Basic of Python Programming¶

This is a practical introduction to Python Programming Language.
Python is an interpreted, high-level, and general purpose programming language that was designed for efficiency, readability, and simplicity.
Python is a popular and go-to programming language in different tech communities, most notable in machine learning and data science.
Python design philosophy emphasizes simplicity and code readability.
- It is simple to read and write: Python syntaxes are very easy to write and easy to recall as well.
- It has a beautiful design and built-in data types.
- It has thousands of great libraries in many disciplines.
- Supportive communities: Good documentation, courses, tutorials, social groups.
- Easy to learn and use due to its simple syntaxes which feel like a natural language.

This introduction will cover the following:

0. Basic Syntax and Structure
1. Variables and Data Types
2. Data Structures
3. Comparison and Logic Operators
4. Control Flow
5. Functions
6. Lambda Functions
7. Built in functions
- 7.1 Map Function
- 7.2 Filter Function
8. More Useful Python Stuff
9. Python Modules
10. Python Modules

# Import necessary modules
import sys
import keyword
import operator
from datetime import datetime
import os

## Keywords

Keywords are the reserved words in Python and can't be used as an identifier

print(keyword.kwlist) # List all Python Keywords

['False', 'None', 'True', 'and', 'as', 'assert', 'async', 'await', 'break', 'class', 'continue', 'def', 'del', 'elif', 'else', 'except', 'finally', 'for', 'from', 'global', 'if', 'import', 'in', 'is', 'lambda', 'nonlocal', 'not', 'or', 'pass', 'raise', 'return', 'try', 'while', 'with', 'yield']

import = 125 # Keywords can't be used as identifiers

Comments in Python¶

Comments can be used to explain the code for more readabilty.

# Single line comment
val1  = 10

# Convert 2 m temperature from Celsius to Kelvin (K = C + 273.15)
t2m_c = 27.3   # daily mean 2 m air temp in C
t2m_k = t2m_c + 273.15  # result in Kelvin
t2m_k

# Multiple line comment
'''
Multiple line comment
Multiple line comment
Multiple line comment
'''

"""
Multiple line comment
Multiple line comment
Multiple line comment
"""

Statements¶

Instructions that a Python interpreter can execute

Single line statement¶

p1 = 10 + 20
p1

Multiple line statement¶

p1 = 20 + 30 \
 + 40 + 50 +\
 + 70 + 80
p1

Multiple line statement¶

p2 = ['a' , 
    'b' , 
    'c' , 
    'd' 
     ]
p2

Indentation¶

Indentation refers to the spaces at the beginning of a code line.
It is very important as Python uses indentation to indicate a block of code.
If the indentation is not correct we will endup with IndentationError error.

p = 10
if p == 10:
    print ('P is equal to 10') # correct indentation

# if indentation is skipped we will encounter "IndentationError: expected an inde
p = 10
if p == 10:
print ('P is equal to 10')

for i in range(0,5):
    print(i)

# Count wet days (> 1 mm) using proper indentation
rain = [0.0, 0.8, 1.2, 5.0, 0.0, 2.0]
wet = 0
for x in rain:
    if x > 1.0:
        wet += 1  # wet = wet + 1
wet

Docstrings¶

1) Docstrings provide a convenient way of associating documentation with functions, classes, methods or modules.

2) They appear right after the definition of a function, method, class, or module.

def square(num):
    '''Square Function :- This function will return the square of a number'''
    return num**2

square(2)

square.__doc__  # We can access the Docstring using __doc__ method

def c_to_k(t_c: float) -> float:
    """Convert Celsius to Kelvin.

    Parameters
    ----------
    t_c : float
        Temperature in C.
    Returns
    -------
    float
        Temperature in Kelvin.
    """
    return t_c + 273.15

c_to_k(30.0)

c_to_k.__doc__

1. Variables and Data Types¶

1.1 Variables¶

Variable is a reserved memory location to store values.
A variable is created the moment you first assign a value to it.
A variable in Python can either be of 3 data types: integer, float, or a string.
Data type specifies the category of the variables.
We can use type(variable_name) to find the type of given variable_name.
Comments do not change anything and are not compiled.
The lines inside triple quotes are ignore during runtime.
We also use = to assign a value to the name of variable.
Example: var_name = 1. Note that it's different to comparison operator of equal to (==).
We can use print() to display the value of variable or the results of any expression.
Be aware of indentations. Python is serious about them.

p =30

'''
id() function returns the “identity” of the object. 
The identity of an object - Is an integer
                          - Guaranteed to be unique
                          - Constant for this object during its lifetime. 
'''
id(p)

Memory address of the variable¶

# Get the memory address in hexadecimal format using hex() function
hex(id(p))

p = 10
q = 10
r = p

# Checking the memory address of the variables
print( 
    id(p) , id(q) , id(r), 
    hex(id(p)) , hex(id(q)) , hex(id(r))
    )

station_id = "ADD001"     # Addis Ababa example code
lat, lon = 9.03, 38.74    # degrees
elev_m = 2355
print(station_id, lat, lon, elev_m)

Variable Assigment¶

Variable names in Python can contain alphanumerical characters
a-z, A-Z, 0-9 and some special characters such as _. Variable names must start with a letter.
By convention, variable names start with a lower-case letter
There are a number of Python keywords that cannot be used as variable names.

intvar = 10 # Integer variable
floatvar = 2.57 # Float Variable
strvar = "Python Language" # String variable
print(intvar)
print(floatvar)
print(strvar)

intvar, floatvar, strvar = 10, 2.57, "Python Language"  # Using commas to separate
print(intvar)
print(floatvar)
print(strvar)

p1 = p2 = p3 = p4 = 44 # All variables pointing to same value
print(p1,p2,p3,p4)

Data Types¶

1.2 Numbers¶

Numbers in Python can either be integers int or floats float.
Integer are real, finite, natural or whole numbers.
Take an example: 1,2,3,4 are integers.
Floats are numbers that have decimal points such as4.6, 6.0, 7.7.
Note that 4.0 is considered as a float data type too.
We can perform operations on numbers. The operations that we can perform include addition, multiplication, division, modular, etc...

int_var = 10
float_var = 12.8


print(type(int_var))
print(sys.getsizeof(val1)) # size of integer object in bytes

print(type(float_var))
print(sys.getsizeof(float_var)) # size of float object in bytes

# Unit conversions common in climate work
wind_ms = 6.0
wind_kmh = wind_ms * 3.6     # m/s -> km/h
precip_mm_day = 12.0
precip_m_day = precip_mm_day / 1000.0
print("Wind (km/h):", wind_kmh, "| Precip (m/day):", precip_m_day)

Boolean¶

Boolean data type can have only two possible values true or false.

bool1 = True

bool2 = False

print(bool1)
print(bool2)
print(type(bool1))
print(type(bool2))

Numeric Operations¶

# Addition

1 + 100

# Multiplication

1 * 100

# Division

1 / 100

# Floor division

## Floor division is a type of division that rounds the result down to the nearest whole number, discarding any fractional part.

7 // 2

# Modular (%)
# This is the remainder or a value remaining after dividing two numbers
# 100 / 1 = 100, remainder is 0

10 % 2

# Powers
# 1 power any number is 1 always

1 ** 100

2 ** 2

1.3 Strings¶

String is a sequence of characters.
Strings are one of the commonly used and important data types.
Strings are expressed in either "..." or '...'.

We can manipulate strings in many ways. A simple example is to concat the strings.

str_var = 'One'
str_var2 = 'Hundred'

str_var + str_var2

str_var + ' ' + 'and' + ' '+ str_var2 + '.'

# We can use print() to display a string

print(" This is a string")

# We can also compare strings to check whether they are similar. 
# If they are similar, case by case, comparison operator returns true. Else false

"A string" == "a string"

"A string" == "A string"

Strings Methods¶

Python provides many built-in methods for manipulating strings.

As a programmer, knowing typical string methods and how to use them will give you a real leverage when working with strings.

sentence = 'this IS A String'

# Case capitalization 
# It return the string with first letter capitalized and the rest being lower cases. 

sentence.capitalize()

# Given a string, convert it into title (each word is capitalized)

sentence_2 = 'this is a string to be titled'
sentence_2.title()

# Converting the string to upper case

sentence.upper()

# Converting the string to upper case

sentence.lower()

# Splitting the string

sentence.split()

You can use replace() method to replace some characters in string with another characters.
Replace method takes two inputs: characters to be replaced, and new characters to be inserted in string, replace('characters to be replaced', 'new characters').

Example, given the string "This movie was awesome", replace the world movie with project.

stri = "This movie was awesome"
stri.replace('movie', 'project')

# In the following string, replace all spaces with `%20'

stri_2 = "The future is great"
stri_2.replace(' ', '%20')

stri_3 = "Climate "
stri_3 = stri_3*5
stri_3

len(stri_3)

mystr = "Hello World"

mystr[0] # First character in string

String Indexing¶

mystr[-1]  # Last character in string

String Slicing¶

mystr[0:5]  # First five characters
# mystr[:5]  # From start to index 5

mystr[6:11] # From index 6 to index 10
# mystr[6:]  # From index 6 to end

mystr[-5:]  # Last five characters

del mystr # Delete a string
print(mystr)

mystr2 = "   Hello Everyone  "
mystr2

mystr2.strip() # Remove leading and trailing whitespace

mystr2.rstrip() # Remove trailing whitespace

mystr2.lstrip() # Remove leading whitespace

mylist =mystr2.split()
mylist

station_name = "Addis Ababa Observatory"
msg = f"Station {station_id} ({station_name}) at {lat:.2f} deg, {lon:.2f} deg"
msg

2. Data Structures¶

Data structures are used to organize and store the data.
Python has 4 main data structures: Lists, Dictionaries, Tuples and Sets.

2.1 List¶

A list is a set of ordered values.
Each value in a list is called an element or item and can be identified by an index.
A list supports different data types, we can have a list of integers, strings, and floats.

What we will see with Python lists:

Creating a list
Accessing elements in a list
Slicing a list
Changing elements in a list
Traversing a list
Operations on list
Nested lists
List methods
List and strings

Creating a List¶

A python list can be created by enclosing elements of similar or different data type in square brackets [...], or with range() function.

# Creating a list

week_days = ['Mon', 'Tue', 'Wed', 'Thur','Fri']
even_numbers = [2, 4, 6, 8, 10]
mixed_list = ['Mon', 1, 'Tue', 2, 'Wed', 3]

# Displaying elements of a list
print(week_days)
print(even_numbers)
print(mixed_list)

Accessing the elements of the list¶

We can access the a given element of the list by providing the index of the element in a bracket. The index starts at 0 in Python.

# Accessing the first elements of the list
week_days = ['Mon', 'Tue', 'Wed', 'Thur','Fri']
week_days[0]

# Get the third element of the list
even_numbers = [2, 4, 6, 8, 10]
even_numbers[2]

# Getting the last element of the list
even_numbers = [2, 4, 6, 8, 10]
print(even_numbers[-1])

Slicing a list¶

Given a list, we can slice it to get any parts or combination of its elements forming another list.

# Get the elements from index 0 to 2. Index 2 is not included.

week_days = ['Mon', 'Tue', 'Wed', 'Thur','Fri']
week_days[0:2]

# Get elements from the last fourth elements to the first
# -1 starts at the last element 'Fri', -2 second last element `Thur'..... -4 to 'Tue'

week_days[-4:]

# Get all elements up to the fourth index

week_days[:4]

# Get all elements from the second to the last index

week_days[2:]

You can use [:] to copy the entire list.

# Get all elements in the list
week_days[:]

Changing elements in a list¶

Python lists are mutable. We can delete or change the elements of the list.

names = ['James', 'Jean', 'Sebastian', 'Prit']
names

# Change 'Jean' to 'Nyandwi' and 'Sebastian' to 'Ras'

names[1:3] = ['Nyandwi', 'Ras']
names

# Change 'Prit' to Sun

names[-1] = 'Sun'
names

# Change `James` to `yonas`

names[0] = 'yonas'
names

In order to delete a given element in a list, we can empty slice it but the better way to delete element is to use del keyword.

# Delete Nyandwi in names list

del names[1]
names

If you know the index of the element you want to remove, you can use pop().
If you don't provide the index in pop(), the last element will be deleted.

names = ['James', 'Jean', 'Sebastian', 'Prit']
names.pop(2)
names

Also, we can use remove() to delete the element provided inside the remove() method.

names = ['James', 'Jean', 'Sebastian', 'Prit']
names.remove('James')
names

We can also use append() to add element to the list.

# Adding the new elements in list

names = ['James', 'Jean', 'Sebastian', 'Prit']
names.append('Jac')
names.append('Jess')
names

Operations on list¶

# Concatenating two lists

a = [1,2,3]
b = [4,5,6]

c = a + b

c

# We can also use * operator to repeat a list a number of times

[None] * 5

# Creating a list with repeated elements
[True] * 4

# Creating a list with repeated elements
[1,2,4,5] * 2

Nested lists¶

# Creating a list in other list

nested_list = [1,2,3, ['a', 'b', 'c']]


# Get the ['a', 'b', 'c'] from the nested_list

nested_list[3]

nested_list[3][0]  # Get 'a' from the nested list

# Indexing and slicing a nested list is quite similar to normal list

nested_list[1]

List Methods¶

Python also offers methods which make it easy to work with lists.
We already have been using some list methods such as pop() and append() but let's review more other methods.

# Sorting a list with sort()

even_numbers = [2,14,16,12,20,8,10]

even_numbers.sort()

even_numbers

# Reversing a string with reverse()

even_numbers.reverse()
even_numbers

# Adding other elements to a list with append()

even_numbers = [2,14,16,12,20,8,10]

even_numbers.append(40)
even_numbers

# Removing the first element of a list

even_numbers.remove(2)
even_numbers

## Return the element of the list at index x

even_numbers = [2,14,16,12,20,8,10]

## Return the item at the 1st index

even_numbers.pop(1)

week_days = ['Mon', 'Tue', 'Wed', 'Thur','Fri']

even_numbers

# pop() without index specified will return the last element of the list

even_numbers = [2,14,16,12,20,8,10]
even_numbers.pop()
even_numbers

# Count a number of times an element appear in a list

even_numbers = [2,2,4,6,8,2]
even_numbers.count(2)

List and strings¶

We previously have learned about strings. Strings are sequence of characters. List is a sequence of values.

# We can convert a string into list

stri = 'Apple'

list(stri)

# Splitting a string produces a list of individual words

stri_2 = "List and Strings"
stri_2.split()

The split() string method allows to specify the character to use a a boundary while splitting the string. It's called delimiter.

stri_3 = "state-of-the-art"

stri_3.split('-')

2.2 Dictionaries¶

Dictionaries are powerful Python data structure that are used to store data of `key and values.
A dictionary is a collection of key and values. A dictionary stores a mapping of keys and values. A key is what we can refer to index.
It is unordered, changeable, and does not allow duplicate keys.

What we will see:

Creating a dictionary
Accessing values and keys in dictionary
Solving counting problems with dictionary
Traversing a dictionary
The setdefault() method

Creating a dictionary¶

We can create with a dict() function and add items later
or insert keys and values right away in the curly brackets { }.

Let's start with dict() function to create an empty dictionary.

# Creating a dictionary

countries_code = dict()
print(countries_code)

You can verify it's a dictionary by passing it through type().

type(countries_code)

Let's add items to the empty dictionary that we just created.

# Adding items to the empty dictionary.

countries_code["Kenya"] = 254

countries_code

Let's create a dictionary with {}. It's the common way to create a dictionary.

countries_code = { 
        "Ethiopia": 251,
        "Kenya": 254,
        "Rwanda":250,
        "Uganda": 49,
        "Tanzania": 91,
}

countries_code

To add key and values to a dictionary, we just add the new key to [ ] and set its new value. See below for example...

countries_code['Djibouti'] = 253
countries_code

Accessing the values and keys in a dictionary¶

Just like how we get values in a list by using their indices, in dictionary, we can use a key to get its corresponding value.

# Getting the code of Rwanda

countries_code["Rwanda"]

We can also check if a key exists in a dictionary by using a classic in operator.

"India" in countries_code

# Should be False

"Kenya" in countries_code

To get all the keys, value, and items of the dictionary, we can respectively use keys(), values(), and items() methods.

# Getting the keys and the values and items of the dictionary

dict_keys = countries_code.keys() # Get all keys of the dictionary
dict_values = countries_code.values() # Get all values of the dictionary
dict_items = countries_code.items() # Get all items (key-value pairs) of the dictionary

print(f"Keys: {dict_keys}\n Values:{dict_values}\n Items:{dict_items}")

Lastly, we can use get() method to return the value of a specified key. Get method allows to also provide a value that will be returned in case the key doesn't exists. This is a cool feature!!

# Get the value of the Kenya

countries_code.get('Kenya')

countries_code

Traversing a dictionary¶

We previously used for loop in dictionary to iterate through the values. Let's review it again.

countries_code

for country in countries_code:
    print(country)

We can also iterate through the items(key, values) of the dictionary.

for country, code in countries_code.items():
    print(country, code)

The setdefault() Method¶

The setdefault() method allows you to set a value of a given key that does not already have a key.
This can be helpful when you want to update the dictionary with a new value in case the key you are looking for does not exist.

countries_code.setdefault("Somalia", 252)

countries_code

# Remove a key-value pair
countries_code.pop("UK")

countries_code

station = {
    "id": "ADD001",
    "name": "Addis Ababa Observatory",
    "coords": (9.03, 38.74),
    "daily_precip_mm": [0.0, 2.1, 0.0, 5.4, 1.2],
}
station["name"], station["coords"]

Summarizing dictionary

Dictionaries are not ordered and they can not be sorted - list are ordered (and unordered) and can be sorted.
Dictionary can store data of different types: floats, integers and strings and can also store lists.

2.3 Tuples¶

Tuple is similar to list but the difference is that you can't change the values once it is defined (termed as immutability).
Due to this property it can be used to keep things that you do not want to change in your program.
Example can be a country codes, zipcodes, etc...

coords = (9.03, 38.74)
lat, lon = coords    # tuple unpacking
lat, lon

# Empty tuple
tup1 = ()

 # tuple of integers numbers
tup2 = (10,30,60)  

print(tup2)

# tuple of float numbers
tup3 = (10.77,30.66,60.89)
print(tup3)

 # tuple of strings
tup4 = ('apple', 'banana', 'cherry')
print(tup4)

 # Nested tuples
tup5 = ('Asif', 25 ,(50, 100),(150, 90))

print(tup5)

# accessing elements in nested tuples

tup5[2]  # Accessing the third element which is a tuple (50, 100)

tup5[2][0]  # Accessing the first element of the third element which is 50

len(tup5) #Length of list

tup = (1,4,5,6,7,8,1)

# Indexing

tup[4]

tup[-1]

## Tuples are not changeable. Running below code will cause an error

tup[2] = 10

# You can not also add other values to the tuple. This will be error
tup.append(12)

# Get the length of a tuple
print(len(tup))

# Count occurrences of an element
print(tup.count(1))

Tuple Slicing¶

# tuple slicing 
tup = (1,4,5,6,7,8,1)

tup[-1]  # Accessing the last element which is 1
tup[0]   # Accessing the first element which is 1
tup[0:3] # Accessing elements from index 0 to 2
tup[-1:3] # Accessing elements from last to index 3

Sorting a tuple with sorted() function¶

tup = (5,2,8,1,4)

sorted(tup)  # Returns a sorted list of the tuple elements

sorted(tup, reverse=True)  # Returns a sorted list of the tuple elements in descending order

2.4 Sets¶

Sets are used to store the unique elements. They are not ordered like list.

codes = ["RA","RA","TS","BR","TS","NSW","DZ"]
unique_codes = set(codes)
unique_codes

set_1 = {1,2,3,4,5,6,7,8}

set_1

set_2 = {1,1,2,3,5,3,2,2,4,5,7,8,8,5}
set_2

len(set_2)

As you can see, set only keep unique values. There can't be a repetition of values.

# List Vs Set

odd_numbers = [1,1,3,7,9,3,5,7,9,9]

print("List:{}".format(odd_numbers))

print("********")

set_odd_numbers = {1,1,3,7,9,3,5,7,9,9}

print("Set:{}".format(set_odd_numbers))

3. Comparison and Logic operators¶

Comparison operators are used to compare values. It will either return true or false.

## Greater than 
100 > 1

## Equal to

100 == 1

## Less than

100 < 1

## Greater or equal to

100 >= 1

## Less or equal to

100 <= 1

'Intro to Python' == 'intro to python'

'Intro to Python' == 'Intro to Python'

Logic operators are used to compare two expressions made by comparison operators.

Logic and returns true only when both expressions are true, otherwise false.
Logic or returns true when either any of both expressions is true. Only false if both expressions are false.
Logic not as you can guess, it will return false when given expression is true, vice versa.

100 == 100 and 100 == 100

100 <= 10 and 100 == 100

100 == 10 or 100 == 100

100 == 10 or 100 == 10

not 1 == 2

not 1 == 1

4. Control Flow¶

We will cover:

If statement
For loop
While loop

4.1 If, Elif, Else¶

Structure of If condition:

if condition:
  do something

else:
  do this

if 100 < 2:

  print("This will not be printed")

if 100 > 2:

  print("This will be printed out")

if 100 < 2:

  print("As expected, no thing will be displayed")

else:
  print('Printed')

# Let's assign a number to a variable name 'jean_age' and 'yannick_age'

john_age = 30
luck_age = 20

if john_age > luck_age:
  print("John is older than Luck")

else:
  print(" John is younger than Luck")

# Let's use multiple conditions 

john_age = 30
luck_age = 20
yan_age = 30

if john_age < luck_age:
  print("John is older than Luck")

elif yan_age == luck_age:
  print(" Yan's Age is same as Luck")

elif luck_age > john_age:
  print("Luck is older than John")

else:
  print("John's age is same as Yan")

We can also put if condition into one line of code. This can be useful when you want to make a quick decision between few choices.

Here is the structure:

'value_to_return_if_true' if condition else 'value_to_return_if_false'

Let's take some examples...

# Example 1: Return 'Even' if below num is 'Even' and `Odd` if not. 

num = 45

'Even' if num % 2 == 0 else 'Odd'

# Example 2: Return True if a given element is in a list and False if not

nums = [1,2,3,4,5,6]

True if 3 in nums else False

pr = 8.0  # mm/day
if pr == 0:
    print("Dry day")
elif pr < 2.5:
    print("Light rain")
else:
    print("Rainy day")

4.2 For Loop¶

For loop is used to iterate over list, string, tuples, or dictionary.

Structure of for loop:

for item in items:
  do something

even_nums = [2,4,6,8,10]

for num in even_nums:
  print(num)

week_days = ['Mon', 'Tue', 'Wed', 'Thur','Fri']

for day in week_days:
  print(day)

sentence = "It's been a long time learning Python. I am revisiting the basics!!"

for letter in sentence:
  print(letter)

sentence = "It's been a long time learning Python. I am revisiting the basics!!"

# split is a string method to split the words making the string

for letter in sentence.split():
  print(letter)

# For loop in dictionary 

countries_code = { "United States": 1,
                 "India": 91,
                 "Germany": 49,
                 "China": 86,
                 "Rwanda":250
            }

for country in countries_code:
  print(country)

for code in countries_code.values():
  print(code)

For can also be used to iterate over an sequence of numbers.

Range is used to generate the sequence of numbers.

for number in range: 
  do something

for number in range(10):
  print(number)

for number in range(10, 20):
  print(number)

One last thing about for loop is that we can use it to make a list. This is called list comprehension.

letters = []

for letter in 'MachineLearning':
  letters.append(letter)

letters

The above code can be simplified to the following code:

letters = [letter for letter in 'MachineLearning']

letters

# Accumulate rain until we reach 10 mm
rain = [0.0, 0.5, 2.1, 7.8, 0.0, 0.0, 3.0]
total = 0.0
for r in rain:
    total += r # total = total + r
total

4.3 While loop¶

While loop will executes the statement(s) as long as the condition is true.

Structure of while loop

while condition:
  statement(s)

a = 10
while a < 20:
    print('a is: {}'.format(a)) # Display the value of a
    a = a + 1

# Walk forward until cumulative rain >= 10 mm or we run out of days
i, cumulative = 0, 0.0
while i < len(rain) and cumulative < 10.0:
    cumulative += rain[i]
    i += 1 # i = i + 1
i, cumulative

5. Functions¶

Functions are used to write codes or statements that can be used multiple times with different parameters.
One fundamental rule in programming is "DRY" or Do not Repeat Yourself.

This is how you define a function in Python:

def function_name(parameters):

  """
  This is Doc String
  You can use it to notes about the functions
  """
  statements 

  return results

* function_name is the name of the function. It must not be similar to any built in functions. We will see built in functions later. * parameters are the values that are passed to the function. * Doc String is used to add notes about the function. It is not a must to use it but it is a good practice.

return specify something or value that you want to return everytime you call or run your function.

# Function to add two numbers and return a sum

def add_nums(a,b):

  """
  Function to add two numbers given as inputs
  It will return a sum of these two numbers
  """

  sum = a+b

  return sum

add_nums(2,4)

add_nums(4,5)

# Displaying the doc string noted early

print(add_nums.__doc__)

def activity(name_1, name_2):

  print("{} and {} are playing basketball!".format(name_1, name_2))

activity("yonas", "Tamirat")

def c_to_k(t_c: float) -> float:
    """Convert Celsius to Kelvin.

    Parameters
    ----------
    t_c : float
        Temperature in C.
    Returns
    -------
    float
        Temperature in Kelvin.
    """
    return t_c + 273.15

c_to_k(30.0)

6. Lamdba Functions¶

There are times that you want to create anonymous functions.
These types of functions will only need to have one expressions.

## Sum of two numbers 

def add_nums(a,b):

  sum = a+b

  return sum

add_nums(1,3)

We can use lambda to make the same function in just one line of code! Let's do it!!

sum_of_two_nums = lambda c,d: c + d

sum_of_two_nums(4,5)

c_to_f = lambda c: c * 9/5 + 32
list(map(c_to_f, [20.0, 25.0, 30.0]))

¶

7. Built in Functions¶

Python being a high level programming language, it has bunch of built in functions which make it easy to get quick computations done.

# using len() to count the length of the string

message = 'Do not give up!'
len(message)

# Using max() to find the maximum number in a list

odd_numbers = [1,3,5,7]
max(odd_numbers)

# Using min() to find the minimum number in a list

min(odd_numbers)

# Sorting the list with sorted()

odd_numbers = [9,7,3,5,11,13,15,1]

sorted(odd_numbers)

Let's learn two more useful built functions: they are map and filter.

7.1 Map function¶

Map gives you the ability to apply a function to an iterable structures such as list.
When used with a list for example, you can apply the function to every element of the list.

Let's see how it works.

def cubic(number):
  return number ** 3

num_list = [0,1,2,3,4]

# Applying `map` to the num_list to just return the list where each element is cubed...(xxx3)

list(map(cubic, num_list))

# Convert a list of C to K using map
temps_c = [24.0, 26.5, 29.0]
temps_k = list(map(lambda c: c + 273.15, temps_c))
temps_k

7.2 Filter function¶

def odd_check(number):

  return number % 2 != 0 

# != is not equal to operation

# Create a list of numbers
num_list = [1,2,4,5,6,7,8,9,10,11]

# Applying `filter` to the num_list to just return the odd numbers in the list
list(filter(odd_check, num_list))

# Keep rainy days >= 1 mm
daily_mm = [0.0, 0.6, 1.2, 3.5, 0.0, 5.0]
wet_days = list(filter(lambda mm: mm >= 1.0, daily_mm))
wet_days

8. More Useful Python Stuff¶

Python is an awesome programming language that has a lot of useful functions.

Let's see more useful things you may need beyond what's we just saw already.

8.1 Enumerate Function¶

Enumerate function convert iterable objects into enumerate object. It basically returns a tuple that also contain a counter.

That's sounds hard, but with examples, you can see how powerful this function is...

seasons = ['Spring', 'Summer', 'Fall', 'Winter']

list(enumerate(seasons))

As you can see, each element came with index counter automatically. The counter initially start at 0, but we can change it.

list(enumerate(seasons, start=1))

Here is another example:

class_names = ['Spring', 'Summer', 'Fall', 'Winter']

for index, class_name in enumerate(class_names, start=0):
  print(index,'-',class_name)

# Find first day exceeding 35C
tmax = [30.0, 31.5, 34.9, 35.1, 33.0]
idx = None
for i, val in enumerate(tmax):
    if val > 35.0:
        idx = i
        break
idx

8.2 Zip Function¶

Zip is an incredible function that takes two iterators and returns a pair of corresponsing elements as a tuple.

name = ['Jessy', 'Joe', 'Jeannette']
role = ['ML Engineer', 'Web Developer', 'Data Engineer']

zipped_name_role = zip(name, role)
zipped_name_role

The zip object return nothing. In order to show the zipped elements, we can use a list. It's also same thing for enumerate you saw above.

list(zipped_name_role)

9. Python Modules¶

A Python module is a file containing Python code, such as functions, variables, or classes, that can be imported and used in another Python program.
Modules are reusable code libraries in Python.
You can import entire modules or specific functions/variables.
Built-in modules are ready to use, while external modules need installation with pip.

Types of Loading Modules - Import the entire module: You can import an entire module and access its functions or variables using the module name.

# Importing the math module
import math

# Use the sqrt function from the math module
result = math.sqrt(16)
print(result)

Importing Specific Functions or Variables¶

# Importing only the sqrt function from math

from math import sqrt

# Directly use the sqrt function
result = sqrt(25)
print(result)

Using an Alias ‘¶

You can give a module or function an alias (short name) for convenience.

# Using an alias for math
import math as m

# Use the alias to call functions
result = m.pow(2, 3)  # 2 raised to the power of 3
print(result)

Importing All Contents of a Module¶

You can import everything from a module, but this is not recommended as it may lead to naming conflicts.

# Importing all contents of math
from math import *

# Use functions without the module name
result = factorial(5)
print(result)

Built-in vs. External Modules¶

Built-in Modules: Python comes with several modules built-in. Examples include:

math (mathematical functions)
os (interacting with the operating system)
sys (system-specific parameters and functions)
random (random number generation)

External Modules: are not built into Python and need to be installed using a package manager like pip.

SciPy
Scikit-learn
TensorFlow
PyTorch
Keras

Getting Help with Modules¶

Using the help() Function: provides detailed documentation about a module.

# Getting help on the math module
import math
help(math)

Using the dir() Function: lists all attributes and functions available in a module.

# Listing all functions in the math module
import math
print(dir(math))

Creating Your Own Module¶

Create a Python file (e.g., my_module.py) with functions or variables.

def greet(name):
    return f"Hello, {name}!"

Using the custom module: import your module in another Python file or script.

import my_module

message = my_module.greet("Yonas")
print(message)

module_src = '''\
def heat_index_c(t_c: float, rh: float) -> float:
    """Approximate heat index in C (demo only)."""
    t_f = t_c * 9/5 + 32
    hi_f = (-42.379 + 2.04901523*t_f + 10.14333127*rh - 0.22475541*t_f*rh
            - 6.83783e-3*t_f*t_f - 5.481717e-2*rh*rh
            + 1.22874e-3*t_f*t_f*rh + 8.5282e-4*t_f*rh*rh
            - 1.99e-6*t_f*t_f*rh*rh)
    return (hi_f - 32) * 5/9
'''
open("climate_utils.py","w").write(module_src)

from climate_utils import heat_index_c
heat_index_c(32.0, 60.0)

10. Common Python Errors¶

Python errors, also called exceptions, occur when something goes wrong during the execution of your program.
Understanding these errors is key to debugging.

SyntaxError¶

SyntaxError occurs when the Python code violates the syntax rules.

print("Hello

print("Hello")  # Corrected version

NameError¶

happens when you use a variable or function that hasn’t been defined.

print(value)  # Trying to print a variable that hasn't been defined

# Corrected version:
value = 10
print(value)  # Output: 10

TypeError¶

TypeError occurs when an operation is performed on incompatible data types.

number = 5
text = "hello"

print(number + text)  # Trying to add a number to a string

# Corrected version:
print(f"{number} {text}")  # Output: 5 hello

IndexError¶

occurs when you try to access an index that’s out of range in a list or similar data structure.

numbers = [1, 2, 3]

print(numbers[3])  # Accessing an index that doesn't exist

# Corrected version:
print(numbers[2])

Debugging Basics¶

Debugging helps identify and fix errors in your program.
Python provides tools like try-except for error handling preventing the program from crashing abruptly when an exception occurs.
Graceful Recovery: can provide informative error messages or take alternative actions to recover from the error.

10 / 0

try:
    result = 10 / 0  # Division by zero causes ZeroDivisionError

except ZeroDivisionError: # except block catches specific errors and prevents the program from crashing.
    print("Error: Cannot divide by zero!")

Catch different types of errors¶

text

value = int("text")

try:
    value = int("text")  # This will cause a ValueError
except ValueError:
    print("Error: Cannot convert text to an integer!")
except TypeError:
    print("Error: There was a type mismatch!")

Catch any error¶

Using Exception catches any type of error.
The variable e contains information about the error.

try:
    result = 10 / 0  # This will cause a ZeroDivisionError
except Exception as e:
    print(f"An error occurred: {e}")

📝 Test Your Knowledge¶

Ready to test your Python programming skills? Take the interactive quiz to assess your understanding of Python basics, from variables and data structures to functions and error handling.

Take the Python Basics Quiz →

Basic of Python Programming¶

Comments in Python¶

Statements¶

Single line statement¶

Multiple line statement¶

Multiple line statement¶

Indentation¶

Docstrings¶

1. Variables and Data Types¶

1.1 Variables¶

Memory address of the variable¶

Variable Assigment¶

Data Types¶

1.2 Numbers¶

Boolean¶

Numeric Operations¶

1.3 Strings¶

Strings Methods¶

String Indexing¶

String Slicing¶

2. Data Structures¶

2.1 List¶

Creating a List¶

Accessing the elements of the list¶

Slicing a list¶

Changing elements in a list¶

Operations on list¶

Nested lists¶

List Methods¶

List and strings¶

2.2 Dictionaries¶

Creating a dictionary¶

Accessing the values and keys in a dictionary¶

Traversing a dictionary¶

The setdefault() Method¶

2.3 Tuples¶

Tuple Slicing¶

Sorting a tuple with sorted() function¶

2.4 Sets¶

3. Comparison and Logic operators¶

4. Control Flow¶

4.1 If, Elif, Else¶

4.2 For Loop¶

4.3 While loop¶

5. Functions¶

6. Lamdba Functions¶

¶

7. Built in Functions¶

7.1 Map function¶

7.2 Filter function¶

8. More Useful Python Stuff¶

8.1 Enumerate Function¶

8.2 Zip Function¶

9. Python Modules¶

Importing Specific Functions or Variables¶

Using an Alias ‘¶

Importing All Contents of a Module¶

Built-in vs. External Modules¶

Getting Help with Modules¶

Creating Your Own Module¶

10. Common Python Errors¶

SyntaxError¶

NameError¶

TypeError¶

IndexError¶

Debugging Basics¶

Catch different types of errors¶

Catch any error¶

📝 Test Your Knowledge¶

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