Python¶

pip¶

to upgrade all python packages, use pip-review

pip3 install pip-review

pip-review --local --auto

https://stackoverflow.com/a/16269635/15493213

remove package¶

pip3 uninstall <package>

requirements.txt¶

create¶

for every libraries you have

python -m pip freeze > requirements.txt

Use pipreqs for a specific directory

Install

pip3 install pipreqs

Use

pipreqs /path/to/project

If the command is not found, add python package path to your path

export PATH=$PATH:~/.local/bin

https://github.com/bndr/pipreqs/issues/69#issuecomment-298758892

If still not found, run with python instead

python3 -m pipreqs.pipreqs

https://stackoverflow.com/a/68965523/15493213

use¶

pip3 install -r requirements.txt

venv (virtual environment)¶

create

python3 -m venv venv
# echo venv/ >> .gitignore

go into

source venv/bin/activate

leave

deactivate

pyenv¶

python version controller

https://github.com/pyenv/pyenv

install¶

https://pyenv.run

add below to the end of ~/.bashrc

export PATH="$HOME/.pyenv/bin:$PATH"
eval "$(pyenv init --path)"
eval "$(pyenv virtualenv-init -)"

restart shell with exec $SHELL or just source ~/.bashrc

https://github.com/pyenv/pyenv-installer

commands¶

pyenv install <version> to install e.g. 3.9.10
pyenv uninstall <version> to uninstall version
pyenv versions to see versions you have & the version you're using (like git branch)
pyenv local <version> to select your desired version for this directory
- python3 -V to check
pyenv global <version> to select your desired version for you machine

import¶

import everything from config.py, including packages, functions, variables, etc. (like include in php or <script></script> in html/js)

from config import *

https://stackoverflow.com/a/17255770/15493213

import from subdirectory¶

Assuming

- main.py
- aa
    - aaa.py

To import function haha() from aaa.py in main.py

from aa.aaa import haha

import from parent¶

e.g. to import from parent's parent directory

import sys
sys.path.append('../')
import <your_file>

or

import sys, os
sys.path.insert(1, os.path.join(sys.path[0], '../..'))
import <your_file>

https://stackoverflow.com/questions/714063/#comment23054549_11158224

`name`¶

When imported, __name__ will be the module's name. When executed directly, __name__ will be __main__.

working directory¶

show current directory¶

ls

import os
os.getcwd()

change directory¶

cd

import os
os.chdir("<path>")

Typing¶

Python can be a pain in the ass work with for bigger scale code due to it being not statistically type, but you can type hint and let your linter like Pylance pick it up to imitate static typing.

Format¶

var_name: type_name = init_val

For example, this Go code

myStr := []string{1,2,3}

should be like this in Python

my_str: list[str] = [1, 2, 3]

For tuple, you should include the type of each slot.

e.g. for a len = 3 (integer, float, string) tuple

my_tup: tuple[int, float, str] = (3, 1.35, "4.05")

Type hinting opencv Mat¶

import numpy as np
import numpy.typing
Mat = numpy.typing.NDArray[np.uint8]

Class¶

Inheritance¶

class Mom():
    def __init__(self):
        self.yes = True

class StepMom():
    def __init__(self):
        self.no = True

class Child(Mom, StepMom):
    def __init__(self):
        # run the __init__ of the parent classes
        super().__init__()
        # now it can access self.yes & self.no
        print(self.yes, self.no)

Unit testing with `unittest`¶

Basics¶

Suppose you want to write unit tests for your functions in main.py

main.py

def no(query: str) -> bool:
    return False

def yes(query: str) -> bool:
    return True

Put your unit tests in test_main.py

import unittest
from main import no, yes

class TestMain(unittest.TestCase):
    def test_no(self):
        mock_query = "Me das tu movil?"
        expected_ans = False
        actual_ans = no(mock_query)
        self.assertEqual(expected_ans, actual_ans)

    def test_yes(self):
        mock_query = "Are you yo mama?"
        expected_ans = True
        actual_ans = yes(mock_query)
        self.assertEqual(expected_ans, actual_ans)

if __name__ == "__main__":
    unittest.main()

Now just run test_main.py, and it will tell you the result. If something's wrong, it will show you the diff.

Mock¶

You can easily mock a function so you don't have to actually run the function when testing your target function.

main.py

def times_two_add_one(num: int) -> int:
    res = times_two(num) + 1
    return res

test_main.py

import unittest
from unittest.mock import MagicMock
from main import *

class TestMain(unittest.TestCase):
    def test_times_two_add_one(self):
        num = 11
        times_two = MagicMock(return_value=22)
        actual = times_two_add_one(num)
        expected = 23
        self.assertEqual(expected, actual)

        # optional: ensure that the parameter passed into times_two is correct
        times_two = assert_called_with(num)
        # or
        times_two.assert_called_with(num)

If you know GoMock, this is equal to

num := 11
times_two.EXPECT(num).RETURN(22)

The great thing about MagicMock is that it does not require you to generate a separate mock file beforehand.

VsCode Extension¶

Use Python Test Explorer for Visual Studio Code

Coverage¶

You can see your test coverage stats as well as the lines covered in a web UI!

Install the coverage module

pip3 install coverage

Run the test

python3 -m coverage run --source . -m unittest

If you don't add the --source flag, all imported internal libraries will also be printed.

See the converate in your terminal

python3 -m coverage report

Generate html files inside /htmlconv showing the lines covered

python3 -m coverage html

Open the html file (for Mac)

open htmlcov/index.html

example

You can write these all into a make file

ut:
    python3 -m coverage run --source . -m unittest
    python3 -m coverage report
    python3 -m coverage html  
    open htmlcov/index.html

random¶

seed¶

You can give a seed for reproduceable results before each random function.

e.g.

import random
random.seed(1)
random.random() # -> 0.13436424411240122
random.random() # -> 0.8474337369372327
random.seed(1)
random.random() # -> 0.13436424411240122

shuffle¶

shuffle a list, in place

import random
a = [1,2,3,4,5]
random.shuffle(a)

Hashing¶

from hashlib import sha256
def get_hash(plain: str) -> str:
    plain = '123456'
    plain = plain.encode()
    S = sha256()
    S.update(plain)
    return S.hexdigest()

matplotlib¶

Auto adjsut your figure layout¶

plt.tight_layout()

Add this if your text is cutoff or whatever.

save figure¶

plt.savefig(f'{fig_name}.pdf', format='pdf', dpi=300)

plot as many on demand¶

https://stackoverflow.com/a/39106673/15493213

import matplotlib.pyplot as plt

xvals = [i for i in range(0, 10)]
yvals1 = [i**2 for i in range(0, 10)]
yvals2 = [i**3 for i in range(0, 10)]

f, ax = plt.subplots(1)
ax.plot(xvals, yvals1)
ax.plot(xvals, yvals2)

f2, ax2 = plt.subplots(1)
ax2.plot(xvals, yvals1)
ax2.plot(xvals, yvals2)

plt.show()

plot 2 charts, each with 2 lines

subplot on demand¶

https://stackoverflow.com/a/49100437/15493213

import matplotlib.pyplot as plt
import numpy as np

f = plt.figure(figsize=(10,3))
ax = f.add_subplot(121)
ax2 = f.add_subplot(122)
x = np.linspace(0,4,1000)
ax.plot(x, np.sin(x))
ax2.plot(x, np.cos(x), 'r:')

style¶

plt.plot(<x_data>, <y_data>, marker='o', markersize=5, linestyle='None')

legend¶

plt.plot(<x_data>, <y_data>, label="line1")
plt.plot(<x_data>, <y_data>, label="line2")
plt.legend()
plt.show()

display Chinese character¶

Simply add this

matplotlib.rcParams['font.family'] = ['Heiti TC']

Replace Heiti TC with other fonts if you're not using MacOS.

ref

gridline¶

plt.grid() to enable gridline

axis label¶

import matplotlib.pyplot as plt
plt.xlabel("x axis")
plt.ylabel("y axis")
plt.title("title")

# or
_, ax = plt.subplot()
ax.set_xlabel("x axis")
ax.set_ylabel("y axis")
ax.set_title("title")

axis min max value¶

Omit -> auto

plt.xlim(left=0, right=100) 
plt.ylim(bottom=0, top=100)
plt.tight_layout() # you may need this

https://stackoverflow.com/a/32634026/15493213

axis interval¶

y axis 20 intervals

import matplotlib.pyplot as plt
ax = plt.gca()
y_min, y_max = [int(i) for i in ax.get_ylim()]
plt.yticks(range(y_min, y_max, (y_max-y_min)//20))
plt.ylim([0, y_max])

hide axis¶

import matplotlib.pyplot as plt
plt.gca().get_xaxis().set_visible(False)

log scale¶

plt.yscale('symlog')

Works for both positives & negatives.

https://stackoverflow.com/a/43372699/15493213

datetime¶

auto formate dates on x axis

import matplotlib.pyplot as plt
plt.gcf().autofmt_xdate()

manual formatting

ax = plt.gca()
# 1 minute 1 tick
ax.xaxis.set_major_locator(md.MinuteLocator())
# format dateime to HH:MM
ax.xaxis.set_major_formatter(md.DateFormatter('%H:%M'))

https://stackoverflow.com/a/69333777/15493213
https://matplotlib.org/stable/api/dates_api.html#matplotlib.dates.MinuteLocator

exec¶

to use in function, use exec(string, globals())

inputs¶

*args -> unpack a list/tuple of args
**args -> unpack a dict of args

def foo(x, y, z):
    pass
# method 1
foo(1, 2, 3)
#method 2
_list = [1, 2, 3]
foo(*_list)
# method 3
dict = {x=1, y=2, z=3}
foo(**_dict)

can also be used reversedly

https://stackoverflow.com/questions/36901/

decorator¶

def plusC(c):
    """add c"""
    def dec(func):
        def wrapper(a, b):
            return func(a,b)+c
        return wrapper
    return dec

@plusC(5)
def plus(a, b):
    return a + b

ans = plus(1, 2)
print(ans) # output 1+2+5 = 8

https://stackoverflow.com/a/53973651/15493213

file¶

read file¶

with open(inputfile, 'r') as file_in:
    matrix = file_in.readlines()

Read file to dict/json¶

import json
mydict = json.load(open("myjson.json"))

Save dict/json to file¶

import json
mydict = [1:1, 2:2]
save
json.dump(mydict, open("myjson.json", "w"))

yaml¶

load¶

For single document:

import yaml
with open('deployment.yaml', 'r') as f:
    deploy = yaml.safe_load(f)

For multiple document combined (with --- seperator, see this):

import yaml
with open('deployment.yaml', 'r') as f:
    deploy = list(yaml.safe_load_all(f))

dump¶

sort_keys=False to preserve insertion order (related Github issue)

single document

import yaml
deployment_yml = dict()
with open('deployment.yaml', 'w') as f:
    yaml.dump(deployment_yml, f, sort_keys=False)

multiple document

import yaml
deployment_yml = list() # list of dicts
with open('deployment.yaml', 'w') as f:
    yaml.dump_all(deployment_yml, f, sort_keys=False)

block literals¶

block literals is multi-line string

e.g.

  - |
    kind: JoinConfiguration
    nodeRegistration:
      kubeletExtraArgs:
        node-labels: "name=edge1"

To create a yml containing this:

import yaml

class folded_unicode(str): pass
class literal_unicode(str): pass

def folded_unicode_representer(dumper, data):
    return dumper.represent_scalar(u'tag:yaml.org,2002:str', data, style='>')
def literal_unicode_representer(dumper, data):
    return dumper.represent_scalar(u'tag:yaml.org,2002:str', data, style='|')

data = {'literal': literal_unicode(
        'kind: JoinConfiguration\n'
        'nodeRegistration:\n'
        '  kubeletExtraArgs:\n'
        '    node-labels: "name=edge"\n'
}
yaml.dump(data)

https://stackoverflow.com/a/7445560/15493213

encode¶

encode to base 64¶

cred = f'{clientID}:{clientSecret}'
b64_cred = base64.b64encode(cred.encode('ascii')).decode('ascii')

decode¶

decoding utf-8 encoded characters represented in unicode escaped sequence¶

You can get text like \u00e5\u0093\u00ad\u00e5\u0093\u00ad if you use json.dump() without ensure_ascii=False.

encoded_text = "\u00e5\u0093\u00ad\u00e5\u0093\u00ad"
decoded_text = encoded_text.encode("latin-1").decode('utf-8')
print(decoded_text)

output: 哭哭

source

trace exceptions¶

import traceback
try:
    # something
except:
    print(traceback.format_exc())

string¶

split¶

import re
old = 'I am, not, you! Fuck!'
new = re.split('[,\s!]', old)
new = re.split(', | |!')

- use | to separate symbols - use [] to use each symbol in the bracket

convert¶

str to json¶

import json
json.loads(str)

datetime¶

from datetime import datetime

datetime to string¶

convert date & time now to iso format string

datetime.now().isoformat()

convert to custom format string

datetime.now().strftime("%Y-%m-%dT%H:%M:%S")

string to datetime¶

convert iso format string to datetime object

datetime.fromisoformat(str)

current time¶

datetime.now()

UTC

datetime.utcnow()

UTC+8

from datetime import datetime, timedelta, timezone
datetime.now(timezone(timedelta(hours=8)))

timedelta¶

datetime.timedelta(days=0, seconds=0, microseconds=0, milliseconds=0, minutes=0, hours=0, weeks=0)

from datetime import timedelta

subtract 2 datetime objects to get a timedelta object

example

haha = datetime.timedelta(days=1, seconds=20, microseconds=610333)
haha.days # -> 1
haha.seconds # -> 20
haha.microseconds # -> 610333

to get total passed time

# in days
haha/timedelta(days=1)
# in seconds
haha/timedelta(seconds=1)
# in microseconds
haha/timedelta(microseconds=1)

https://docs.python.org/3/library/datetime.html#datetime.timedelta.total_seconds

iterate time with timedelta¶

e.g. iterate from tiempo_prev to tiempo with 1 second as unit

while tiempo_prev != None:
    tiempo_prev += timedelta(seconds=1)
    if tiempo_prev >= tiempo: break
    x_vals.append(tiempo_prev)
    y_vals.append(0)

https://www.adamsmith.haus/python/answers/how-to-iterate-through-a-range-of-dates-in-python

Heap / Priority Queue¶

Use heapq for min heap.

Transform, push, and pop

import heapq
mylist = [1,2,3,4,5]
# transform into heap
heapq.heapify(mylist)
# push into heap
heapq.heappush(mylist, (5, 'label 5'))
# pop from heap
res = heapq.heappop(mylist)

K Smallest/Largest

import heapq
mylist = [(1,2),(2,3),(1,3),(4,-2)]
# return a list of k smallest with custom comparison formula
res = heapq.nsmallest(5, mylist, key = lambda x: x[0]+x[1])
res = heapq.nlargest(5, mylist, key = lambda x: x[0]+x[1])

collections¶

import collections

OrderedDict¶

remember the insertion order
great for implementing LRU, see Leetcode 146. LRU Cache

deque¶

a double sided simple queue, O(1) for enqueuing & dequeuing from both sides
append()
appendleft()
pop()
popleft()

Counter¶

return a hash map, counting each element of a list

sort¶

sort 2D list¶

#x = [[10,16],[2,8],[1,6],[7,12]]
sorted(x, key = lambda section: section[1]) # sort by second value

sort dict by value¶

# x={1: 1, 2: 2, 3: 0}
sorted(x.items(), key=lambda item: item[1])

infinity¶

float('inf')

Symbolic Math¶

Use sympy

pip3 install sympy

Integral¶

e.g. to calculate the mean of a hyperexponential distribution

import sympy as sp

t = sp.symbols('t')
f = 1-0.01*sp.exp(-18*t)-0.82*sp.exp(-0.015*t)
mean = sp.integrate((1-f), (t, 0, sp.oo))
print(f"mean = {mean.simplify()}")

Laplace Transform¶

e.g. calculate laplace transform (t -> s)

import sympy as sp

s, t = sp.symbols('s t')
f1 = 2/12*sp.exp(t/12)
F1 = sp.laplace_transform(f1, t, s)
print(F1)

e.g. calculate inverse laplace transform (s -> t)

from sympy.integrals.transforms import inverse_laplace_transform

s, t = sp.symbols('s t')
F = (2/(1-12*s))/((1/(1-12*s))*((1/(3+15*s))+(4/(6+75*s)))-1)
f = inverse_laplace_transform(F, s, t)
print(f)

numpy¶

matrix multiplication¶

use operator @

save np array to csv¶

np.savetxt('<path/to.file>.csv', <2d np array>, delimiter=',', fmt='%i')

fmt='%i' for saving into all integer

pandas¶

Save 2d array to csv¶

import pandas as pd
arr = [["a", "b", "c"], [1,2,3], [3,4,5]]
pd.DataFrame(arr).to_csv(output.csv, index=False, header=False)

https://stackoverflow.com/a/41096943/15493213

get column names¶

import pandas as pd
f = pd.read_csv("<your_file>.csv")
cols = f.columns.tolist()

merge csv files¶

Left join f2 to f1

import pandas as pd
f1 = pd.read_csv('filename1.csv')
f2 = pd.read_csv('filename2.csv')
f = f1.merge(f2, how='left', on='MergeCol')

https://stackoverflow.com/a/42583953/15493213

ipynb notebook¶

convert between ipynb & python¶

pip3 install ipynb-py-convert

ipynb-py-convert <in.ipynb> <out.py>

ipynb-py-convert <in.py> <out.ipynb>

https://stackoverflow.com/a/66565946/15493213

run ipynb¶

ipython3 -c "% run something.ipynb"

environmental variables¶

Use python-dotenv.

Intall

pip3 install python-dotenv

Usage

# .env
PASSWORD=admin

from dotenv import load_dotenv
import os
load_dotenv() # load .env
password = os.getenv('PASSWORD')

dealing with URL¶

use urllib

convert dict to query string¶

use urllib.parse.urlencode

import urllib.parse

qjson = {'id': 1, 'medium': 'reddit'}
query = urllib.parse.urlencode(qjson)

requests¶

pip3 install requests

post¶

import requests
import json
data = dict()
request.post(<url>, data=json.dumps(data))

response¶

import requests
import
res = request.post(<url>, <data>)
status_code = res.status_code
res_body = json.loads(res.text)

Rounding numbers¶

To round but keep leading zeros, see https://stackoverflow.com/a/56776787/15493213

def fround(num: float, digits: int = 2) -> str:
    regex = r"0[1-9]"
    float_part = str(num).split(".")[1]
    float_limiter = re.search(regex,float_part).start() if float_part.startswith("0") else -1
    rounded = f'{num:2.{float_limiter+1+digits}f}'
    return rounded

Simple web server¶

python3 -m http.server

You can also use VsCode's Live Preview plugin.

Web Framework¶

Django
Flask

Database interaction¶

see SQLAlchemy

Floating Points¶

Floating points can only be approximated due to the binary nature of machines, so it's easy to create unexpected results when dealing with floating points.

https://docs.python.org/3/tutorial/floatingpoint.html

Troubleshooting¶

/usr/bin/env: ‘python’: No such file or directory¶

Assuming you have python3 installed, do

sudo ln -s /usr/bin/python3 /usr/bin/python

https://askubuntu.com/a/1235537

Python¶

pip¶

remove package¶

requirements.txt¶

create¶

use¶

venv (virtual environment)¶

pyenv¶

install¶

commands¶

import¶

import from subdirectory¶

import from parent¶

__name__¶

working directory¶

show current directory¶

change directory¶

Typing¶

Format¶

Type hinting opencv Mat¶

Class¶

Inheritance¶

Unit testing with unittest¶

Basics¶

Mock¶

VsCode Extension¶

Coverage¶

random¶

seed¶

shuffle¶

Hashing¶

matplotlib¶

Auto adjsut your figure layout¶

save figure¶

plot as many on demand¶

subplot on demand¶

style¶

legend¶

display Chinese character¶

gridline¶

axis label¶

axis min max value¶

axis interval¶

hide axis¶

log scale¶

datetime¶

exec¶

inputs¶

decorator¶

file¶

read file¶

Read file to dict/json¶

Save dict/json to file¶

yaml¶

load¶

dump¶

block literals¶

encode¶

encode to base 64¶

decode¶

decoding utf-8 encoded characters represented in unicode escaped sequence¶

trace exceptions¶

string¶

split¶

convert¶

str to json¶

datetime¶

datetime to string¶

string to datetime¶

current time¶

timedelta¶

iterate time with timedelta¶

Heap / Priority Queue¶

collections¶

OrderedDict¶

deque¶

Counter¶

sort¶

sort 2D list¶

sort dict by value¶

`name`¶

Unit testing with `unittest`¶