print("{greeting!r:20}".format(greeting="Hello"))

'Hello'

print("{one} {two!r}".format(one="ten", two="twenty"))

ten 'twenty'

import six

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import colors


colors_ = list(six.iteritems(colors.cnames))

# Add the single letter colors.
for name, rgb in six.iteritems(colors.ColorConverter.colors):
    hex_ = colors.rgb2hex(rgb)
    colors_.append((name, hex_))

# Transform to hex color values.
hex_ = [color …

import re

test = [ ('i sure like eating pie, but i love donuts', True),
         ('i sure like eating pie, but i hate donuts', True),
         ('i sure hate eating pie, but i like donuts', False) ]

rx = re.compile …

import numpy as np

x1 = np.arange(1,10).reshape(3,3)
print(x1.shape)

x1_new = x1[:,np.newaxis]
print(x1_new.shape)

(3, 3)
(3, 1, 3)

import pyutil as pyu
pyu.get_local_pyinfo()

'conda env: ml312-2024; pyv: 3.12.7 | packaged by Anaconda, Inc. | (main, Oct  4 2024, 13:27:36) [GCC 11.2.0]'

print(pyu.ps2("pandas"))

pandas==2.2.3

from functools import reduce
product = reduce((lambda x, y: x * y), [1, 2 …

import numpy as np
import pandas as pd

df = pd.read_csv('data1.csv')

df

from numba import jit
import numpy as np
import time

x = np.arange(100).reshape(10, 10)

@jit(nopython=True)
def go_fast(a): # Function is compiled and runs in machine code
    trace = 0
    for i in …

import re

pattern = re.compile("^([0-9]+)+$")

content  = "s23434"

if(pattern.match(content)):
    print(pattern.match(content).pos)
else:
    print('not matched')

not matched

content  = "23434"

if(pattern.match(content)):
    print('matched at : ', pattern.match(content).pos …

from collections import defaultdict

counter = defaultdict(int)

content = "one 2 1 three 4 2 1 7 6 six 8 9 8"

content

'one 2 1 three 4 2 1 …

import tensorflow as tf
import numpy as np
import os

# Just disables the warning, doesn't enable AVX/FMA
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'

a = np.zeros((3, 3))
ta = tf.convert_to_tensor(a)

with tf.Session …