miss out on these 24 Amazing Python Libraries for Data Science
- 파이썬 활용, 파이썬 프로젝트로 할 수 있는 일들을 알아보자!
- Top 10 Python libraries of 2019
- Abseil Python Common Libraries
- Advanced Python Scheduler
- AGATE: A BETTER DATA ANALYSIS LIBRARY FOR JOURNALISTS
- Ajgu - a simple graph database power by BerkleyDB key-value store
- anaconda - http://continuum.io/downloads
- install
- Conda Package Repository
- conda.pydata.org
conda install -c anaconda cx_oracle- might need to proxy
https_proxy=http[s]://x.y.z.w:port ... - might need to execute after
sudo -i
- might need to proxy
- jjhelmus
- 파이선 가상환경 콘다 시작하기
- 아나콘다 가상환경
- conda tab completion (자동완성) 만들기
- practice - 다른 버전의 파이썬 설치하고 사용하기
- How to Start a Data Science Project in Python
- 데이터 분석을 위한 기본적인 Python 환경 설정 방법
- Anaconda의 Conda를 활용해 분리된 환경 설정
- 하나의 Python 데이터 분석 프로젝트의 디렉토리를 구성하는 방법
- Python Tutorial: Anaconda - Installation and Using Conda
- Python - Install Anaconda, Jupyter Notebook, Spyder on Windows 10
- How To Install Anaconda!
- Install Python 🐍 with Anaconda: Jupyter Notebook and Spyder
- What is Anaconda? Install Anaconda On Windows
- Install Python (Anaconda) on Windows + Setting Python and Conda Path (2017)
- how to install anaconda python on windows 10
- How to Download and Install Python 3.6 on Windows 10
- Advanced Features of Conda Part 1
- Advanced Features of Conda Part 2
- Conda에 대한 간단 고찰 및 mac에서 Jupyter notebook 시 오류 해결
- Why you need Python environments and how to manage them with Conda
- conda 환경에서 pip 패키지도 동시에 업데이트 하기
conda install accelerateHow to put that GPU to good use with Python
- Data Science for Losers
- LEARNING PYTHON FOR DATA SCIENCE: CHEAT SHEETS
- Python Anaconda & GPU - 세팅 및 성능 비교
- 초간단 머신러닝 개발 환경 세팅하기 (with 아나콘다)
- Accelerate Python Performance Powered by Anaconda
- Anaconda-Python 환경에서 VSCode를 사용하는 방법(프로젝트 생성, 환경 구축, 디버깅)
- 데이터 분석을 위한 파이썬 개발환경 구축 (Windows)
- How to get started with Python for Deep Learning and Data Science
- angr is a framework for analyzing binaries
- API-Hour - Write efficient network daemons (HTTP, SSH...) with ease. http://pythonhosted.org/api_hour
- Asyncio Time Travel Loop
- asyncwsgi
- Autologging — easier logging and tracing for Python classes
- Autowire - light & simple dependency injection library for Python
- Bake — the strangely familiar workflow utility makefile과 비슷하게 bakefile을 통해 작업 처리. automation
- BARF : A multiplatform open source Binary Analysis and Reverse engineering Framework
- bcrypt Hashing passwords with Python and Bcrypt
- BeeWare - The IDEs of Python
- Bin Packing Algorithm http://towry.me
- bioread - for reading the files produced by BIOPAC's AcqKnowledge software
- Bokken - Open Source Reverse Code Engineering
- Bolt - an open source library providing a Python interface to ndarrays backed by local or ditributed implementations
- BoopSuite - A Suite of Tools written in Python for wireless auditing and security testing
- Boost.Python
- bpython - A fancy curses interface to the Python interactive interpreter http://bpython-interpreter.org
- BTables: A fast, compact disk format for machine learning
- c8d - A Chip-8 disassembler in Python
- castervoice - On Voice Coding
- Celery
- Introduction to Celery
- Introduction to Celery
- Three quick tips from two years with Celery
- Celery 관련 기사/튜토리얼/How-To를 읽고 메모한 내용
- Asynchronous Tasks With Django and Celery
- Celery 4.0의 주요 변경사항 정리
- 파이썬 동시성 프로그래밍 - (6) 분산 (celery)
- Celery를 이용한 긴 작업 처리
- Real time celery monitoring using websockets https://wscelery.readthedocs.io
- Checklist to build great Celery async tasks
- Celery로 TelegramBot 알림 보내기
- 셀러리: 시작하기
- 셀러리 입문하기
- Asynchronous Tasks in Python - Celery Backend Tutorial
- Asynchronous Tasks in Python - Getting Started With Celery
- Celery 관련 기사/튜토리얼/How-To를 읽고 메모한 내용
- Flower - Celery monitoring tool
- cffi
- Clutterm - A clutter based terminal written in pure python (no vte lib)
- colout - a simple command to add colors to a text stream in your terminal
- Conductor - A system for testing distributed systems across a network
- conference-tracker - Minimal-maintenance conference tracker
- Connexion - a framework that automagically handles HTTP requests based on OpenAPI Specification (formerly known as Swagger Spec) of your API described in YAML format
- Coverage.py 4.0
- CPython
- CPython internals: A ten-hour codewalk through the Python interpreter source code
- CPython internals: A ten-hour codewalk through the Python interpreter source code
- Escaping a Python sandbox with a memory corruption bug
- Back to the Low Level
- Python Is Fast!
- Peephole: CPython은 어떻게 코드를 최적화하는가
- Kavya Joshi The Memory Chronicles A Tale of Two Pythons PyCon 2017
- A fantastic dive into the internals of how CPython and Micropython manage memory differently
- Under the C
- CPython internals: why bother? (James Powell)
- Why Python's The Best Language For AI (and How To Make It Even Better)
- Dynamic Code Instrumentation with Hacked Interpreters || James Powell
- Blurb-it is now available CPython contribution 방법
- Jean Baptiste Aviat Writing a C Python extension in 2017 PyCon 2017
- credstash - A little utility for managing credentials in the cloud
- Chromote - Simple wrapper to drive Google Chrome from Python using the Remote Debugging Protocol 1.1 API
- cx_Oracle - PYTHON – CX_ORACLE THROWS MISSING LIBCLNTSH.SO.11.1 WHEN EXECUTED BY DJANGO-CHRONOGRAPH
- cython
- cython
- Speeding up non-vectorizable code with Cython
- Fast Python loops with Cython
- Easy wins with Cython: fast and multi-core by Caleb Hattingh
- CYTHON JOURNEY
- WRAPPING MAPLESIM C CODE FOR PYTHON
- Cython Tutorial - Bridging between Python and C/C++ for performance gains
- Cython: Speed up Python and NumPy, Pythonize C, C++, and Fortran, SciPy2013 Tutorial, Part 1 of 4
- Cython: Blend the Best of Python and C++ | SciPy 2015 Tutorial | Kurt Smith
- Pycon 2016: Fast Python! Don't Bother?
- Parallel Python – Making Code Run 2000x Faster
- Alex Orlov Cython as a Game Changer for Efficiency PyCon 2017
- Achieving C-like performance in Python without Cython or other libraries?
- Protecting Python Sources With Cython
- dash - a Python framework for building analytical web applications. No JavaScript required
- Dask Dask provides advanced parallelism for analytics, enabling performance at scale for the tools you love
- Datajoy - Python & R, for scientists Easy to use, online data processing with Python and R
- DataMatrix - an intuitive Python library for working with column-based and continuous data
- dateutil - powerful extensions to datetime
- Dedupe de-duplication and entity resolution quickly on structured data
- DET (extensible) Data Exfiltration Toolkit
- DiffPy - Atomic Structure Analysis in Python A free and open source software project to provide python software for diffraction analysis and the study of the atomic structure of materials
- docx Microsoft Office Word 2007
- DoGelang
- dontasq - Extend built-in Python collections with LINQ-for-objects style methods
- Edward is a Python library for probabilistic modeling, inference, and criticism
- Elizabeth - a Python library, which helps generate mock data for various purposes. This data can be particularly useful during software development and testing. http://lk-geimfari.github.io/elizabeth
- enaml - Declarative User Interfaces for Python
- Eric - a full featured Python editor and IDE, written in Python
- extruct is a library for extracting embedded metadata from HTML markup
- fabric
- Faster CPython FAT Python
- Faust - A library for building streaming applications in Python
- fbchat: Facebook Chat (Messenger) for Python
- Feather: A Fast On-Disk Format for Data Frames for R and Python, powered by Apache Arrow
- FinTech package for Python (SEPA, EBICS & more)
- [flake8 - a python tool that glues together pep8, pyflakes, mccabe, and third-party plugins to check the style and quality of some python code]((https://gitlab.com/pycqa/flake8)
- Flanker - an open source parsing library written in Python by the Mailgun Team
- flexx - Python UI tookit based on web technology http://flexx.readthedocs.org
- flickrd - 파이썬3으로 작성한 플리커 사진 다운로드 프로그램
- FilterPy - a Python library that implements a number of Bayesian filters, most notably Kalman filters
- GDB dashboard - Modular visual interface for GDB in Python
- gevent - Coroutine-based concurrency library for Python http://gevent.org
- Ghost.py - Webkit based scriptable web browser for python. http://ghost-py.readthedocs.org
- GOOGLER: NOW YOU CAN GOOGLE FROM LINUX TERMINAL!
- google API
- Google-Search-PDF-Crawler-pdf2txt-
- goSecure - an easy-to-use and portable Virtual Private Network (VPN) solution
- goto - A function decorator to use goto in Python
- gping - Ping, but with a graph
- Grumpy: Go running Python
- happybase
- HASK - Haskell language features and standard libraries in pure Python
- hazelnut - an APACHE licensed library written in Python designed to provide a simple and pythonic way to parse the /proc/meminfo file on LINUX based systems
- High-Frequency-Trading-Model-with-IB - A high-frequency trading model using Interactive Brokers API with pairs and mean-reversion in Python
- highlander - There can be only one... process
- howdoi - 파이썬 유틸 howdoi 분석
- htsint: a Python library for sequencing pipelines that combines data through gene set generation
- HTTPie: a CLI, cURL-like tool for humans
- Hy
- Ibis: Scaling the Python Data Experience
- Informer (TGInformer) - a bot library that allows you to masquerade as multiple REAL users on telegram and spy on 500+ Telegram channels per account
- Instagram-API-python
- Instagram Private API - A Python wrapper for the Instagram private API with no 3rd party dependencies. Supports both the app and web APIs
- invoice2data - Data extractor for PDF invoices
- iterfzf: Pythonic interface to fzf
- Japronto! - screaming-fast, scalable, asynchronous Python 3.5+ web micro-framework integrated with pipelining HTTP server based on uvloop and picohttpparser
- Jellyfish - a python library for doing approximate and phonetic matching of strings
- json streamer - A fast streaming JSON parser for Python that generates SAX-like events using yajl
- Kanna makes html components easier to display. like table, panel, etc
- KeePassC is a curses-based password manager compatible to KeePass v.1.x and KeePassX
- Keras: Theano-based Deep Learning library
- KicomAV
- Kite - Your programming copilot Kite augments your coding environment with all the internet’s programming knowledge
- Kore4 and Python
- Krill - The hacker's way of keeping up with the world
- LemonGraph - a log-based transactional graph (nodes/edges/properties) database engine that is backed by a single file
- Levenshtein Automata implementations
- LanderDB - An embedded database engine written in Python
- libtclpy - This is a Tcl extension to effortlessly to call bidirectionally between Tcl and Python, targeting Tcl >= 8.5 and Python 2.6 - 2.7
- LightNet: Bringing pjreddie's DarkNet out of the shadows
- logcoin - A toy crypto-currency based on a discrete logarithm zero-knowledge protocol, in <95 lines
- logpy - Logic Programming in Python
- Lomond
- Luigi - Batch data processing in Python
- Managing Containerized Data Pipeline Dependencies With Luigi
- Luigi 예제
- Jonathan Dinu: Scalable Pipelines with Luigi or: I’ll have the Data Engineering, hold the Java!
- Intro to Building Data Pipelines in Python with Luigi
- Luigi, The Friendly Pipeline Plumber by IanMLewis
- Using Luigi Pipelines in a Data Science Workflow
- Luigi workflow engine을 사용하여 기계 학습 파이프 라인을 작성하는 데 필요한 예제 코드 포함
- 예제의 주요 기능은 Apache MADlib (incubating)
- Luigi 태스크의 PL/pgSQL을 통해 실행
- Data pipelines, Luigi, Airflow: everything you need to know
- Create your first ETL in Luigi
- lupa - Lua in Python http://pypi.python.org/pypi/lupa
- macropy - Macros in Python: quasiquotes, case classes, LINQ and more!
- Magic Python - a package with preferences and syntax highlighter for cutting edge Python 3, although Python 2 is well supported, too
- Mani - a distribued cron like scheduler
- Memspector - Inspect memory usage of python functions
- MicroPython
- minikeyvalue
- miracle-ad - AAA 중 Authorization 관련 모듈 - miracle-acl
- MORPHiS is a global encrypted distributed datastore intended to replace the cloud for storage and far more
- MySQL-python
- practice - installation on Redhat & Ubuntu
- practice - installation on macos sierra
- Escaping Strings for MySQL in Python 난 잘 되지 않음
- A quick guide to using MySQL in Python
- Python MySQL Tutorial
- Unofficial Windows Binaries for Python Extension Packages
- Insert / Retrieve file and images as a Blob in MySQL using Python
- natsort - Simple yet flexible natural sorting in Python
- NBAPB (Blog Auto Posting Bot)
- NetworkX -> graph
- NeuPy - Neural Networks in Python
- Neural Doodle - Use a deep neural network to borrow the skills of real artists and turn your two-bit doodles into masterpieces
- Numba
- Nuitka - the extremely compatible Python compiler
- Ohmu - View space usage in your terminal
- oneliner - Convert any Python file into a single line of code
- Opnieuw: A simple and intuitive retrying library for Python
- Orator - AN ACTIVERECORD ORM FOR PYTHON
- Oxyry Python Obfuscator
- p - Dead Simple Interactive Python Version Management
- Pampy: The Pattern Matching for Python you always dreamed of
- paramiko
- Passpie: manage login credentials from the terminal
- pattern.graph
- PeachPy is a Python framework for writing high-performance assembly kernels
- Pendulum - PYTHON DATETIMES MADE EASY
- petl - Extract, Transform and Load (Tables of Data) — petl 1.1.1
- PewSQL - Analytics Done inside RDBMS
- plotline - A Grammar of Graphics for Python based on ggplot2
- plydata is a library that provides a small grammar for data manipulation
- pomegranate - a package for graphical models and Bayesian statistics for Python, implemented in cython
- Pseudo takes an algorithm / a simple program and generates idiomatic code for it in Python, JavaScript, C#, Go and Ruby
- Ptop - An awesome task manager written in Python !
- ptracer - A library for ptrace-based tracing of Python programs https://ptracer.readthedocs.io
- PTVS - Python Tools for Visual Studio https://microsoft.github.io/PTVS
- pullbox - A dead-simple dropbox alternative using Git
- Pulsar - Concurrent framework for Python
- pyahocorasick - a fast and memory efficient library for exact or approximate multi-pattern string search
- py-ascii-graph - A simple python lib to print data as ascii histograms
- pyClamd - use ClamAV antivirus from Python
- PyCryptodome
- PycURL - Python interface to libcurl http://pycurl.io
- pyDash - A Python App For Monitoring Your Linux Server
- PyDataSentry - Memory for Data Science
- pydbgen
- PyEBPF — eBPF proxy routines generation and Python callbacks (iovisor/bcc wrapper)
- pyexperiment - Run experiments with Python - quick and clean
- PyFormat - Using % and .format() for great good!
- PyFuzz2 - My little fuzzing framework inspired by grinder
- pygal chart
- pygit: Just enough of a Git client to create a repo, commit, and push itself to GitHub
- py-googletrans - Free Unofficial Google Translate API for Python. Translates totally free of charge. http://py-googletrans.rtfd.org/en/latest/googletrans.html
- pyhwp - .hwp file format v5 parser in python http://pythonhosted.org/pyhwp
- pyinotify
- PyInstaller is a program that freezes (packages) Python programs into stand-alone executables, under Windows, Linux, Mac OS X, FreeBSD, Solaris and AIX
- pyjs is a Rich Internet Application (RIA) Development Platform for both Web and Desktop. With pyjs you can write your JavaScript-powered web applications entirely in Python
- Pykka - a Python implementation of the actor model
- pyldap
- pylearn2-practice
- Pylint - Star your Python code!
- Pylons
- PyMC: Bayesian Stochastic Modelling in Python http://pymc-devs.github.com/pymc
- PyMySQL
- Pymunk - a easy-to-use pythonic 2d physics library that can be used whenever you need 2d rigid body physics from Python
- pyo3 - Rust bindings for the Python interpreter
- pyOpenCL
- pyOpt - a Python-based package for formulating and solving nonlinear constrained optimization problems in an efficient, reusable and portable manner
- pypapago 개발기
- pyparsing
- PyPatt: Python Pattern Matching
- PyPinkSign - Small python code for K-PKI certificates. 공인인증서를 다루는 파이선 코드
- PyPy.js - an experiment in building a fast and compliant python environment for the web
- pyrax Creating Cloud Servers using Python & Pyrax
- pyscale - Predicting Application Workload via Extreme Value Analysis
- pysftp a kind of wrapper of paramiko
- Pyston - an open source Python implementation that aims to be both highly compatible and high-performance
- PyStruct - Structured Learning in Python
- Python tools for Vivado Projects
- Python Wheels
- Pythran
- PyTongue - Write python in any language
- PyTree - a python package, which you can use to generate trees, realistic or fractal one. However the whole pricipale is based on fractals
- pyvim - Pure Python Vim clone
- Pyxley: Python Powered Dashboards
- PyV8 - a python wrapper for Google V8 engine
- PyVNCs - Simple command line multiplatform python VNC Server
- QPython
- quack - Build system on top of build systems
- Ray - a fast and simple framework for building and running distributed applications
- readchar - Utilities to read single characters and key-strokes
- readability - fast python port of arc90's readability tool, updated to match latest readability.js!
- Remap: Nested Data Multitool for Python
- REMOVESTAR Tool to automatically replace 'import *' in Python files with explicit imports
- Requests - an elegant and simple HTTP library for Python, built for human beings
- Advanced Usage
- practice - requests vs. http client speed
- practice - download file
- api
timeout=(connect timeout, read timeout)
- 매우 큰 파일을 --data-binary로 보낼 때는 적절한 크기로 file을 나눠서 여러 번 호출하는 방법밖에 없는 거 같음
- mmap을 사용해서도 해보려고 했지만, mmap object를 그냥 넘겨주는 건 되도, mmap의 일부를 읽으면 str이 되거나 다시 file로 저장해야 하기 때문에 결국 다를 바 없음
- Line Notification with python
pip install --upgrade requests[security]- PYTHON: USING THE
REQUESTSMODULE TO DOWNLOAD LARGE FILES EFFICIENTLY - 네이버 실시간 급상승 크롤링
- 네이버 실시간 급상승 크롤링 02
- asynchronous requests
- How I used Python to find interesting people to follow on Medium
- Requests' secret: pool_connections and pool_maxsize
- Python Requests Throttle
- The right way to use requests in parallel in Python
- Python parallel http requests using multiprocessing
- Make sessions safer in multi-process environment
- Requests hang multiprocessing
- Cory Benfield Requests Under The Hood PyCon 2017
- not so much about the requests library per se than about tradeoffs in programming, handling of exotic edge cases and an exercise in pragmatism
- requests-file requests에서 file://... 로컬 URL 내용 가져오기
- requests-mock provides a building block to stub out the HTTP requests portions of your testing code
- Python Tutorial: Write a Script to Monitor a Website, Send Alert Emails, and Reboot Servers
- LINE Messaging API 사용해보기(2)
- 아이패드 PYTHONISTA 어플로 구글번역 EXTENSION 만들기
- retroactive - Fun with time travel: Implementing retroactive data structures in Python http://python-retroactive-data-structures.readthedocs.org
- RIBOSOME - A simple generic code generation tool
- RiceDB – A simple, portable configuration file manager
- rlundo - interactive interpreters magical undo powers
- Rosalind is a platform for learning bioinformatics and programming through problem solving
- RPyC - Transparent, Symmetric Distributed Computing remote python call
- RPython
- runcython - Making cython as easy as python
- Ryu component-based software defined networking framework http://osrg.github.io/ryu
- RxPy
- Sake - A self-documenting build automation tool
- schedule - Python job scheduling for humans
- schema - a library for validating Python data structures
- Scrapy
-
proxy 설정을 통해 해결 cf. scrapy-not-scraping-https@stackoverflow
localhost: ssh_exchange_identification: Connection closed by remote host scrapy tcp connection timed out 110 connection timed out scrapy scrapy.core.downloader.handlers.http11.TunnelError: Could not open CONNECT tunnel
-
- ShinySDR - This is the software component of a software-defined radio receiver
- ShivyC - C compiler created in Python
- SimpleSQLite - Python library to simplify the table creation and data insertion in SQLite database (Automatic table creation from data. Support various data type for insertion: dictionary/namedtuple/list/tuple) http://simplesqlite.readthedocs.org/en/stable/apis/simplesqlite.html
- SlopPy: An error-tolerant Python interpreter that facilitates sloppy programming
- Slouchy uses your webcam to check if you're slouching and alert you if you are
- Snake - Full Python Scripting in Vim
- Snakebite is a python library that provides a pure python HDFS client and a wrapper around Hadoops minicluster
- SnoPy - Snobol Pattern Matching Extension for Python
- sofi - an OS agnostic UI module for Python
- Sorted Containers sorted collections type
- spidermonkey - Python/JavaScript bridge module, making use of Mozilla's spidermonkey JavaScript implementation
- SQLAlchemy
- sqlbuilder
- sqlbuilder.readthedocs.io
- practice - sqlbuilder 간단히 test해봤는데 python에서 호출할 query를 만드는 데는 확실히 유용할 거 같음
- stackhut
- Supervisor: A Process Control System Supervisor is a client/server system that allows its users to monitor and control a number of processes on UNIX-like operating systems
- Talk Python To Me - A podcast on Python and related technologies
- Template Engine
- TermFeed - Terminal Feed is a minimal feed reader for the terminal (without curses)
- terminal-palette - A simple library to color texts in terminal
- TextBlob Sentiment: Calculating Polarity and Subjectivity
- textsearch - Find strings/words in text; convenience and C speed
- TAICHI: OPEN-SOURCE COMPUTER GRAPHICS LIBRARY
- Thonny - Python IDE for beginners
- tomorrow - Magic decorator syntax for asynchronous code in Python
- topydo - A command-line todo list application using the todo.txt format
- Tornado
- tox
- tqdm A Fast, Extensible Progress Meter (progress bar)
- Tesseract-OCR
- transcript - Python 3.6 to JavaScript compiler - Lean, fast, open! - http://www.transcrypt.org
- transducers-python
- transition 유한 상태 기계를 Django에 적용하여 상태 변경을 관리하기
- TrumpScript parser, tokenizer, compiler 참고
- Twisted Introduction
- Twitter
- Twitter API tutorial
- rainbowstream - A Twitter client on terminal
- Retweet automatically retweets tweets from a Twitter user
- Writing a Console Twitter Client in Python
- Create A Twitter Bot With Python
- 트위터 언팔로워 트래커
- Build A Twitter Bot With Python That Gets You Followers
- Accessing the Twitter API with Python
- TwoTerm - Simple side-by-side terminal program. PyQt4/PyQt5 based. Python2/Python3
- uBiome Open Source - A place for microbiome enthusiasts to share tools, tips, sequences, and more
- Undebt is a fast, straightforward, reliable tool for performing massive, automated code refactoring used @Yelp
- uvicorn - The lightning-fast asyncio server, for Python 3. 🦄 http://www.uvicorn.org
- uvloop is a fast, drop-in replacement of the built-in asyncio event loop
- Uzi - an stunning Ransomeware due to its features
- vaex - Out-of-Core DataFrames for Python, ML, visualize and explore big tabular data at a billion rows per second. https://vaex.io
- Vaex: A DataFrame with super strings spark보다 빠르다는 benchmark
- A Billion Rows A Second - Working with BIG! data in Python
- validus - A dead simple Python data validation library. It supports Python 3 only
- vtcheck - Virus Total API Python Script
- Vy - A vim-like in python made from scratch
- Watchdog Python API library and shell utilities to monitor file system events
- Wavelet rasterization is a method for analytically calculating an anti-aliased rasterization of arbitrary polygons or shape bounded by Bezier curves
- wdb - An improbable web debugger through WebSockets
- websockets - a library for building WebSocket servers and clients in Python with a focus on correctness and simplicity
- Whoosh
- wrapt - A Python module for decorators, wrappers and monkey patching
- wttr.in - Web frontend for wego terminal에서 curl로 날씨 확인
- xarray - N-D labeled arrays and datasets in Python
- xincapio - Get IP address, MAC address and Disk Serial Number
- xonsh shell a Python-powered, cross-platform, Unix-gazing shell language and command prompt
- xs-vm - eXtremely small virtual machine written in Python
- yosai - A Security Framework for Python Applications
- youtube-dl - Command-line program to download videos from YouTube.com and other video sites
- YTFS - File system which enables you to search and play movies from YouTube as files - with tools of your choice
- cachetools - Extensible memoizing collections and decorators
- methodtools.lru_cache functools.lru_cache가 classmethod나 staticmethod에 대해 제대로 동작하지 않아 이를 보완하기 위해 작성했다고 함
- Ring - Cache interface as a programming language integration
- supycache - Simple yet capable caching decorator for python
- Quick & Simple Call Graphs in Python
- Callgraph - a Python package that defines a decorator, and Jupyter magic, to draw dynamic call graphs of Python function calls
- Call Map: A Tool for Navigating Call Graphs in Python
- Code2graph: Automatic Generation of Static Call-Graphs for Python Source Code
- Pyan3: Offline call graph generator for Python 3
- pycallgraph - call graph visualizations for Python applications
pycallgraph [--max-depth=n] [--include "path.to.*"] graphviz -- <python src>
- 10 Python image manipulation tools
- Image Text Recognition in Python
- Ravi Chityala, "Image processing using Python", PyBay2016
- Create ASCII Art Text Banners in Python
- CNN-Image-Processing - Python module for image processing using cellular neural networks (CNN)
- gif2txt - Gif image to to Ascii Text. (Just a toy)
- img2txt - Image to Ascii Text, can output to html or ansi terminal
- imgaug - Image augmentation for machine learning experiments. http://imgaug.readthedocs.io
- Legofy - a python program that takes a static image or gif and makes it so that it looks as if it was built out of LEGO
- PIL
- Pillow, the friendly PIL fork
- PyCNN - Image Processing in Cellular Neural Networks with Python
- SIPSkia : Simple Image Processing by Skia
- My Python Development Environment, 2020 Edition
- pex - a library for generating .pex (Python EXecutable) files which are executable Python environments in the spirit of virtualenvs
- pip
-
apt-get install -y python-dev python-pipfatal error: Python.h: No such file or directoryyum install epel-release -y && yum install python-pip -y && yum install python-devel -yHow to install python-pip in CentOS7 Docker Container
-
"pip -t": A simple and transparent alternative to virtualenv
-
pip --index-url/--trusted-host옵션 자동 지정$ cat requirements.txt --index-url http://my.pypi.internal/index --trusted-host my.pypi.internal myteam.common==0.0.1 ...
-
- Python: beyond the basics I - pip, virtualenv, pipenv & list comprehensions
- pipenv
- pipreqs - Generate pip requirements.txt file based on imports of any project
- pipwin
pip install pipwin& e.g.pipwin install opencv-python- www.lfd.uci.edu/~gohlke/pythonlibs에 올려져있는 윈도우용 whl 파일을 pip 와 비슷하게 설치
- Poetry - Python dependency management and packaging made easy. https://poetry.eustace.io
- pyenv
- pyenv Tutorial
- 맥에서의 파이썬 개발 환경 자동화(pyenv, virtualenv, autoenv)
- pyenv, virtualenv, autoenv 를 사용하여 Python 개발환경 구축하기
- pyenv, virtualenv, autoenv를 활용한 자동화 구현하기
- pyenv + virtualenv + autoenv 를 통한 Python 개발 환경 구축하기
- PYTHON: PYENV, PYVENV, VIRTUALENV – WHAT’S THE DIFFERENCE?
- pyenv, conda, virtualenv, pip, autoenv
Pyenv 와 Virtualenv 를 이용한 Python 패키지 및 버전 의존성문제 해결- pyenv와 virtualenv를 사용한 파이썬 개발환경 구성
- Python 실전 개발 생태계 pyenv, docker
- virtualenv
- practice - use virtualenv in shell script
- How To Setup Python Virtualenv on Ubuntu 15.04
- 독립적인 가상의 파이썬 실행환경, virtualenv (1)
- 독립적인 가상의 파이썬 실행환경, virtualenv (2)
- pip와 virtualenv를 이용한 파이썬 디플로이먼트
- python virtual environment setup in ubuntu
- 개발환경 구축하기
- 파이썬 프로젝트 시작하기 - Virtualenv
- Virtualenv/VirtualenvWrapper OS별 설치&이용법
- Connect virtualenv
- 파이썬의 개발 “환경”(env) 도구들
- Python 개발환경 구성
- 파이썬의 실행 환경을 지탱하는 도구들
- dh-virtualenv - a tool that aims to combine Debian packaging with self-contained virtualenv based Python deployments
- Virtualenv 설치 및 dependencies 관리하기
- Python Virtual(Isolated) Environments
- 파이썬 가상환경(virtualenv)만들기
- Python Virtual Environments made easy
- Comparing Python Virtual Environment tools
- Virtual Environments in Python Made Easy
- The Python Package Dreamteam
- Python Virtualenv with Hadoop Streaming
- 가상환경 virtualenv(1)
- 가상환경 virtualenv(2) - 실행/설치/관리
- 가상환경 virtualenv(3) - 설치 패키지 사용하기
- How to use Python virtualenv
- curses
- npyscreen
- picotui - Lightweight, pure-Python Text User Interface (TUI) widget toolkit with minimal dependencies. Dedicated to the Pycopy project. https://github.com/pfalcon/pycopy
- PyInquirer - A Python module for common interactive command line user interfaces
- Urwid - Console user interface library for Python
- Scaling Python Microservices with Kubernetes
- BUILDING MICROSERVICES WITH PYTHON AND FLASK
- Miguel Grinberg - Microservices with Python and Flask - PyCon 2017
- Python in Serverless Architectures
- Armada is a complete solution for development, deployment, configuration and discovery of microservices
- Chalice Python Serverless Microframework for AWS
- Python Serverless Microframework, Chalice 사용하기, 01
- Python Serverless Microframework, Chalice 사용하기, 02
- Python Serverless Microframework, Chalice 사용하기, 03
- Python Serverless Microframework, Chalice 사용하기, 04
- Python Serverless Microframework, Chalice 사용하기, 05
- Python Serverless Microframework, Chalice 사용하기, 06
- Python Serverless Microframework, Chalice 사용하기, 07
- Python Serverless Microframework, Chalice 사용하기, 08
- Nirum: IDL compiler and RPC/distributed object framework for microservices http://nirum.org
- Somata - a protocol and framework for building software on a network of connected microservices
- MOOC: Python (파이썬 강좌)
- K-MOOC: Python
- K-MOOC Operation Research : Numpy Part #1
- Quantitative Economics with Python
- Sungchul Lee 연대 수학과 교수
- Microsoft: We want you to learn Python programming language for free
- Python for Beginners
- Music Genre Classifier
- 파이썬으로 계이름 맞히기
- cherrymusic - Stream your own music collection to all your devices! The easy to use free and open-source music streaming server http://www.fomori.org/cherrymusic
- Librosa - audio and music processing in Python
- 파이썬 데이터 사이언스 Cheat Sheet: NumPy 기본
- あなたのデータサイエンス力を 飛躍的に向上させるNumPy徹底入門
- Python Basics for Data Science
- Python Numpy Tutorial
- Python Numpy Tutorial
- NUMPY TUTORIAL : STEP BY STEP GUIDE
- cs228-python-tutorial.ipynb
- NumPy Tutorial: Data analysis with Python
- 100 numpy exercises
- 100 numpy exercises (100% complete)
- NumPy Exercises
- NumPy Cheat Sheet: Data Analysis in Python
- github.com/zerosum99/python_numpy
- How to pip install NumPy in two seconds flat
- Blaze translates a subset of modified NumPy and Pandas-like syntax to databases and other computing systems
- Peak detection in the Python world
- 파이썬 + Numpy + 선형대수 기초 + 이해하기 20160519
- Chapter 4. Numpy 기본 : 배열과 벡터 계산
- Python numpy 기초 - 선형대수학 풀어보기
- Python numpy pandas matplotlib 이해하기 20160815
- TF-KR 첫 모임: Zen of NumPy
- numpy
- 파이썬에 numpy 설치하기 For Windows
- Numpy
- GT-Py: Accelerating NumPy Programs with Minimal Programming Effort
- Practical Tutorial on Data Manipulation with Numpy and Pandas in Python
- Numexpr - a fast numerical expression evaluator for NumPy
- tinynumpy - A lightweight, pure Python, numpy compliant ndarray class
- Data Analysis with Python
- 머신러닝을 위한 기초 수학 살펴보기
- numpy 맛보기
- Why you should start using .npy file more often…
- 파이썬으로 데이터 분석하기 #4-1
- NumPy와 C++ Extensions의 성능 비교
- NumPy와 C++ Extensions의 성능 비교
- NumPy Python Tutorial 2018
- python1010 azure notebooks
- einsum
- Mars Alibaba Open-Sources Mars to Complement NumPy
- PyData Tel Aviv Meetup: Creating Meaningful Features from Clickstream Data - Shir Meir Lador
- numpy tutorial
- Numpy — Python made efficient
- A Visual Intro to NumPy and Data Representation
- Python NumPy Tutorial for Beginners
- Numpy: What Has Changed and What Is Going To Change?
- Data Engineering with Python Numpy & Pandas
- Pythonic Data Cleaning With Pandas and NumPy
- 파이썬(python) numpy 의 array(ndarray)와 matrix 데이터 타입
- practice
- read excel
data.iloc[:,0:8].values.tolist()행은 모두 사용하고, 열은 [0,8]만 추출해서 리스트로 변환data = pd.read_csv("pima-indians-diabetes.csv", encoding = 'euc-kr', [header=None])header=None 첫 번째 행을 헤더가 아니라 데이터로 간주- Visualization of pd.DataFrame as a Markdown format
- Pandas Profiling
- 판다스 기초
- Pandas 팬더스 강의 기초 실습
- 10 Minutes to pandas
- Data analysis in Python with pandas
- Pandas Cheat Sheet: Data Wrangling in Python
- Data Wrangling with pandas Cheat Sheet
- github.com/zerosum99/python_pandas
- pandas.pivot_table
- Data Munging with Pandas - John Fries, CTO, OpenMail
- Ultimate guide for Data Exploration in Python using NumPy, Matplotlib and Pandas
- Pandas writing dataframe to CSV file
- Improving Pandas’s Excel Output
- Updated: Using Pandas To Create an Excel Diff
- Bringing the python data stack to the shell prompt
- Discovery Engines: Statistical Learning with Python and pandas
- Efficient Tabular Storage
- Pandas Categoricals
- Adding a Simple GUI to Your Pandas Script
- 스타워즈 TATOOINE행성의 비밀
- Pandas 기초 이해하기 20160422
- Pandas 이해하기 20160423
- Pandas series 이해하기 20160425
- Pandas data frame 이해하기 20160425
- Pandas data frame 이해하기 2편 20160501
- GroupBy-fu: improvements in grouping and aggregating data in pandas
- troubleshooting
pd.read_csv('filename', error_bad_lines=False)Python Pandas Error tokenizing datapandas.parser.CParserError: Error tokenizing data. C error: Buffer overflow caught - possible malformed input file.read_csv C-engine CParserError: Error tokenizing data 제대로 해결되지 않는 경우가 있음
- An Introduction to scientific python: Pandas
- Data Analysis with Python and Pandas
- Data Analysis w/ Python 3 and Pandas
- IO Tools (Text, CSV, HDF5, ...)
- 네이버 파이낸스 - 재무제표 크롤링
- (Daum부동산) DataFrame 행 추출과 컬럼으로 합치기
- PublicDataReader - 부동산 데이터 수집하기
- Python & JSON: Working with large datasets using Pandas
- pandas.pydata.org/pandas-docs/stable/10min.html
- Quick Tip: The easiest way to grab data out of a web page in Python
- Graphing bike path data with IPython Notebook and pandas
- 김영근 - pandas contribution 하기
- Pycon2017 이성용 Dances with the Last Samurai django + pandas + python-docx 를 이용한 통계업무도구 만들기
- 파이썬에서 주가데이터 읽어오기
- Open Machine Learning Course. Topic 1. Exploratory data analysis with Pandas
- The Pandas DataFrame – loading, editing, and viewing data in Python
- Quick dive into Pandas for Data Science
- Selecting Subsets of Data in Pandas
- pandas column 의 위아래 값의 차이를 비교해보자
- pandas 시간정보로 .srt 자막을 만들어보자
- Pandas: 한 셀의 데이터를 여러 행으로 나누기
- Pandas: 그룹 내에서 상위 n개 가져오기
- 23 great Pandas codes for Data Scientists
- Python Pandas Tutorial | Pandas For Data Analysis | Python Pandas | Python Tutorial | Simplilearn
- Tidying Up Pandas
- How to build your data science muscle memory: Slicing and Mapping Data for Machine Learning
- pandas .head() to .tail() (Beginner) | SciPy 2018 Tutorial | Niederhut, Augspurger, Van den Bossche
- Minimally Sufficient Pandas
- Cleaning and Tidying Data in Pandas - Daniel Chen
- Using The Pandas Category Data Type
- Pandas 10분 완성
- Pandas 기초 - cheat sheet 따라하기
- 10 Python Pandas tricks that make your work more efficient
- Modin Get faster pandas with Modin, even on your laptops
- Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
- Pandas Tutorial (Data Analysis In Python)
- 파이썬 판다스 데이터프레임 apply함수 사용 - 특정 조건(if)의 값 바꾸기!
- Pandas - 연비 TEST Data 분석 1
- Pandas - Gapminder Data 분석(그래프 분석) 3
- Pandas - 1880 ~ 2010 년까지 출생 자료 분석 - 남/여 출생 수
- Pandas - Json Data 분석 4(Data 시각화)
- Pandas - 영화 진흥원 API 상영 순위 분석
- Best practices with pandas
- SQL과 파이썬 pandas의 비교
- My top 25 pandas tricks
- 판다스 코드 속도 최적화를 위한 초보자 안내서
- PyData Tel Aviv Meetup: Getting to Know any Dataset in 4 Lines of Python - Eyal Trabelsi
pandas_profiling,pivottablejs,pydqc.data_compare - One-stop Guide to Data Manipulation in Python 여러가지 pandas 사용법 예제
- Learn a new pandas trick every day!
- 편리한 판다스 무조건 좋을까?
- Why and How to Use Pandas with Large Data
- Binning Data with Pandas qcut and cut
- Cleaning Up Currency Data with Pandas
- 상관관계 분석(Pandas) & Heatmap 그리기
- Tips for Selecting Columns in a DataFrame
- Finding Natural Breaks in Data with the Fisher-Jenks Algorithm
- Data Preparation Basic(데이터 전처리 기초) 1
- Data Preparation Basic(데이터 전처리 기초) 2
- Data Preparation Basic(데이터 전처리 기초) 3
- Efficient Pandas: Using Chunksize for Large Data Sets
- 파이썬으로 로또 당첨번호 및 당첨금 데이터 분석 하기 feat.pandas, pyplot
- Python Tools for Record Linking and Fuzzy Matching fuzzymatcher, recordlinkage
- 파이썬과 판다스로 배우는 통계 기초
- vaex - Out-of-Core DataFrames for Python, visualize and explore big tabular data at a billion rows per second. https://vaex.io
- EuroPython Podcast Questions
- EuroPython 2018
- EuroPython 2019 Unleash the power of C++ in Python
- How Thinking in Python Made Me a Better Software Engineer
- pyvideo.org
- 2016년 12월 파이썬 격월 세미나 & 송년회 후기!
- 2017년 10월 파이썬 세미나 - Python & Data
- 2017년 1월 3주차 파이썬 주간 소식
- 2017년 1월 4주차 파이썬 주간 소식
- 2017년 2월 1주차 파이썬 주간 소식
- 2017년 2월 2주차 파이썬 주간 소식
- 2017년 2월 3주차 파이썬 주간 소식
- 격월 세미나
- pycon 2014
- pyconkr 2014
- pycon 2015
- PyCon 2015
- python names and values
- pycon 2015: are we still changing the world?
- pycon 2015 montreal
- raymond hettinger - beyond pep 8 -- best practices for beautiful intelligible code - pycon 2015
- pycon 2015 talks: our must see picks (1/6)
- david beazley - modules and packages: live and let die! - pycon 2015
- brett slatkin - how to be more effective with functions - pycon 2015
- Machine Learning: Python and the Power of Ensembles by Bargava Raman Subramanian
- pyconkr 2015
- 파이콘 한국 2015 (pycon korea 2015) 후기!!
- 2015 py con word2vec이 추천시스템을 만났을 때
- 한국어와 nltk, gensim의 만남
- the hitchhiker's guide to the python memory
- 알파희 - pypy/rpython으로 20배 빨라지는 아희 jit 인터프리터
- celery의 빛과 그림자
- 약속
- profiling - 실시간 대화식 프로파일러
- 파이콘 코리아 2015 코드 골프 되돌아보기
- pycon korea 2015
- 후기
- 김도형: 파이썬 기반의 대규모 알고리즘 트레이딩 시스템 소개 - PyCon Korea 2015
- 김현호: 오늘 당장 딥러닝 실험하기 - PyCon Korea 2015
- 유재명: R vs. Python: 누가, 언제, 왜 - PyCon Korea 2015
- 김재석: 도도와 파이썬: 좋은 선택과 나쁜 선택 - PyCon Korea 2015
- 임덕규: 업무에서 빠르게 만들어 사용하는 PyQt 프로그래밍 - PyCon Korea 2015
- pycon 2016
- pycon.kr/2016apac
- pycon.kr/2016apac/program/schedule
- Python으로 한자검색 텔레그램 봇 개발 후기
- 디자이너의 코딩 도전기
- 지적 대화를 위한 깊고 넓은 딥러닝 Pycon APAC 2016
-
- 이미지(사람의 얼굴 사진)을 이해하고 스스로 만드는 모델
-
- github.com/carpedm20/DCGAN-tensorflow
- 2. Atari 게임을 화면의 픽셀만 보고 배우는 모델
- 3. 이미지 버전의 '왕 - 남자 + 여자 = 여왕'
- 4. 뉴럴 네트워크로 만든 튜링 머신
- 5. 강화 학습 모델들
- 6. 픽셀을 하나씩 예측하며 이미지를 만드는 모델
- 7. Question Answering, Language Model
- 8. Character-level Language Models
- 9. Teaching Machines to Read and Comprehend
- 10. Neural Variational Inference for Text Processing
- 11. Text-based Games using Deep Reinforcement Learning
- 12. Continuous Deep Q-Learning with Normalized Advantage Functions
- 정경업: Django로 쇼핑몰 만들자 - PyCon APAC 2016
- PyCon APAC 2016 - 너의 사진은 내가 지난 과거에 한일을 알고 있다
- 파이콘 2016 pycon 1일차 후기
- 삶의 의미는 성장에 있다
- 파이콘 삼총사 : Tox, Travis 그리고 Coveralls
- PyConAPAC 2016 부스 운영기
- PyCon APAC 2016 후기
- 스프린트와 튜토리얼
- CODING BATTLE 가위바위보! - 못다한 이야기
- PyCon APAC 2016 후기
- PyCon APAC 2016 발표자 & 자원봉사자 후기
- 김대현 : 파이썬을 활용한 똑똑한 주식투자 (시스템 트레이딩) - PyCon APAC 2016
- 김영욱: Python으로 IoT, 인지(Cognitive), 머신러닝 삼종세트 활용하기 - PyCon APAC 2016
- 김경훈: 뉴스를 재미있게 만드는 방법; 뉴스잼 - PyCon APAC 2016
- 양민지: Regular expression [A-Z]+ - PyCon APAC 2016
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- 임성준: Python, VTK를 만나다! - Python, VTK를 활용한 3차원 볼륨 데이터의 시각화 및 활용 - PyCon APAC 2016
- 김영근 : 어느 흔한 파이썬 개발자의 집 소개 - PyCon APAC 2016
- 안명호 : Python + Spark, 머신러닝을 위한 완벽한 결혼 - PyCon APAC 2016
- 김태훈: 지적 대화를 위한 깊고 넓은 딥러닝 (Feat. TensorFlow) - PyCon APAC 2016
- 이홍주: Python 으로 19대 국회 뽀개기 - PyCon APAC 2016
- 홍민희: RPC 프레임워크 제작 삽질기 - PyCon APAC 2016
- 김동문: 검색 로그 시스템 with Python - PyCon APAC 2016
- 정민영 : 10만 라인, 26280시간의 이야기 - PyCon APAC 2016
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- Amit Kumar: Demystifying Python Method Resolution Order - PyCon APAC 2016
- PyCon AU 2016 참가 후기
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- pycon.kr/2017/program/list
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- PYCON2017 api tutorial 관련 자료
- 파알못의 파이콘 2017 참가 후기
- Charles Ochoa: The Joy of Integer Programming: Solving Hard Combinatorial Problems in Python
- 유서원: Practical automation for beginners
- 박준철: Python 게임서버 안녕하십니까 : RPC framework 편
- 2017-10 강대명 - 파이썬으로 풀어보는 아주 심플한 검색엔진의 원리
- 천원경매
- 조인석: 파이썬 vs 자바 초보 대상
- 이성용 : 개발자 없는 통계업무 부서에서 Django+Pandas+Selenium+python-docx으로 통계업무도구 만들기
- PyCon 2017
- Allen Downey - Introduction to Digital Signal Processing - PyCon 2018
- PyConKr 2018
- PyCon KR 2018 영상 다운 받기
- 인생을 짧아요, 엑셀대신 파이썬
- A Development of Log-based Game AI using Deep Learning
- pyconkr-2018-booklet
- PyCon Korea 2018 Day1 Lightning Talk - Python으로 LibreOffice의 한자 목록 공헌하기
- PyconKR 2018 Python으로 나만의 IOT 구축하기
- 학습하는 조직과 Python: 뱅크샐러드 사례를 중심으로
- PYCON Korea 2018 Python Application Server for Recommender System
- Animal iris recognition
- pycon korea 2018 드론 및 인공위성 영상을 이용한 태양광발전소 입지분석
- 생활탐사 - 파이썬으로 일상에 도움 되는 뉴스 만들기
- PyCon KR 2018 땀내를 줄이는 Data와 Feature 다루기
- 파이콘 2018 후기
- 2018. 05 파이썬 개발환경 구성하기 거의 끝판왕 Docker Compose - 김승호 compose뿐만 아니라 docker 명령 기본에 대한 것도 알기 좋음
- PyCon 2019
- Pycon 2019 Korea youtube 링크 정리
- Raymond Hettinger - Modern solvers: Problems well-defined are problems solved - PyCon 2019
- PyCon Korea 2019 법률을 디버깅하다 Debugging law
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- 머신러닝 및 데이터 과학 연구자를 위한 python 기반 컨테이너 분산처리 플랫폼 설계 및 개발 python이 아니라 프로젝트 설계 및 구현 관점에서 재미있게 볼 수 있는 이야기
- from banksalad import python 뱅크샐러드의 사내 python이용에 관한 발표
- 파이콘 한국 2019 스포카 코드 챌린지 수상작 및 참여작을 소개합니다
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- PyOhio 2019 Surviving Without Python python 전반
- A Machine Learning Data Pipeline - PyData SG
- Marco Bonzanini - Building Data Pipelines in Python
- PyData Paris 2016 - Automatic Machine Learning using Python & scikit-learn
- PyData London 2018
- PyData London 2019
- PyData Seattle 2017 Keynote Jake VanderPlas 여러가지 data 관련 library 역사(?)
- Optimizing numerical calculations in Python - Jakub Urban - PyData Prague, January 2019
- Ryan Williams: Accelerating Single-cell Bioinformatics with N-dimensional Arrays | PyData Miami 2019 HDF5, Zarr, dask, zappy
- PyData Ann Arbor: Katie Bauer | Building "Time On Site" at Reddit
- PyPy Vectorization
- PyPy warmup improvements
- Automatic SIMD vectorization support in PyPy
- "파이썬 성능 향상을 위한" 파이파이란 무엇인가
- cppyy: C++ bindings for PyPy
- ubuntu pypy 설치 & benchmark
- PyPy's new JSON parser
- 2 & 3 호환
- Cheat Sheet: Writing Python 2-3 compatible code
from __future__ import print_functionif sys.version_info[:2] <= (2, 7): import urllib else: from urllib.parse import urlencode- Python 2 & 3 Compatible print and input
- Python 2 와 3 공존하기
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- Zero to Hero with Python Tutorial FULL- Easy Learning python 3.4 from begin to advance (Compact)
- Python 3 in Science: the great migration has begun!
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- Python의 미래, Python 3로 넘어가기
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- concurrent.futures - Easy parallel python with concurrent.futures
- PyParallel.org
- Python 3.5 Brings New Language Features and Library Modules
- Python 3.5 and multitasking
- ZipPy: A Simple Python 3 for the JVM
- Python Changes 2014+
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- Why Python 3 exists
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- Python 2to3 - Convert your Python 2 to Python 3 automatically!
- Python 3 Basics Tutorial Series
- Python 3 Patterns, Recipes and Idioms
- 파이썬 마이크로 실전 패턴
- The Case Against Python 3 (For Now)
- The Case Against “The Case Against Python 3”
- Home Assistant - a home automation platform running on Python 3
- 파이썬 3.6에서 바뀐 점
- syntax_sugar
- Tiny Python 3.6 Notebook
- Lessons Learned: Digital Ocean for Python 3
- Optimizations which made Python 3.6 faster than Python 3.5
- Instagram Makes a Smooth Move to Python 3
- python3에서 자주 실수하는 부분
- www.python3statement.org 2020까지 python2.7 지원 중단하기로 하는 project 모음
- Migrating to Python 3 with pleasure
- 5 speed improvements in Python 3.7
- Python 3.7의 새로운 기능들
- Modern Functions in Python 3
- PyCon KR 2019 Why is Python 3.7 fastest
- What’s New In Python 3.8
- Try out walrus operator in Python 3.8 Get started with Python 3.8 alpha 1
- 파이썬(Python) 3.8 릴리스와 주요 변경 사항
- Some New Features in Python 3.8
- Cool New Features in Python 3.8
- 놓쳐서는 안 될' 파이썬의 새로운 기능 6가지 3.8
- Reimplementing a Solaris command in Python gained 17x performance improvement from C
- github.com/elegant-scipy
- Scipy Lecture Notes
- SciPy Cheat Sheet: Linear Algebra in Python
- SciPy 2015: Scientific Computing with Python Conference
- Keynote: Machine Learning for Social Science | SciPy 2016 | Hanna Wallach
- 2D Convolution in Python similar to Matlab's conv2
- Area of sinc and jinc function lobes
- SciPy 1.0: fundamental algorithms for scientific computing in Python
- Unification in SymPy
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- Python Sympy 모듈 이해하기
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- Generating Python code from SymPy
- Beginning Test-Driven Development in Python
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- 파이썬 시작하기 TDD부터 PyPI에 배포까지 (1)
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- A simple introduction to Test Driven Development with Python
- Automated Tests in Python
- python testing
- Unit Tests in Python || Python Tutorial || Learn Python Programming
- Reduce testing time by Multiprocessing in python
- faker, factory boy 깔끔한 파이썬 테스트 코드를 위한 Faker와 Factory Boy
- mutation testing
- property based testing
- Introduction to property-based testing
- Property-based Testing from Scratch (in Python)
- 5-minute intro to property-based testing in Python with hypothesis
- Episode #67: Property-based Testing with Hypothesis
- Hypothesis with David MacIver - Episode 52
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- Intro to property-based testing in Python
- 우아하게 준비하는 테스트와 리팩토링 - 한성민
- PyCon KR 2019 테스트에 걸리는 시간을 92% 줄이기 주로 Django 기반이지만 매우 좋은 내용
- nosetests
- pytest: helps you write better programs
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installaion; anaconda에서
pip install -U pytest로 오류가 발생하면conda update pytest이용$ [http_proxy=http://x.y.z:port https_proxy=http://x.y.z:port] pip install -U pytest ... Cannot remove entries from nonexistent file /path/to/anaconda/lib/python2.7/site-packages/easy-install.pth $ [http_proxy=http://x.y.z:port https_proxy=http://x.y.z:port] conda update pytest -
PyTest, the testing framework you've been dreaming of by Eli Gur
-
Open Sourcing Pytest Tools pytest-flakefinder, unittest2pytest
-
- pytest-bdd - BDD library for the py.test runner
- pytest-benchmark 파이썬 벤치마크 테스트
- pytest-flakefinder - Runs tests multiple times to expose flakiness
- Tabletests
- unittest
- unittest.mock
- practice - unittest
- Python Tutorial: Unit Testing Your Code with the unittest Module
- Mock Everything
- Python Mock Cookbook
- Python Mock Gotchas
- Python Mocking 101: Fake It Before You Make It
- Using the Python mock library to fake regular functions during tests
- Mocking Python With Kung Fu Panda
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- Mocking Objects in Python
- Mocking private methods in python
- Mocking complicated
__init__in Python - Assigning instance variables in function called by
__init__vs. function called from__init__ - Another approach to mocking properties in Python
- Another approach to mocking properties
- How in the world do you Mock a name attribute?
- How to Mock a name attribute?
- Allow doubling a particular instance method on all instances of a class
- Today I Learned: 파이썬 단위 테스트 모듈, unittest
- Python Unit Testing With VS Code
- unittest2pytest - Convert unittest asserts to pytest rewritten asserts
- vcr.py - Automatically mock your HTTP interactions to simplify and speed up testing
- Learn How to Use Static Type Checking in Python 3.6 in 10 minutes
- Panel Discussion: What is Static Typing in Python? | PyBay 2017
- Dynamic Typing in Python
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- Next Steps with Python Type System
- callable() in Python
- Typesetting With Python
- Our journey to type checking 4 million lines of Python
- Falling into a type world with Python
- Enforce.py - Python 3.5+ runtime type checking for integration testing and data validation
- LibCST - A concrete syntax tree parser and serializer library for Python that preserves many aspects of Python's abstract syntax tree https://libcst.readthedocs.io
- MonkeyType - A system for Python that generates static type annotations by collecting runtime types
- mypy an experimental optional static type checker for Python
- Static Typing for Python
- Dec 2016 BayPiggies Talk at LinkedIn: Introducing Type Annotations for Python
- Python Type Hints by Sunghyun Hwang
- Type Hints(PEP 484, PEP 526) - 1
- Jukka Lehtosalo, David Fisher Static Types for Python PyCon 2017
- PYCON UK 2017: MyPy: The Good, The Bad and The Ugly
- mypy Python's gradual typing implementation - Itzhak Kasovitch - Pycon Israel 2017
- Type-Checking Python Programs With Type Hints and mypy
- Python tricks: Type hints and static type checking
- Type-checked Python In The Real World
- Clearer Code at Scale (Static Types in Python)
- Python static type checker (mypy)
- Type checking in Python using mypy
- mypy와 함께하는 Python Typing
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- PyCon KR 2019 Python Type Hinting and Static Type Checking
- Python Type Hints: Pros & Cons
- Release: Static type checker in Python
- PyAnnotate: Auto-generate PEP-484 annotations
- pydantic - Data validation and settings management using python 3.6 type hinting
- Pyre - A performant typechecker for Python
- pyright - Static type checker for the Python language
- pytype - A static analyzer for Python code
- Tsukkomi for Python types, inspired by typeannotations package https://pypi.python.org/pypi/tsukkomi
- typeguard - Run-time type checker for Python
- 김명신: Python 개발을 위한 최상의 무료 개발 도구 Visual Studio와 Visual Studio Code - PyCon Korea 2015
- Dan Taylor - Get Productive with Python in Visual Studio Code
- Python in Visual Studio Code – October 2018 Release jupyter support
- Python in Visual Studio Code – October 2019 Release
- Let’s Build A Web Server
- Brython - A Python 3 implementation for client-side web programming
- mod_wsgi
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yum install pcre-devel.x86_64 -yapt-get install libpcre3-dev -y
- What package I should install for 'pcre-devel'?
- py2exe로 생성된 exe에서 py 소스 구하기 및 \xec... 문자열 변환
- py2exe와 py2app을 통한 Windows/OS X용 실행파일 만들기
- Windows COM (ActiveX) client 사용
- Create a standalone Windows installer for your Python application
- 윈도우에서 여러 버전의 파이썬을 설치
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- Using Events in Python Win32 | Part 1
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- VBA 개체 모델에서는 사용자가 이벤트를 일으킬 때, VBA 코드를 실행할 수 있는 이벤트에 액세스 가능
- 이 이벤트들은 클래스 객체를 사용하여 Python 내부의 Win32 COM 라이브러리를 통하여 액세스 가능
- How to Use the PyIDispatch Object in Pythoncom
- PyIDispatch 객체와 이 객체를 활용하여 COM 객체에 속한 다른 방법 및 속성을 호출하는 방법
- Win32COM 라이브러리는 표준화 된 방식으로 다른 COM 개체들과 통신할 수 있는 디스패치 인터페이스 개체를 활용
- How to Use Word VBA in Python
- 새로운 Word 문서를 만들고, 문서에 테이블을 추가하고, Python을 사용하여 링크를 추가하는 방법
- Word VBA 모델
- How to Use PYODBC With SQL Servers in Python
- pyodbc 라이브러리를 사용하여 SQL Server, Access 데이터베이스 및 Excel 통합 문서에 연결하는 것과 데이터를 데이터베이스에 삽입하는 방법
- Building a Windows Shortcut with Python
- Python과 Windows Program간의 데이터 공유 memory mapped file, MFC <-> python
- Dependency Walker - free utility that scans any 32-bit or 64-bit Windows module (exe, dll, ocx, sys, etc.) and builds a hierarchical tree diagram of all dependent modules
- DUMPBIN Reference examine COFF, exe, DLL files
- ironpython
- win32clipboard clipboard 로 text, image 복사하기 , 가져오기
- win32gui 응용프로그램창 백그라운드로 숨기는 방법(win32gui)