v1.1.0

Full Changelog: v1.0.6...v1.1.0

v1.0.5

What's Changed

• Added docstrings to all methods by @sn in #5

Full Changelog: v1.0.4...v1.0.5

v1.0.4

What's Changed

• Cleanups + updating the README.md file by @sn in #4

Full Changelog: v1.0.3...v1.0.4

v1.0.3

What's Changed

• Fixed numerous bugs by @sn in #3

Full Changelog: v1.0.2...v1.0.3

v1.0.2

What's Changed

• Fixed: both getattr and getitem - they need to wrap list items that are dicts. by @sn in #2

Full Changelog: v1.0.1...v1.0.2

v1.0.1

What's Changed

• Added: LLM SKILLS.md file and updated the versioning. by @sn in #1

New Contributors

• @sn made their first contribution in #1

Full Changelog: v1.0.0...v1.0.1

v1.0.0

nitro-datastore v1.0.0

The first stable release of nitro-datastore - a powerful Python library for managing JSON data with multiple access patterns and advanced querying capabilities.

Highlights

Three Ways to Access Your Data:

data.site.name              # Dot notation
data['site']['name']        # Dictionary access
data.get('site.name')    # Path-based

Chainable Query Builder:

results = (data.query('posts')
    .where(lambda p: p.get('published'))
    .sort(key=lambda p: p.get('views'), reverse=True)
    .limit(10)
    .execute())

Bulk Operations:

count = data.update_where(
    condition=lambda path, value: 'http://' in value,
    transform=lambda value: value.replace('http://', 'https://')
)

Path Introspection:

emails = data.find_paths('users.*.email')  # Pattern matching
stats = data.stats()                        # Data analysis

Key Features

• Multiple Access Patterns - Dot notation, dictionary-style, and path-based access
• Chainable Queries - Filter, sort, limit, group, and pluck with elegant API
• Bulk Operations - Transform data efficiently with conditional updates
• Path Operations - Glob patterns (*, **) and deep searching
• File I/O - Load/merge JSON files and directories with deep merging
• Data Introspection - Analyse structure, compare versions, track changes
• Transformations - Immutable transformations for keys and values
• Security - Path traversal protection, file size limits, circular reference detection
• Performance - 1.8M+ ops/sec, intelligent caching, sub-millisecond queries

Performance (5MB Dataset)

• get() operations: 1.8M ops/sec
• has() operations: 2.9M ops/sec
• Query 3,402 items: 0.0011s
• Bulk update 3,401 values: 0.0796s

Installation

pip install nitro-datastore

Quick Start

from nitro_datastore import NitroDataStore

data = NitroDataStore.from_directory('configs/')

active_users = data.query('users').where(lambda u: u.get('active')).execute()

data.set('app.version', '1.0.0')
data.save('output.json')

What's Included

• 0 Dependencies - Pure Python implementation
• Type Hints - Full type annotations with PEP 561 compliance
• 205 Tests - 100% test coverage
• 8 Examples - 2,589 lines of example code
• Security - Production-ready protection mechanisms

Documentation

See README.md for complete documentation and examples/ for detailed usage examples.

Requirements

• Python 3.7+
• No external dependencies

Get Started: pip install nitro-datastore