Python Cheatsheet

Table of Content

Main
Basic and necessary commands needed to execute a well-defined python code at the command line.
Getting started with the language
Function
Data Structures
Pandas
- Data Structures in Pandas
NLTK
Errors and Exceptions
- Exceptions
Python Snippets

Main

if __name__ == '__main__':    # If file is not imported, this will be executed
    main()

Basic and necessary commands needed to execute a well-defined python code at the command line.

Opening a python shell.

$ python3

Installing a package

$ pip3 install <package-name>

Running a python script

$ python3 <filename>.py

Calculating the time of execution

$ time python3 <filename>.py

Importing a py script

import <filename>

Getting started with the language

Basic I/O

Input

input("Input: ")

Output Python automatically points the cursor to a new line. We need not specify explicitly.

print("Output")

Variables and Constants

In python, we need not specify the datatype of a variable. The interpreter interprets the value and assigns a suitabe datatype for that.

number = 0
org = "GitHub"

Conditional Statements

In python, we do not write a block of code in a pair of paranthesis. We write it after : followed by an indentation in the next line.

The conditional statements include if, if-else, nested if and so on...

x,y = 0,1
if x < y:
  print("x is less than y")
else:
  print("x is not less than y")

Note that the colon (:) following is required. Similarly, the nested if also works.

Iterative statements

As other programming languages, we have

for loop

for i in range(5):
  print(i)

The range function starts off with 0 till the number(excluded).

while loop

i=0
while(i < 10):
  print("{} is less than 10".format(i))
  i += 1

String formatting

There are a few ways to format a string in Python.

Using the % operator Strings can be formatted using the % operator:

>>> foo = 'world'
>>> 'Hello %s' % foo
'Hello world'

To subsitute multiple instances, wrap the right hand side in a Tuple:

>>> foo = 'James'
>>> bar = 'Nancy'
>>> 'Hi, my name is %s and this is %s' % (foo, bar)
'Hi, my name is James and this is Nancy'

You can also do variable subsitutions with a dictionary:

>>> dict = { "name": "Mike", "country": "Canada" }
>>> 'I am %(name)s and I am from %(country)s' % dict
'I am Mike and I am from Canada'

.format()

Introduced in Python 3, but is available in Python 2.7+

>>> 'Hello {}'.format('world')
'Hello world'

Similar to the above, subsitutions can be referred by name:

>>> 'Hi {name}, your total is ${total}'.format(name='Bob', total=5.50)
'Hi Bob, your total is $5.5'

f-Strings

Available in Python 3.6+. Works similar to the above, but is more powerful as arbitrary Python expressions can be embedded:

>>> a = 5
>>> b = 10
>>> f'Five plus ten is {a + b} and not {2 * (a + b)}.'
'Five plus ten is 15 and not 30.'

Function

Function is a block of code which runs when it is called.
Functions are declared using the def keyword. Function name must be a valid identifier.
Function arguments can be literal values, variables (valid identifiers), and expressions.

def sum(a, b) :
	return a + b

def subtract(a, b) :
	return a - b

def getPerson(name, age) :
	person = { "name": name, "age": age }
	return person

Function Call

Functions can be called by passing the arguments according to the declaration.

a = 20
b = 50
c = sum(a, b)
d = sum(b, 50)
e = subtract(b, a)
p = getPerson("Joe", 25)

# OUTPUT:
print( "Sum - {} plus {}: {}" . format( a, b, c ) ) # Sum - 20 plus 50: 70
print( "Sum - {} plus 50: {}" . format( b, d ) ) # Sum - 50 plus 50: 100
print( "Subtraction - {} minus {}: {}" . format( b, a, e ) ) # Subtraction - 50 minus 20: 30
print( "Person - {}" . format( p ) ) # Person - {'name': 'Joe', 'age': 75}

Function as Object

All data in a Python is represented by objects. There’s nothing particularly special about functions. They’re also just objects.

def yell(text):                   # Define function yell
	return text.upper() + '!'


>>> bark = yell                   # Declare an object "bark" that contains the function "yell"
>>> bark('woof')                  # You could now execute the "yell" function object by calling bark
'WOOF!'

Nested Function

Functions can be defined inside other functions. These are often called nested functions or inner functions.

def speak(text):                          # Define function speak
	def wisper(t):                    # Function wisper does not exist outside speak
		return t.lower() + '...'
	return wisper(text)


>>> speak('Hello, World')
'hello, world...'

Lambda

The lambda keyword in Python provides a shortcut for declaring small anonymous functions.

>>> add = lambda x, y: x + y
>>> add(5, 3)
8

You could declare the same add function with the def keyword, but it would be slightly more verbose:

def add(x, y):
	return x + y
>>> add(5, 3)
8

Data Structures

Lists

# These are all inplace operations returns a None value

<list>.append(<ele>)            # Add an element to the end of the list
<list>.sort()                   # Sorts the given list
<list>.pop([<ele>])             # Removes the last element if no argument else removes the element at the index given
<list>.clear()                  # Makes it an empty list
<list>.insert(<index>, <ele>)   # Adds the element before the index
<list>.extend(<iterator>)
<list>.reverse()                # Reverse a given list

# These are not inplace operations and has a return value

<list>.copy()                   # Makes a shallow copy of the list
<list>.index(<ele>)             # Returns the index of the given element
<list>.count(<ele>)             # Returns the number of occurrences of the element

Dictionaries

key-value pairs.

<dict> = {'Google':100, 'Facebook':80, 'Apple':90}

<dict>['Amazon'] = 85                           # Adding a key along with the value

# Accessing the dictionary
for key in <dict>:
  print("{key} -> {x}".format(key=key, x=<dict>[key]))

<dict>.keys()                                   # Print all the keys
<dict>.values()                                 # Print all the values
len(<dict>)                                     # Find the length of the dictionary
<dict>.pop(<key>)                               # Removes the item with the specified key name
<dict>.copy()                                   # Make a copy of a dictionary

A dictionary can also contain many dictionaries, this is called nested dictionaries.

Tuple

A tuple is a collection which is ordered, indexed and unchangeable. In Python tuples are written with round brackets.

this_tuple = ('books', 'pen', 'paper')          # Defined a tuple

# Accessing Tuple Items
print(this_tuple[2])                            # paper

Changing Tuple Values

Tuples are immutable, which means they cant to changed once they are created.
If a value inside tuple needs to be changed, the tuple must be converted to a list.
Newly created list can be converted back to tuple after updating changes.

desk_tuple = ("pen stand", "plant", "marker")
desk_list = list(desk_tuple)
desk_list[2] = "highlighter"
desk_tuple = tuple(desk_list)

print(desk_tuple[2])                            # highlighter

Creating tuple with one item

To create a tuple with only one item, you have to add a comma after the item, otherwise Python will not recognize it as a tuple.

this_tuple = ("Python",)
print(type(this_tuple))                         # tuple

# NOT a tuple
this_tuple = ("Python")
print(type(this_tuple))                         # str

Deleting a tuple

Tuples are unchangeable, so you cannot remove items from it, but you can delete the tuple completely:

this_tuple = ('books', 'pen', 'paper')
del this_tuple
print(this_tuple)                               # ERROR: this_tuple is not defined
## Third party libraries

Pandas

$ sudo pip3 install pandas          # Installing pandas module in Ubuntu

import pandas as pd

<dataframe>.head([<n>])             # Display the first n rows of the Dataframe, default value is 5 rows
<dataframe>.tail([<n>])             # Display the last n rows of the Dataframe, default value is 5 rows
<dataframe>.info()                  # Gives some information like, row and column datatypes, non-null count, and memory usage
<dataframe>.describe()              # Provides some descriptive statistics about the numerical rows in the dataframe

Data Structures in Pandas

In Pandas, total of three data structures are used

Series
DataFrame
Panel

#Series
sr = pd.Series([100, 200, 300, 400],
index=["red", "green", "yello", "black"])
print(sr)
print(sr.values)
print(sr.index)

#A series class has a structure that allows you to give values in one-dimensional arrays an index that corresponds to each value.

#DataFrame
values = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
index = ['one', 'two', 'three']
columns = ['A', 'B', 'C']

df = pd.DataFrame(values, index=index, columns=columns)
print(df)
print(df.index)
print(df.columns)
print(df.values)
#DataFrame passes a two-dimensional list as a parameter. Compared to a series, a data frame is added up to columns, consisting of columns, indexes, and values.

NLTK

$ sudo pip3 install nltk                    # Installing nltk module in Ubuntu

import nltk

# Before trying any function download the word list
nltk.download('punkt')
nltk.download('averaged_perceptron_tagger')

Errors and Exceptions

Program stops working on error Python raises exceptions when it encounter error.
To avoid this, try-catch blocks are used.

Exceptions

No syntax errors found, program starts execution.
Errors detected during execution are called exceptions.
Use try: except: finally: to catch and handle the exceptions.
Use try: except: finally: to avoid program termination on exceptions.
Use try: except: else: instead of try: except: finally: for alternate flows.
Multiple except can be use to catch the exceptions.

a = 10 * (1/0)

# Throws division by zero exception and terminate the program
# Traceback (most recent call last):
  File "", line 1, in
    a = 10 * (1/0)
# ZeroDivisionError: division by zero

# Updated Program - Valid - Try: Except: Finally
b = 10
try:
    a = 10 * (1/b)
    print( "a = {}" .format( a ) )
except:
    print( "Caught divide by zero - while getting a" )
    print( "Execute on error - b must be non-zero value" )
finally:
    print( "Execute Always - normal and exceptional flow" )

# OUTPUT
a = 1.0
Execute Always - normal and exceptional flow

## Updated Program - Error - Try: Except: Finally
b = 0
try:
    a = 10 * (1/b)
    print( "a = {}" .format( a ) )
except:
    print( "Caught divide by zero - while getting a" )
    print( "Execute on error - b must be non-zero value" )
else:
    print( "Alternate to exceptional flow" )

# Output
Caught divide by zero - while getting a
Execute on error - b must be non-zero value
Execute Always - normal and exceptional flow

Python Snippets

Anagrams

An anagram is a word or phrase formed by rearranging the letters of a different word or phrase, typically using all the original letters exactly once.

from collections import Counter
def anagram(first, second):
    return Counter(first) == Counter(second)
anagram("abcd3", "3acdb") # True

Memory

This snippet can be used to check the memory usage of an object.

import sys

variable = 30
print(sys.getsizeof(variable)) # 24

Print a string N times

This snippet can be used to print a string n times without having to use loops to do it.

n = 2
s ="Programming"
print(s * n) # ProgrammingProgramming

Chunk

This method chunks a list into smaller lists of a specified size.

def chunk(list, size):
    return [list[i:i+size] for i in range(0,len(list), size)]

Get vowels

This method gets vowels (‘a’, ‘e’, ‘i’, ‘o’, ‘u’) found in a string.

def get_vowels(string):
    return [each for each in string if each in 'aeiou']
get_vowels('foobar') # ['o', 'o', 'a']
get_vowels('gym') # []

Length of Last Word in a string

This method gets the length of last word in a given string.

def lengthOfLastWord(self, s: str) -> int:
        if(s.split()):
            lst=s.split()
            last=lst[-1]
            return len(last)
        return 0

Valid Palindrome

This method returns a bool value specifying whether a string is palindromic or not.

def isPalindrome(self, s: str) -> bool:
        s = [ x.lower() for x in s if x.isalnum() ]
        return s == s[::-1]

Check Lowercase

This method checks if a string is in lower case or not.

def toLowerCase(self, str):
        """
        :type str: str
        :rtype: str
        """
        return str.lower()

Count Negatives in a sorted Matrix

This method returns the count of negative numbers in a sorted matrix.

def countNegatives(self, grid: List[List[int]]) -> int:
        count = 0
        for num in grid:
            for n in num:
                if n < 0:
                    count += 1
        return count

Write to file

This method takes in the name of file and content then write the content into the file. If the file doesn't exist then it creates the file.

def write_to_file(filename, content):
  try:
    with open(filename, "w+") as f:
      f.write(content)
    print("Written to file successfully.")
  except Exception as e:
    print("Failed to write to file with error: ")
    print(e)

Median of given array

This method returns the median of the given list/array as an output.

import statistics
def median(arr):
    print(statistics.median(arr))

Even or Odd

This function determines the given number is even or odd.

def find_Evenodd(num):

    if(num%2==0):
        print(num," Is an even")
    else:
        print(num," is an odd")

Palindrome

This function returns "yes" if given string is a palindrome, else "no". Palindrome is a string whose reverse is the string itself.

def isPalindrome(s):
    if (s == s[::-1]):
        return "yes"
    else:
        return "no"

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