Mini Dataset API

A generic REST API built with FastAPI that works with any CSV dataset. Load any CSV file, and instantly get endpoints to query, filter, sort, and summarize your data — without writing a single line of code for each new dataset.

Built as a portfolio project covering FastAPI, Pandas, Pydantic, REST API design, and generic/reusable backend architecture.

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Features

• Works with any CSV dataset — no code changes needed per dataset
• Filter rows by any column with operators: eq, gte, lte, contains
• Sort results by any column in ascending or descending order
• Paginate results with limit and offset
• Get column names and their data types via a dedicated endpoint
• Get descriptive statistics for all numeric columns
• Auto-generated interactive API documentation at /docs
• Configurable dataset path via environment variable

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Project Structure

mini-api/
├── data/
│   └── dataset.csv         # Your input CSV file goes here
├── app/
│   ├── __init__.py         # Empty — marks app as a Python package
│   ├── loader.py          # CSV loading and in-memory DataFrame storage
│   ├── filters.py         # Filtering and sorting logic
│   ├── models.py          # Pydantic response models
│   └── routes.py          # All API endpoint definitions
├── main.py                 # FastAPI app entry point
├── requirements.txt        # Project dependencies
└── README.md

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Setup

1. Clone the repository

git clone https://github.com/alizahai/mini-api.git
cd mini-api

2. Create and activate a virtual environment

python -m venv venv

# On Windows
venv\Scripts\activate

# On macOS/Linux
source venv/bin/activate

3. Install dependencies

pip install -r requirements.txt

4. Add your CSV file

Place your CSV file inside the data/ folder and name it dataset.csv. Or set a custom path via environment variable (see Configuration section).

5. Start the server

python main.py

The API will be live at http://127.0.0.1:8000

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Configuration

By default the API loads data/dataset.csv. To use a different file path, set the DATASET_PATH environment variable before starting the server:

# Windows
set DATASET_PATH=data/my_custom_file.csv

# macOS/Linux
export DATASET_PATH=data/my_custom_file.csv

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API Endpoints

GET /

Returns a welcome message and lists available endpoints.

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GET /columns

Returns all column names in the dataset and their data types. Call this first when working with a new dataset to know what columns are available for filtering and sorting.

Example response:

{
  "Registration Number": "object",
  "CGPA": "float64",
  "MT-111": "float64"
}

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GET /data

Returns rows from the dataset. Supports filtering, sorting, and pagination.

Parameter	Type	Default	Description
filter_col	string	None	Column name to filter on
filter_val	string	None	Value to filter by
filter_op	string	eq	Filter operator: eq, gte, lte, contains
sort_by	string	None	Column name to sort by
order	string	asc	Sort direction: asc or desc
limit	integer	100	Number of rows to return (max 1000)
offset	integer	0	Number of rows to skip (for pagination)

Filter operators:

Operator	Meaning	Works on
eq	Equal to	Numeric and text columns
gte	Greater than or equal to	Numeric columns only
lte	Less than or equal to	Numeric columns only
contains	Partial text match (case-insensitive)	Text columns only

Examples:

# Get first 100 rows
GET /data

# Filter by exact numeric value
GET /data?filter_col=CGPA&filter_val=3.5&filter_op=eq

# Filter rows where CGPA is 3.0 or above
GET /data?filter_col=CGPA&filter_val=3.0&filter_op=gte

# Filter by text match
GET /data?filter_col=Registration Number&filter_val=CS&filter_op=contains

# Sort by CGPA descending
GET /data?sort_by=CGPA&order=desc

# Combine filter, sort, and pagination
GET /data?filter_col=CGPA&filter_val=2.5&filter_op=gte&sort_by=CGPA&order=desc&limit=10&offset=0

# Get next page
GET /data?filter_col=CGPA&filter_val=2.5&filter_op=gte&sort_by=CGPA&order=desc&limit=10&offset=10

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GET /summary

Returns descriptive statistics for all numeric columns in the dataset.

Example response:

[
  {
    "column": "CGPA",
    "mean": 2.85,
    "median": 2.79,
    "std_dev": 0.52,
    "min": 1.2,
    "max": 3.94
  }
]

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Interactive Documentation

FastAPI automatically generates interactive API documentation. Once the server is running, open your browser and visit: http://127.0.0.1:8000/docs

You can explore all endpoints, see expected parameters, and test requests directly from the browser without any external tool.

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Dependencies

Library	Purpose
fastapi	Web framework for building the API
uvicorn	ASGI server that runs the FastAPI application
pandas	CSV loading, in-memory data storage, filtering and sorting
pydantic	Response model validation and JSON serialization

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Author

Aliza Haider GitHub: alizahai