A Python project that fetches user data from a real JSON API and performs useful operations such as searching users, creating company summaries, and finding the user with the longest name.

Build a practical Python application that connects to an external API and processes the returned JSON data.

The project demonstrates:

API → JSON → Python → Data Processing → Analysis

• 🌐 Fetch data from a JSON API
• 🔎 Search users by name
• 🏢 Create company-wise user summaries
• 📏 Find the user with the longest name
• 📊 Process JSON data using Python
• ⚠️ Handle API request errors
• 🌐 Handle network failures
• ⏱️ Use request timeout
• 🧠 Work with nested JSON data

• Python
• REST API
• JSON
• requests
• Object-Oriented Programming
• Lists
• Dictionaries
• Lambda functions

python-json-api-analyzer/
│
├── main.py
├── api_analyzer.py
├── README.md
└── .gitignore

test_api.py was used during development to understand the API response and should not be uploaded to the final repository.

The project uses:

https://jsonplaceholder.typicode.com/users

JSONPlaceholder provides sample JSON data that can be used for learning and testing APIs.

pip install requests

python main.py

🌐 JSON API DATA ANALYZER
1. Search User
2. Company Summary
3. Longest Name
4. Exit

The application follows this flow:

Python Program
      ↓
API Request
      ↓
JSON API Response
      ↓
response.json()
      ↓
Python List / Dictionaries
      ↓
Data Processing
      ↓
Analysis / Output

The program sends a GET request:

response = requests.get(
    "https://jsonplaceholder.typicode.com/users",
    timeout=10
)

Sends a GET request to the API.

Prevents the program from waiting indefinitely for the server.

The API response is converted into Python data using:

data = response.json()

The returned data is mainly a list containing dictionaries.

For example:

data[0]["name"]

gets the first user's name.

For nested data:

data[0]["company"]["name"]

gets the first user's company name.

The application searches users by name:

if name.lower() in user["name"].lower():

Using .lower() makes the search case-insensitive.

For example:

Search: lean

can find:

Leanne Graham

The project creates a dictionary to count users by company:

summary = {}

For each user:

company = user["company"]["name"]

If the company is not already present:

if company not in summary:
    summary[company] = 0

Then its count is increased:

summary[company] += 1

This produces a summary such as:

Romaguera-Crona: 1 user(s)
Deckow-Crist: 1 user(s)
Romaguera-Jacobson: 1 user(s)

The project uses Python's max() with a lambda function:

user = max(
    users,
    key=lambda user: len(user["name"])
)

The key tells max() what value should be compared.

Here:

len(user["name"])

calculates the length of every user's name.

The user with the greatest name length is returned.

The project checks the HTTP status:

if response.status_code != 200:
    print("API request failed. ❌")
    return []

A successful API request normally returns:

200

The program also handles request/network errors:

except requests.RequestException:
    print("Network error. Please check your internet connection. ❌")
    return []

This prevents the application from crashing when a request fails.

Provides the HTTP status code of the API response.

Example:

200 → Successful request
404 → Resource not found
500 → Server error

Converts JSON response data into Python objects such as lists and dictionaries.

Converts text to lowercase.

Useful for case-insensitive comparisons.

Checks whether one value exists inside another.

Example:

"lean" in "leanne graham"

returns:

True

Used to find the maximum item according to a specific value.

Example:

max(users, key=lambda user: len(user["name"]))

This pattern:

if company not in summary:
    summary[company] = 0

summary[company] += 1

is a common Python technique for counting occurrences.

The project handles:

• Failed API requests
• Network errors
• Empty search input
• Invalid menu choices
• API timeout

• Classes
• Objects
• Methods
• Lists
• Dictionaries
• Nested dictionaries
• Loops
• Conditions
• String methods
• Lambda functions
• max()
• Exception handling

• REST API basics
• GET requests
• HTTP status codes
• JSON responses
• Nested JSON
• API timeout
• Network error handling

• requests.get()
• response.status_code
• response.json()
• requests.RequestException

Previous project:

CSV → Python → SQLite → SQL Analysis

Current project:

API → JSON → Python → Data Analysis

This project is an important step toward working with real APIs and eventually building AI applications that consume external data.

Possible upgrades:

• Add more API endpoints
• Search by email
• Search by company
• Search by city
• Display all users
• Add sorting
• Export API data to CSV
• Store API data in SQLite
• Add API caching
• Build a Streamlit interface
• Add charts and visualizations

Ayushman Tiwari

GitHub:

https://github.com/ayushman-ece

Completed ✅

This project demonstrates how Python can communicate with an external JSON API, process nested JSON data, and perform useful data analysis with error handling.