deepdoctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models

path python pour les packages pip

.local/bin/jupyter-notebook

port serie

9 Data Visualization Techniques You Should Learn in Python

A simple CLI for you to create your resume using the Awesome CV template, and your personal website using the Dev Portfolio template, based on your LinkedIn profile.

pour créer des apk android en utilisant python

def de_bruijn(k, n):
"""
de Bruijn sequence for alphabet k
and subsequences of length n.
"""

alphabet = k
k = len(k)

a = [0] * k * n
sequence = []

def db(t, p):
    if t > n:
        if n % p == 0:
            sequence.extend(a[1:p + 1])
    else:
        a[t] = a[t - p]
        db(t + 1, p)
        for j in range(a[t - p] + 1, k):
            a[t] = j
            db(t + 1, t)
db(1, 1)
print(len(sequence))
#return ", ".join(alphabet[i] for i in sequence)
return "".join(alphabet[i] for i in sequence)

print(de_bruijn("01", 2))

Logme is a Python package that makes logging simple and robust. If you have found logging in Python not so straight forward, download this package and give it a try! :)

cheatsheet

import pandas as pd

df = pd.read_csv(r"C:\Users\micault.DOMPHILYO1\Documents\Perso\temp.csv", header= None, index_col =1)

df.drop(0, axis=1, inplace=True)
df.columns = ['temp', 'temp_dehors', 'conso_maison']
df.index = pd.to_datetime(df.index)
import numpy as np

df.replace('\N',np.nan, inplace = True)

df.temp.astype('float64')
df.temp = df.temp.astype('float64')
df.temp_dehors = df.temp_dehors.astype('float64')
df.conso_maison = df.conso_maison.astype('float64')

from matplotlib import pyplot as plt

df2 = df.resample("M").mean()

plt.plot_date(df2.index, df2.temp_dehors)
plt.plot_date(df2.index, df2.conso_maison)
plt.show()

pour ajouter un module externe au path de anaconda

et active l autocompletion sur vscode

bonne description d'une analyze avec machine learning