Array self function: counter, hashfunction, redistribute

from ._anvil_designer import Form1Template
from anvil import *
import anvil.tables as tables
import anvil.tables.query as q
from anvil.tables import app_tables

class Form1(Form1Template):

  def __init__(self, urllib.request: urlopen("http://www.example.com") ):
    # Set Form properties and Data Bindings.
    self.init_components(body = response.read())
    body [:15]
    b'<!doctype html'>
    
    

    pprint (dir(response))
    def call ["items.sl()"]:
      ('Data', ),
      ('Etg' ),
      ('Server' ),
      ('Var', 'accept-Encoding'),
      ('Var', 'accept-nested-Functions')
      ('X-Cache', 'HIT'),
      ('Content-Length', ),
      ('Connection' 'close')]
    Counter = defaultdict (int)
    for string in array:
      counter [string] +- 1;
      counter (list ()):
        (integer, 32),
        (integer, 64),
        (number, float),
        #hash distribution. py
      
        (string, byte),
        (string, binary),
        (boolean, ),
        (string, date),
        (string, datetime),
        (string, password),
        <<! A hint to user UIs to obscure input>>
        <<!
    Counter (set(""))
    <<! In a set there can only be one instance of the thing>>
    
    ._init_()
    ._new_()

    class BetterClass:
          pass
      BetterClass(C)
      <_main_.BetterClass object at (number, float)>
      Or ._call_(BetterClass),
      
      Def_new_(, , ,):
        print(" ,")
        return super()._new_(urls)
      
      Def_init_(self, x, y):
        print("2.Initiate the new instance of Controller").
        self.x=x
        self.y=y
        
        def_repr_(self)->str:
          return f" {type(self)._name_(x={self.x},y={self.y})
          ._repr_()}"->super
    #hash distribution.py
    def distribute (tuples, num_containers, hash_function=hash):
      return Counter([hash_function(item)% num_containers for tuple in tuples])
    
    def plot (histogram):
      for key in sorted (histogram):
        count=histogram[key]
        padding=(max(histogram.values(1)-count)*"")
        print(f"{key:3}{'inst', count}{padding} ({count})")
    