juanarrivillaga

# So, assuming the lists have the same length, e.g.:

dummy_data = {
    "Date":["01/24/2029","10/28/2027", "01/24/2024","03/24/2024"],
    "Company Name":["Mcdonalds", "Burger King", "KFC","Popeyes"],
    "File_name_location":["C/Documents/Files/invoice1.pdf", "C/Documents/Files/invoice1.pdf","C/Documents/Files/invoice1.pdf", "C/Documents/Files/invoice1.pdf"],
}

# Then, to sort everything, simply get a list of sorted indices. 
# This can be done easily. Since you don't want `datetime.date` objects 

juanarrivillaga

import types
import copy

def clone_class(klass):
    def _exec_body(ns):
        ns_no_slots = {
            k:v for k,v in vars(klass).items()
            if not isinstance(v, types.MemberDescriptorType)
        }
        ns |= copy.deepcopy(ns_no_slots)

juanarrivillaga

import datetime

DAYS_IN_MONTH = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]


def is_leap_year(year: int) -> int:
    return year % 4 == 0 and (year % 100 != 0 or year % 400 == 0)


def add_months(date: datetime.date, months: int) -> datetime.date:

juanarrivillaga

class BagOfClass(type):
    class Value:
        pass

    def __iter__(klass):
        for attr_value in vars(klass).values():
            if isinstance(attr_value, type) and issubclass(
                attr_value, BagOfClass.Value
            ):
                yield attr_value

juanarrivillaga

class SimpleSuper:
    def __init__(self, cls, instance):
        self.cls = cls
        self.instance = instance
    def __getattr__(self, name):
        mro = type(self.instance).mro()
        next_cls = mro[mro.index(self.cls) + 1]
        attribute = getattr(next_cls, name)
        if hasattr(attribute, "__get__"):
            return attribute.__get__(self.instance, self.cls)

juanarrivillaga

import matplotlib.pyplot as plt
import pandas as pd
from timeit import timeit

setup = """
def list_comp(d):
    return [ (x*2)/3 for x in d ]

def pre_allocate(d):
    result = [None]*len(d)

juanarrivillaga

import pandas as pd
import matplotlib.pyplot as plt
from timeit import timeit
from tqdm import tqdm

gen_exp = "tuple(x for x in range({}))"
list_comp = "tuple([x for x in range({})])"


N = range(1, 500_001, 5000)

juanarrivillaga

def parse_code(msg):
    f,l,i=[item for item in msg.split('0') if len(item)>0]  
    return {'first_name':f,'last_name':l,'id':i}

def parse_code(msg):
    result = []
    for item in msg.split("0"):
        if len(item) > 0:
            result.append(item)
    f,l,i = result

juanarrivillaga

import pandas as pd
df = pd.read_csv('en_bigram.csv')
st = df[df["right"] == "some_text"]["left"]
st[st.str.startswith("My")].to_list()


# using a dict reader
import csv
result = []
with open("en_bigram.csv") as f:

juanarrivillaga

class Range:
    def __init__(self, start, stop, step=1):
        self.start = start
        self.stop = stop
        self.step = step
    def __getitem__(self, index):
        result = self.start + index*self.step
        if result >= self.stop:
            raise IndexError("Index out of range")
        return result