ndca 1.0.0

NDCA (Nested Data Collection API) — a fast, safe, and human-readable nested data storage and manipulation library for Python.

NDCA 1.0.0 — Nested Data Collection API

NDCA (Nested Data Collection API) is a high-performance, secure, and production-ready Python library for managing deeply nested structured data using a compact, human-readable format. It is designed for reliability, atomic persistence, safe in-memory operations, and a clean, intuitive API suitable for scripts, services, and small-to-medium projects.

Key Features:

• Human-readable format: Store and read nested dictionaries and lists in a clear, concise structure.
• Safe operations: All reads and writes use deep-copy semantics to prevent accidental mutation.
• Atomic file writes: Data is safely persisted to disk, ensuring integrity even during crashes or interruptions.
• Optional autosave: Automatically save changes to the assigned file (file("x.ndca", autosave=True)).
• Flexible path-based access: Get, write, and delete nested values using dot notation for dictionaries (a.b.c) and bracket notation for lists (arr[0], arr[]).
• Merge and append: Merge dictionaries (merge) or append items to lists (append) effortlessly.
• Pop and update: Remove or retrieve values (pop(path, default)) and update values with a callback (update(path, fn, default)).
• Numeric and boolean utilities: Increment numbers (incr(path, step)) and toggle booleans (toggle(path)).
• Key management: Rename keys or paths (rename(old_path, new_path)) and clear any path safely (clear_path(path)).
• Full serialization support: Convert to and from NDCA text format (dumps(data) / loads(text)).
• Version: 1.0.0 — stable, fully-featured, and production-ready.

Usage Example:

from ndca import NDCA, file, get, write, delete, wipe, save, dump, merge, append, pop, update, incr, toggle, rename, clear_path, loads, dumps

db = NDCA("data.ndca", autosave=True)
db.write("user.name", "Viren")
db.append("user.scores", 10)
db.incr("user.level")
db.toggle("user.active")
db.rename("user.name", "user.username")
text = db.dumps()
new_data = loads(text)