pyramid_mako | Mako templating system bindings for the Pyramid web | Application Framework library

import requests
import pandas as pd
import numpy as np
import plotly.express as px

state = requests.get(
    "https://raw.githubusercontent.com/satyam2829/Choropleth/main/us-states.json"
).json()
data = pd.read_csv(
    "https://raw.githu

import altair as alt
from vega_datasets import data

df = data.cars()

# 1. Create violin plot
violin = alt.Chart(df).transform_density(
    "Horsepower",
    as_=["Horsepower", "density"],
).mark_area().encode(
    x="Horsepower:Q",
    y

import numpy as np
from matplotlib import pyplot as plt

def f(x):
    return np.sin(x)

x = np.arange(0, 100, 0.1)
y = f(x)

fig, ax = plt.subplots()
ax.plot(x, y)
#this can be defined for each axis object either using a def function
#or 

from random import randint

num_iterations = 10000
num_people = 45
num_duplicates_overall = 0

# generate a random birthday for each person, check if there was a duplicate,
# and repeat num_iterations times
for i in range(num_iterations):

nl = [[800, 1], [400, 2]]  # each inner list is a fundraising project. the first number in each inner loop refer to the desired amount of money, and the second number is the number of the project

for i in range(3): # there will be 3 donat

import glob

Raw_txt = ""
files = [file for file in glob.glob(r'C:\\Users\\Hp\\Desktop\\RAW\\*.txt')]
for file_name in files:
    with open(file_name,"r+") as file:
        Raw_txt += file.read() + "\n" # I added a new line in case you wan

import simpy
import random

speed_1 = 3          # Avg. processing time of Machine 1 in minutes
speed_2 = 4          # Processing time of Machine 2 in minutes
time = 120           # Sim time in minutes


# Class setup for Machine 1 
# This

# import statements
from math import floor # method to round down to the nearest integer, see [here][1] 
from itertools import groupby # method to group by keys, see [here][2]

def function3(l, n): 
# as thebadgateway said, this looks like

import random
from typing import List

class Matrix:
    def __init__(self, N: int, M: int):
        ### Edit Here ###
        self.N = N
        self.M = M
        # make matrix with randInt
        self.matrix = [[]]
        self.rand_in

def overlaps(exons_dict):
    '''
    Computes overlap between all exons in the dictionary. Returns it as a list
    of (start, end) tuples, with start and end inclusive.

    >>> overlaps(EXAMPLE)
    [(77, 323), (1245, 1507), (6