100 Days Of Python - Day 30

Day 30

Handling Errors and Exceptions

Errors

• Errors are mistakes that occur during the execution of a program.
• Errors are caused by invalid code.
• Some common errors in Python include:
  • KeyError - This error occurs when a dictionary does not have a specific key.
  • IndexError - This error occurs when you try to access an index in a list that does not exist.
  • NameError - This error occurs when a variable is not defined.
  • TypeError - This error occurs when an operation or function is applied to the wrong type.
  • ValueError - This error occurs when a built-in operation or function receives an argument that has the right type but an inappropriate value.

Exceptions

• Exceptions are errors that occur during the execution of a program.
• They are handled using try and except , else and finally statements.
• Exceptions are raised when the program encounters an error.

Try, Except, Else, and Finally

• try - except - else - finally statements are used to handle exceptions.
• try is used to test a block of code for errors and is used when we expect an error to occur.
• except is used to handle the exception. That is, if the try code does not work, the code in the except block will be executed.
  • except can be used to handle a specific error.
  • It can also be used to handle multiple errors.
  • It can be used to catch the error and print a message.
• else is used to execute code if the try code does not raise an exception.
• finally is used to execute code, regardless of whether the try code raises an exception or not.

Example

try:
    file = open("a_file.txt") # FileNotFoundError
    a_dictionary = {"key": "value"}
    print(a_dictionary["key"]) # KeyError
except FileNotFoundError:
    file = open("a_file.txt", "w") # Create a file
    file.write("Something")
except KeyError as error_message: # Catch the error and print a message
    print(f"The key {error_message} does not exist.") # The key 'key' does not exist.
else:
    content = file.read()
    print(content)
finally:
    file.close() # File was closed.
    print("File was closed.")# File was closed.

Raising Exceptions

• raise is used to raise an exception.
• raise can be used to raise a specific error with a type and a message.
• raise can be used in situations where we want to raise an error if a certain condition is met. For example, if we want to raise an error if a number is negative.

Example

height = float(input("Height: "))
weight = int(input("Weight: "))
if height > 3:
    raise ValueError("Human height should not be over 3 meters.")
bmi = weight / height ** 2
print(bmi)

• In the above example,
  • if the height is greater than 3,
  • a ValueError will be raised with the message Human height should not be over 3 meters.

IndexError Handling

• IndexError occurs when you try to access an index in a list that does not exist.
• IndexError can be handled using try and except statements.

Example

fruits = ["Apple", "Pear", "Orange"]
# IndexError: list index out of range
# print(fruits[3])
# Handle IndexError
try:
    print(fruits[3])
except IndexError:
    print("Index does not exist.")

• In the above example,
  • if the index does not exist,
  • the IndexError will be handled and the message Index does not exist. will be printed.

KeyError Handling

• KeyError occurs when a dictionary does not have a specific key.

Example

facebook_posts = [
    {"Likes": 21, "Comments": 2},
    {"Likes": 13, "Comments": 2, "Shares": 1},
    {"Likes": 33, "Comments": 8, "Shares": 3},
    {"Comments": 4, "Shares": 2},
    {"Comments": 1, "Shares": 1},
    {"Likes": 19, "Comments": 3},
]
total_likes = 0

# KeyError: 'Likes'
# for post in facebook_posts:
#     total_likes = total_likes + post["Likes"]
# print(total_likes)

# Handle KeyError
for post in facebook_posts:
    try:
        total_likes = total_likes + post["Likes"]
    except KeyError:
        pass
print(total_likes)

• In the abouve example,
  • we are trying to access the key Likes in the dictionary post.
  • In the first loop, the KeyError will be raised because the key Likes does not exist in the dictionary post.
  • In the second loop, the KeyError is handled and the loop will continue.

TypeError Handling

• TypeError occurs when an operation or function is applied to the wrong type.

• The following example is based on the NATO Phonetic Alphabet project from Day 26.
• If the user enters a name that contains a number, the TypeError will be raised. In order to handle the TypeError, we can use try and except statements.

Example

import pandas

data = pandas.read_csv("nato_phonetic_alphabet.csv")

phonetic_dict = {row.letter: row.code for (index, row) in data.iterrows()}

# TypeError: 'int' object is not iterable
# name = input("Enter a name: ").upper()
# nato_list = [phonetic_dict[letter] for letter in name]
# print(nato_list)

# Handle TypeError
try:
    name = input("Enter a name: ").upper()
    nato_list = [phonetic_dict[letter] for letter in name]
except KeyError:
    print("Sorry, only letters in the alphabet please.")
    generate_phonetic()
else:
    print(nato_list)

generate_phonetic()

# Output
# Enter a name: 123
# Sorry, only letters in the alphabet please.

JSON Data

• JSON stands for JavaScript Object Notation.

Writing JSON Data

• JSON data can be written to a file using the json module which is built into Python.
• The json module has the following methods:
  • dump() - Used to write data to a file.
  • dumps() - Used to convert a Python object into a JSON string.
• The dump() method takes two arguments:
  • The data to be written.
  • The file to write the data to.
  • and optionally, the indent argument which is used to format the JSON data.

Example

import json

# Create a dictionary
data = {
    "name": "John",
    "age": 30,
    "married": True,
    "divorced": False,
    "children": ("Ann", "Billy"),
    "pets": None,
    "cars": [
        {"model": "BMW 230", "mpg": 27.5},
        {"model": "Ford Edge", "mpg": 24.1},
    ],
}

# Convert the dictionary to a JSON string
json_data = json.dumps(data)

# Write the JSON data to a file
with open("data.json", "w") as file:
    json.dump(json_data, file, indent=4)

# Output
# {
#     "name": "John",
#     "age": 30,
#     "married": true,
#     "divorced": false,
#     "children": [
#         "Ann",
#         "Billy"
#     ],
#     "pets": null,
#     "cars": [
#         {
#             "model": "BMW 230",
#             "mpg": 27.5
#         },
#         {
#             "model": "Ford Edge",
#             "mpg": 24.1
#         }
#     ]
# }

Reading JSON Data

• JSON data can be read from a file also using the json module which is built into Python.
• The json module has the following methods:
  • load() - Used to read data from a file.
  • loads() - Used to convert a JSON string into a Python object.
• The load() method takes one argument:
  • The file to read the data from.
• It converts the JSON data into a Python dictionary.

Example

import json

# Read the JSON data from a file
with open("data.json", "r") as file:
    json_data = json.load(file)

# Convert the JSON data into a Python dictionary
data = json.loads(json_data)

print(data["name"]) # John

Updating JSON Data

• JSON data can be updated using the json module which is built into Python.
• The json module has the following methods:
  • load() - Used to read data from a file.
  • loads() - Used to convert a JSON string into a Python object.
  • dump() - Used to write data to a file.
  • dumps() - Used to convert a Python object into a JSON string.
• Update the JSON data as follows:
  • Read the JSON data from the file.
  • Convert the JSON data into a Python dictionary.
  • Update the Python dictionary.
  • Convert the Python dictionary into JSON data.
  • Write the JSON data to the file.

Example

import json

# Read the JSON data from a file
with open("data.json", "r") as file:
    json_data = json.load(file)

# Convert the JSON data into a Python dictionary
data = json.loads(json_data)

# Update the Python dictionary
data["age"] = 31

# Convert the Python dictionary into JSON data
json_data = json.dumps(data)

# Write the JSON data to a file
with open("data.json", "w") as file:
    json.dump(json_data, file, indent=4)

# Output
# {
#     "name": "John",
#     "age": 31,
#     "married": true,
#     "divorced": false,
#     "children": [
#         "Ann",
#         "Billy"
#     ],
#     "pets": null,
#     "cars": [
#         {
#             "model": "BMW 230",
#             "mpg": 27.5
#         },
#         {
#             "model": "Ford Edge",
#             "mpg": 24.1
#         }
#     ]
# }