philipperemy

import requests
from bs4 import BeautifulSoup


def get_downloads_count(package_name: str):
    badge_url = f"https://static.pepy.tech/badge/{package_name}"
    response = requests.get(badge_url)
    download_count = int(
        BeautifulSoup(response.text, 'html.parser')
        .find_all('text')[-1].text.replace('k', '000').replace('m', '000000')

philipperemy

import numpy as np

# online computation of the mean and the variance.

class RollingMean:

    def __init__(self):
        self.st = 0.0
        self.n = 0

philipperemy

//  y-cruncher Configuration File
//  Version: 0.7.8 Build 9507
//
//  Load this from y-cruncher or run directly:
//      y-cruncher config filename.cfg
//
//  If you're copying Windows file paths into here, be sure to replace
//  all backslashes "\" with forward slashes "/". Backslash is an
//  escape character.
//

philipperemy

import numpy as np

# FIND LARGEST K ELEMENTS IN A 2D ARRAY IN NUMPY

def find_k_largest_elements_in_2d_array(arr: np.array, k=1):
    assert len(arr.shape) == 2
    h, w = arr.shape
    top_indices = np.flip(arr.flatten().argsort()[-k:])
    return np.divmod(top_indices, w)

philipperemy

import matplotlib
import matplotlib.pyplot as plt
import numpy as np

matplotlib.use('MACOSX')

img_h, img_w = 250, 500

img = np.zeros((img_h, img_w))

philipperemy

import tensorflow as tf
from tensorflow import keras
from tensorflow.keras.applications import Xception
import numpy as np

num_samples = 1000
height = 224
width = 224
num_classes = 1000

philipperemy

def new_chrome_browser(headless=True, download_path=os.path.dirname(os.path.abspath(__file__))):
    """Helper function that creates a new Selenium browser"""
    options = webdriver.ChromeOptions()
    user_agent = 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/60.0.3112.50 Safari/537.36'
    if headless:
        options.add_argument('headless')
        options.add_argument('--window-size=1280x1024')
        options.add_argument('--disable-gpu')
        # options.add_argument(f'user-agent={user_agent}')
    if download_path is not None:

philipperemy

import json

import requests

CODE_REQUEST_URL = "https://graph.accountkit.com/v1.2/start_login?access_token=AA%7C464891386855067%7Cd1891abb4b0bcdfa0580d9b839f4a522&credentials_type=phone_number&fb_app_events_enabled=1&fields=privacy_policy%2Cterms_of_service&locale=fr_FR&phone_number=#placeholder&response_type=token&sdk=ios"
CODE_VALIDATE_URL = "https://graph.accountkit.com/v1.2/confirm_login?access_token=AA%7C464891386855067%7Cd1891abb4b0bcdfa0580d9b839f4a522&confirmation_code=#confirmation_code&credentials_type=phone_number&fb_app_events_enabled=1&fields=privacy_policy%2Cterms_of_service&locale=fr_FR&login_request_code=#request_code&phone_number=#phone_number&response_type=token&sdk=ios"
TOKEN_URL = "https://api.gotinder.com/v2/auth/login/accountkit"

HEADERS = {

philipperemy

set -e

PACKAGES="$(find . -type f -iname "*.R" -exec cat {} + | grep "^library" | sed 's/library(//g' | cut -d ')' -f 1 | sed -e 's/^"//' -e 's/"$//' | sort -u | xargs)"

for package in $PACKAGES;
do
    echo "Installing package: ${package}..."
    rscript -e "install.packages('${package}', repos='https://cran.rstudio.com')"
done

philipperemy

# On Mac OSX

# Will run AIRODUMP scan of all BSSIDs
# sudo airport -s

# Will run AIRODUMP sniff on channel 11
# sudo airport en0 sniff 11
# Atm, I can't find how to sniff on all channels at the same time.

if [ $# -eq 0 ]