juanarrivillaga

from timeit import timeit
import pandas as pd, numpy as np
import matplotlib.pyplot as plt

N = range(500, 100001, 500)

setup1 = 'import numpy as np; n = {}; fv = np.frompyfunc("{{}}_{{}}".format, 2, 1); a = np.arange(n); b = a + a.size'
stmt1 = "fv(a, b)"

from_func = [

juanarrivillaga

from typing import List
def non_intersecting(L1: List[List[str]], L2: List[str]) -> List[List[str]]:    
    """Return a new list that contains the original lists inside L1 that do not
    contain any of the string in L2

    >>> non_intersecting([['e', 'h', 'c', 'w'], ['p', 'j'], ['w', 's', 'u']], ['k', 'w'])
    [['p', 'j']]
    """
    bad = set(L2)
    result = []

juanarrivillaga

In [1]: import numpy as np

In [2]: lst = list(range(100000))

In [3]: import random

In [4]: idx = random.sample(lst, 100000//2)

##################################################################################
# List comprehension vs naive for-loop, list comprehension less than twice as fast

juanarrivillaga

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

gen = 'sum(1 for x in seq if x < 0)'

floop = '''
result = 0
for x in seq:
    if x < 0:

juanarrivillaga

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

sc = '[i for i in range({})]'
sg = 'list(i for i in range({}))'

N = range(1, 1000001, 10000)

tc = [timeit(sc.format(n), number=10) for n in N]

juanarrivillaga

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

stmt = "-1 in mydict.values()"
setup = "mydict = dict(zip(range({0}),range({0})))".format

N = range(0, 100001, 1000)

def timer(n, k):

juanarrivillaga

import functools
import timeit
import pandas as pd
import itertools

def flatten(nested):
    result = []
    for sub in nested:
        for x in sub:
            result.append(x)

juanarrivillaga

import functools
from collections import namedtuple

def namedtuple_me(series, name='S'):
   klass =  _get_class(tuple(series.index), name)
   return klass._make(series)

@functools.lru_cache(maxsize=None)
def _get_class(fieldnames, name):
    return namedtuple(name, fieldnames)

juanarrivillaga

In [21]: import numpy as np

In [22]: arr = np.arange(1, 10000)

In [23]: lst = list(range(1, 10000))

In [24]: def f():
    ...:     for x in arr:
    ...:         pass
    ...:

juanarrivillaga

import timeit
from pprint import pprint

s1 = """
if x == 1:
    y = 31
elif x == 2:
    y = 28
elif x == 3:
    y = 31