class NegativeMarksError(Exception):
   pass

def check_marks(mark):
    try:

        if(mark < 0):
            raise NegativeMarksError

        if(mark > 50):
            print('pass')
        else:
            print('fail')
    except ValueError:
        print('ValueError: Some value error')
    except TypeError:
        print('TypeError: Cannot …

def check_marks(mark):
    try:

        if(mark < 0):
            raise ValueError

        if(mark > 50):
            print('pass')
        else:
            print('fail')
    except ValueError:
        print('ValueError: Some value error')
    except TypeError:
        print('TypeError: Cannot convert into int')

check_marks …

from cachetools import TTLCache

cache = TTLCache(maxsize=10, ttl=10)

cache['city'] = 'Toronto'

cache['city']

'Toronto'

# Run the cell below after 10 seconds

cache['city']

'Toronto'

# more 
# https://stackoverflow.com/questions/31771286/python-in-memory-cache-with-time-to-live

from cachetools import TTLCache 
import time

cache = TTLCache(maxsize=10, ttl=10)

cache['city'] = 'Toronto'

print(cache['city'])

Toronto

time.sleep(5)

if('city' in cache):
    print(cache['city'])
else:
    print('Cache not found')

Toronto

time.sleep …

from bs4 import UnicodeDammit

print("inside main method")

dammit = UnicodeDammit(b"Sacr\xc3\xa9 bleu!")

inside main method

print(type(dammit))

<class 'bs4.dammit.UnicodeDammit'>

print(dammit.unicode_markup)

Sacré bleu!

print(type(dammit.unicode_markup))

<class 'str'>

print(dammit …

city = input("Enter your city : ")

Enter your city : Toronto

city

'Toronto'

import numpy as np
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split, GridSearchCV, cross_val_score
from sklearn.metrics import confusion_matrix, accuracy_score, classification_report

X = np.array(
    [
        [1, 1], [1, 2], [2 …

import pandas as pd

url = 'https://gist.githubusercontent.com/michhar/2dfd2de0d4f8727f873422c5d959fff5/raw …

# scipy
import scipy
print('scipy: %s' % scipy.__version__)

scipy: 1.2.1

# numpy
import numpy
print('numpy: %s' % numpy.__version__)

numpy: 1.16.2

# matplotlib
import matplotlib
print('matplotlib: %s' % matplotlib.__version__)

matplotlib: 3.0.3

# pandas …

import webanalyzer

w = webanalyzer.WebAnalyzer()

w.headers = {
    "User-Agent": "custom ua",
    "header-key": "header-value"
}

w.allow_redirect = True
w.aggression = 0
r = w.start("http://www.fatezero.org")

print(r)

[{'name': 'Script', 'origin': 'whatweb'}, {'name': 'HTML5', 'origin': 'whatweb'}, {'name': 'Fastly …