| # usage: python crack_pdf_password.py --pdf EAadhaar.pdf --age 70 | |
| import itertools | |
| import multiprocessing | |
| from multiprocessing import Manager, Pool | |
| from tqdm import tqdm | |
| from PyPDF2 import PdfReader | |
| import time | |
| import threading | |
| import argparse |
| // YT Tutorial: https://youtu.be/im3rWaN_2Qo | |
| import { useReducer } from "react"; | |
| const readObject = (obj, path) => { | |
| let val = null; | |
| if (path.includes(".")) { | |
| path | |
| .split(".") | |
| .map((path) => (val = val ? val[path] || null : obj[path] || null)); | |
| return val; |
| // Find the video element that is supposed to play the stream | |
| const videoElement = document.querySelector('video'); | |
| if (videoElement) { | |
| const stream = videoElement.srcObject; | |
| // Check if the stream is available and active | |
| if (stream instanceof MediaStream && stream.active) { | |
| // Get video tracks from the stream | |
| const videoTracks = stream.getVideoTracks(); |
| { | |
| "editor.formatOnSave": true, | |
| "python.formatting.provider": "black", | |
| "python.formatting.blackPath": "<path-to-black-formatter>" | |
| } |
| version: "3.8" | |
| services: | |
| app: | |
| image: nvidia/cuda:11.6.2-base-ubuntu20.04 | |
| command: nvidia-smi | |
| deploy: | |
| resources: | |
| reservations: | |
| devices: |
| import asyncio | |
| import fractions | |
| import logging | |
| import threading | |
| import time | |
| from typing import Optional, Set, Tuple | |
| import av | |
| from av import AudioFrame, VideoFrame | |
| from aiortc.mediastreams import AUDIO_PTIME, MediaStreamError, MediaStreamTrack |
Install aria2c:
sudo apt install aria2 -y
Use below command to utilize full bandwidth:
aria2c --file-allocation=none -c -x 10 -s 10 -d "mydir" URL --check-certificate=false
-c allows continuation of download if it gets interrupted, -x 10 and -s 10 allow up to 10 connections per server, and -d "mydir" outputs file to directory mydir.
| import torch | |
| import torchvision | |
| from torchvision import transforms | |
| from torch.utils.data import DataLoader | |
| data_path = './Archive_jpg/' | |
| transform_img = transforms.Compose([ | |
| transforms.Resize((480, 640)), | |
| # transforms.CenterCrop(256), |
| import redis | |
| import fakeredis | |
| import ujson | |
| from contextlib import suppress | |
| class RedisClient: | |
| def __init__(self, host=None, port=6379, db=0, prefix='libtorrent'): | |
| self.prefix = prefix | |
| self.host = host |