geeksambhu

from __future__ import annotations
from typing import Any, Dict, Iterable, Type, TypeVar, Protocol

from boto3.dynamodb.conditions import Attr, Key
from pydantic import BaseModel, ValidationError

T = TypeVar("T", bound=BaseModel)


class TableLike(Protocol):

geeksambhu

import time
import pyautogui
from random import randint, uniform, choice
pyautogui.FAILSAFE = False
NO_OF_WINDOWS = 3  # minimum 2

key_press = 0
mouse_move = 0

def pointer_move():

geeksambhu

accessible-pygments==0.0.5
alabaster==0.7.16
appnope==0.1.4
asttokens==2.4.1
attrs==23.2.0
Babel==2.15.0
beautifulsoup4==4.12.3
black==23.12.1
bleach==6.1.0
certifi==2024.7.4

geeksambhu

1. install npm

2. Run mkdir nepsealpha-scrap; cd nepsealpha-scrap; npm init

3. Install dependencies

npm install csv-writer puppeteer

geeksambhu

def download_file_from_url(url, folderpath):
    r = requests.get(url, allow_redirects=True, headers=headers, stream=True)
    if r.status_code == 200:
        print("\nDownloading.. %s"% url.split('/')[-1])
        with open('%s/%s'%(folderpath, url.split('/')[-1]), 'wb') as f:
            total_length = r.headers.get('content-length')
            if total_length is None:  # no content length header
                f.write(r.content)
            else:
                dl = 0

geeksambhu

'''
Interview hack: Memorize preorder/inorder/postorder tree ITERATORS (no recursion) and their reverses.
It simplifies a disproportionate number of questions to simple for loops (see below).

I consider the implementations below the simplest way to memorize the iterative tree traversal algorithms,
because they are so similar to each other, and to their respective recursive versions.

Notes:
- We only visit a node after we have expanded its children (i.e. added them to the stack) in the desired order.
- `x is curr` does the expanded flagging for us, because we always expand the current node.

geeksambhu

import json, csv
from collections import OrderedDict
_json=json.loads(open('data.json', 'r').read(), object_pairs_hook=OrderedDict)
out=open('converted.csv', 'w')
writer = csv.writer(out)
writer.writerow(_json[0].keys())
for row in _json:
    writer.writerow(row.values())

geeksambhu

Homebrew build logs for xapian on macOS 10.13.4
Build date: 2018-05-15 17:17:40

geeksambhu

# This is an example config for the mass publish script
# The outermost item is the section_id the articles belong in.
# The next level is the directory the articles are in, note that you can have
# multiple directories for one section_id, but not multiple entries of the same
# section_id. The final level is the names of the articles in the directory.

115001566429:
  html:
    - index.html:
    - installation.html:

geeksambhu

import re
class LogProcess:
    DATE_REGEX      = r"\d{4}\-\d{1,2}\-\d{1,2}"
    LOG_LEVEL_REGEX = r"(?<=\[)\w+(?=\])"
    
    
    def __init__(self, filename):
        self.logfile    = filename
        self.data       = {}
        self.logvalues  = {}