nitro-datastore 1.0.1

Schema-agnostic JSON data store with dot notation, chainable queries, bulk operations, and built-in security features

Nitro DataStore

A flexible, schema-free data store for JSON in Python. Access nested data with dot notation, dictionary style, or path strings.

from nitro_datastore import NitroDataStore

data = NitroDataStore({'site': {'name': 'Nitro', 'url': 'https://nitro.sh'}})

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

No more config.get('site', {}).get('theme', {}).get('color', '#000'). Just config.get('site.theme.color', '#000').

Installation

pip install nitro-datastore

For AI coding assistants (Claude Code, etc.):

npx skills add nitrosh/nitro-datastore

Quick Start

Creating a DataStore

# From a dictionary
data = NitroDataStore({'title': 'Hello', 'settings': {'theme': 'dark'}})

# From a JSON file
data = NitroDataStore.from_file('config.json')

# From a directory (auto-merges all JSON files alphabetically)
data = NitroDataStore.from_directory('data/')

Reading & Writing

# Get with defaults
name = data.get('user.name', 'Anonymous')

# Set (creates intermediate dicts automatically)
data.set('config.cache.ttl', 3600)

# Check existence
if data.has('user.email'):
    email = data.get('user.email')

# Delete
data.delete('user.temp_token')

# Merge another datastore
data.merge(other_data)

Saving

data.save('output.json', indent=2)
plain_dict = data.to_dict()

Query Builder

Filter and transform collections with a chainable API:

data = NitroDataStore({
    'posts': [
        {'title': 'Python Tips', 'views': 150, 'published': True},
        {'title': 'Web Dev', 'views': 200, 'published': True},
        {'title': 'Draft', 'views': 0, 'published': False}
    ]
})

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

# Utilities
count = data.query('posts').where(lambda p: p.get('published')).count()
titles = data.query('posts').pluck('title')
by_category = data.query('posts').group_by('category')
first = data.query('posts').first()

Path Discovery

Explore unknown data structures:

# List all paths
paths = data.list_paths()

# Glob patterns (* = single segment, ** = any depth)
titles = data.find_paths('posts.*.title')
urls = data.find_paths('**.url')

# Find all occurrences of a key
all_urls = data.find_all_keys('url')

# Find values by predicate
emails = data.find_values(lambda v: isinstance(v, str) and '@' in v)

Bulk Operations

# Update all matching values
count = data.update_where(
    condition=lambda path, value: 'http://' in str(value),
    transform=lambda value: value.replace('http://', 'https://')
)

# Clean up
data.remove_nulls()
data.remove_empty()

Transformations

Transformations return new instances (immutable):

# Transform all values
upper = data.transform_all(lambda path, v: v.upper() if isinstance(v, str) else v)

# Transform all keys (e.g., kebab-case to snake_case)
snake = data.transform_keys(lambda k: k.replace('-', '_'))

Comparison

data1.equals(data2)  # True/False

diff = old.diff(new)
# {'added': {...}, 'removed': {...}, 'changed': {...}}

Security

Built-in protections for file operations:

# Path traversal protection
data = NitroDataStore.from_file(user_path, base_dir='/safe/directory')

# File size limits
data = NitroDataStore.from_file(path, max_size=10*1024*1024)

Also includes: path validation, circular reference detection.

Common Gotchas

Issue	Solution
Kebab-case keys (user-name)	Use data['user-name'] instead of dot notation
Keys with dots (key.name)	Use data['key.name'] - path methods treat dots as separators
Transform doesn't mutate	Assign the result: data = data.transform_keys(...)

Examples

See the examples/ directory for comprehensive demos:

• 01_basic_operations.py - Access patterns and CRUD
• 02_file_operations.py - Load, save, directory merging
• 03_querying.py - Query builder usage
• 04_path_operations.py - Path discovery and patterns
• 05_bulk_operations.py - Batch updates and cleanup
• 06_data_introspection.py - describe(), stats(), flatten()
• 07_comparison.py - diff() and equals()
• 08_comprehensive_example.py - Real-world workflow
• 09_security_features.py - Security protections

Ecosystem

• nitro-ui - Programmatic HTML generation
• nitro-cli - Static site generator
• nitro-dispatch - Plugin system
• nitro-validate - Data validation

License

MIT License. See LICENSE for details.