neevdb 3.0.2

A lightweight file-based database engine built with pure Python

NeevDB 🗄️

A lightweight, file-based database engine built with pure Python — zero dependencies, zero setup.

NeevDB ("neev" = foundation in Hindi) is a database engine written from scratch in Python. It supports tables, CRUD operations, SQL-like queries, an interactive CLI shell, and a full REST API server.

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📦 Install

# Core — zero dependencies
pip install neevdb

# With REST API server support
pip install neevdb[server]

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📁 Project Structure

NeevDB/
├── neevdb/
│   ├── __init__.py       # Package entry point
│   ├── core.py           # Main database engine (CRUD + Query)
│   ├── storage.py        # File read/write layer
│   ├── query.py          # SQL-like query parser and executor
│   └── server.py         # Optional REST API server (FastAPI)
├── tests/
│   ├── test_core.py      # Core test suite (12 tests)
│   └── test_v2.py        # Full test suite (50+ tests)
├── api.py                # FastAPI REST API server
├── cli.py                # Interactive terminal shell
├── dashboard.html        # Browser dashboard UI
├── start.py              # One-command server launcher
├── pyproject.toml        # Package config
└── README.md

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⚡ Quick Start

from neevdb import NeevDB

db = NeevDB("mydata.json")

db.create_table("users")
db.insert("users", {"name": "Alice", "age": 25, "city": "Mumbai"})
db.insert("users", {"name": "Bob",   "age": 17, "city": "Delhi"})

# Find all
all_users = db.find_all("users")

# Find with condition
adults = db.find("users", lambda row: row["age"] > 18)

# Update
db.update("users", lambda row: row["name"] == "Bob", {"age": 20})

# Delete
db.delete("users", lambda row: row["name"] == "Alice")

# Count
total = db.count("users")

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🔍 Query Engine

db.query("SELECT * FROM users")
db.query("SELECT * FROM users WHERE age > 18")
db.query("SELECT name, city FROM users")
db.query("SELECT * FROM users ORDER BY age")
db.query("SELECT * FROM users ORDER BY age DESC")
db.query("SELECT * FROM users LIMIT 5")
db.query("SELECT name, city FROM users WHERE age > 18 ORDER BY name LIMIT 3")

Supported WHERE operators

Operator	Meaning	Example
=	Equal to	WHERE city = Mumbai
!=	Not equal to	WHERE status != draft
>	Greater than	WHERE age > 18
<	Less than	WHERE price < 500
>=	Greater or equal	WHERE score >= 90
<=	Less or equal	WHERE stock <= 10

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🌐 REST API Server

Start the server with one command:

python start.py

Or with a custom database file:

python start.py mydata.json

Browser opens automatically at http://localhost:8000 with the dashboard.

From Python:

from neevdb.server import start
start(db_path="mydata.json", host="0.0.0.0", port=8000)

API Endpoints

Method	Endpoint	Description
GET	/api	Health check
GET	/api/stats	Database statistics
GET	/api/tables	List all tables
POST	/api/tables/{name}	Create a table
DELETE	/api/tables/{name}	Drop a table
GET	/api/tables/{name}/records	Get records (+ filters)
GET	/api/tables/{name}/records/{id}	Get record by ID
POST	/api/tables/{name}/records	Insert a record
PUT	/api/tables/{name}/records/{id}	Update a record
DELETE	/api/tables/{name}/records/{id}	Delete a record
POST	/api/query	Run SQL-like query

Query parameters for GET /records

?where=age>18          → Filter records
?order=name            → Sort by field
?desc=true             → Sort descending
?limit=5               → Max records

Use from any frontend

// Fetch users older than 18, sorted by name
const res  = await fetch('http://localhost:8000/api/tables/users/records?where=age>18&order=name')
const data = await res.json()
console.log(data.records)

// Insert a record
await fetch('http://localhost:8000/api/tables/users/records', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({ data: { name: 'Alice', age: 25 } })
})

// Run a query
const res = await fetch('http://localhost:8000/api/query', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({ query: 'SELECT * FROM users WHERE age > 18 ORDER BY name LIMIT 5' })
})

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💻 CLI Shell

python cli.py
python cli.py mydata.json

NeevDB > SHOW TABLES
NeevDB > CREATE TABLE users
NeevDB > INSERT INTO users name=Alice age=25 city=Mumbai
NeevDB > SELECT * FROM users WHERE age > 18
NeevDB > SELECT * FROM users ORDER BY age DESC LIMIT 5
NeevDB > DELETE FROM users WHERE name = Alice
NeevDB > DROP TABLE users
NeevDB > HELP
NeevDB > EXIT

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🧪 Running Tests

# Core tests (12 tests)
python tests/test_core.py

# Full test suite (50+ tests)
python tests/test_v2.py

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🛠️ How It Works

Your Code / CLI / Browser
         │
         ▼
    NeevDB Core       ← CRUD operations, table management
         │
         ├──► Query Engine   ← Parses SQL-like strings
         │
         ├──► Storage        ← Reads/writes JSON file to disk
         │
         └──► REST API       ← FastAPI server (optional)
                  │
                  └──► Dashboard HTML  ← Browser UI

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📦 Zero Dependencies (Core)

Module	Used for
json	Saving and loading data
os	File path checks
re	Query string parsing
datetime	Auto-generating timestamps
sys	CLI argument handling

Optional server dependencies: fastapi, uvicorn

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🚀 Built By

Manish Dange — built NeevDB from scratch as a learning project. "Neev" means foundation in Hindi — this is the foundation of something bigger.

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📌 Changelog

v3.0.1

• Fixed bug and errors

v3.0.1

• Fixed dashboard loading from any folder
• API endpoints unified under /api/ prefix
• start.py always runs from correct directory

v3.0.0

• Fixed dashboard loading from any folder
• Improved error messages

v2.0.0

• Optional REST API server (pip install neevdb[server])
• from neevdb.server import start — one line server start
• Dashboard HTML UI
• Full test suite (50+ tests)

v1.0.0

• JSON file storage
• Tables, CRUD operations
• SQL-like query engine (SELECT/WHERE/ORDER BY/LIMIT)
• Interactive CLI shell
• 12 passing tests

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📌 Roadmap

• Phase 1 — JSON storage, Tables, CRUD
• Phase 2 — Query Engine (SELECT/WHERE/ORDER BY/LIMIT)
• Phase 3 — Interactive CLI Shell
• Phase 4 — PyPI publish (pip install neevdb)
• Phase 5 — REST API server + Browser Dashboard
• Phase 6 — Indexes for faster queries
• Phase 7 — Multi-table JOIN support
• Phase 8 — Deploy to cloud (Railway/Render)