sertalpbilal

@ECHO OFF
for /r %%F in (*) do if %%~zF LSS 1000000 ( if %%~xF EQU .mp3 del "%%F" )

sertalpbilal

.header {
  max-height: 0px;
  visibility: hidden;
}

.fixed-title {
	position: fixed;
	display: block;
	top: 50px;
	max-width: 720px;

sertalpbilal

import requests
result = requests.get(r'https://www.microcenter.com/product/630283/amd-ryzen-9-5900x-vermeer-37ghz-12-core-am4-boxed-processor?storeid=071')
print(result.status_code) # This should be 200 if all goes OK
print(result.text) # This text will go to Beautiful Soup

sertalpbilal

You can save the python file to your machine, replace your team ID and run

python download_fpl_api.py

This will create a directory data and will include all files in JSON format.

sertalpbilal

   if punt_length is not None:
       punt_length = int(punt_length)
       final_gw = gameweeks[-1]
       model.add_constraints((so.expr_sum(transfer_out[p,w2] for w2 in range(w, w+punt_length)) <= 1-transfer_in[p,w] for p in players for w in gameweeks if w <= final_gw-punt_length+1), name='f_punt_length')

sertalpbilal

let get_all_data = () => {
    
    let gws = Array.from(jQuery(".ptsshoq")).map(i => i.textContent).filter(i => i.includes('GW')).map(i => parseInt(i.split('GW')[1]))
    let first_week = Math.min(...gws)
    let last_week = Math.max(...gws)

    let jsondata= jQuery("#fplr_api").text()
    let d=JSON.parse(decodeURIComponent(escape(window.atob(jsondata))))

    let main_keys = ['name', 'pos', 'team_abbrev', 'now_cost']

sertalpbilal

    bb_gw = 29

    model.add_constraints((so.expr_sum(lineup[p,w] for p in players) == 11 + (4 if bb_gw == w else 0) for w in gameweeks), name='lineup_count')
    model.add_constraints((so.expr_sum(bench[p,w,0] for p in players if player_type[p] == 1) == 1 - (1 if bb_gw == w else 0) for w in gameweeks), name='bench_gk')
    model.add_constraints((so.expr_sum(bench[p,w,o] for p in players) == 1 - (1 if bb_gw == w else 0) for w in gameweeks for o in [1,2,3]), name='bench_count')
    model.add_constraints((so.expr_sum(captain[p,w] for p in players) == 1 for w in gameweeks), name='captain_count')
    model.add_constraints((so.expr_sum(vicecap[p,w] for p in players) == 1 for w in gameweeks), name='vicecap_count')
    model.add_constraints((lineup[p,w] <= squad[p,w] for p in players for w in gameweeks), name='lineup_squad_rel')
    model.add_constraints((bench[p,w,o] <= squad[p,w] for p in players for w in gameweeks for o in order), name='bench_squad_rel')
    model.add_constraints((captain[p,w] <= lineup[p,w] for

sertalpbilal

getMyRank = () => {let me = parseFloat(jQuery("#my_dataviz9 .bubbles[r=6]")[0].getAttribute("cy")); let others = jQuery("#my_dataviz9 .bubbles[r=2]").toArray().map(i => parseFloat(i.getAttribute('cy'))); return others.filter(i => i < me).length + 1}; getMyRank()

sertalpbilal

from unicodedata import combining, normalize
import pandas as pd
import requests
from fuzzywuzzy import fuzz
import numpy as np

# To remove accents in names
def fix_name_dialect(name):
    new_name = ''.join([c for c in normalize('NFKD', name) if not combining(c)])
    return new_name.replace('Ø', 'O').replace('ø', 'o').replace('ã', 'a')

sertalpbilal

import pandas as pd
import pathlib
import os
import json
from unicodedata import combining, normalize
import requests
from fuzzywuzzy import fuzz
import numpy as np
from abc import ABC, abstractmethod