BexTuychiev

variable = 'Python'

if type(variable) in [set, int, str, dict, list, float, tuple, bool]:
    print('It is a built-in type')
else:
    print('Maybe not a built-in?')

BexTuychiev

generator = (number for number in range(10))

if type(generator) == "<class 'generator'>":
    print('Are you crazy?')

BexTuychiev

import types

generator = (number for number in range(10))

if isinstance(generator, types.GeneratorType):
    print("Finally, a generator!")

BexTuychiev

# A function to reverse a string
def reverse_string(text: str, upper: bool = False) -> str:
    reversed_text: str = text[::-1]
    if upper:
        return reversed_text.upper()
    return reversed_text

BexTuychiev

def function_name(arg1: type1, opt_arg: type2 = default) -> return_type:
    pass

BexTuychiev

import pandas as pd

"""Option One""""

# Load file as an ExcelFile object
excel = pd.ExcelFile('financial_sample.xlsx')
# Print out the sheet names
print(excel.sheet_names) # Prints out 'Sheet1' and 'Sheet2'

# Load the two sheets as individual DataFrames

BexTuychiev

from sas7bdat import SAS7BDAT
import pandas as pd

with SAS7BDAT('skinproduct.sas7bdat') as file:
    sas_df = file.to_data_frame()

print(sas_df)

BexTuychiev

import h5py

filename = 'ligo_data.hdf5'

data = h5py.File(filename, 'r')
print(data.keys())
# Values for each group can be accessed like this
print(data['meta'].value)

BexTuychiev

import pickle

with open('pickle_file.pkl', 'rb') as file:
    data = pickle.load(file)

print(data)

num_list = [range(1000000)]
# How to save a Python object to a pickle file
with open('new_pickle.pkl', 'wb') as file:

BexTuychiev

# Importing matlab files
import scipy.io
import pandas as pd

filename = "ja_data2.mat"

matlab = scipy.io.loadmat(filename)

print(type(matlab)) # prints out 'class <dict>'