ndca 5.0.0

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

NDCA 5

Nested Data Collection API
Version 5.0.0

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INFO

NDCA 5 (Nested Data Collection API) is a high-performance, production-ready Python library for storing, reading, and manipulating nested structured data using a compact, human-readable format. It supports atomic persistence, safe in-memory operations, advanced table utilities, pagination, CSV import/export, and hash-verified writes.

Version 5.0.0 introduces enhanced table features, multi-level inheritance, Unicode support, advanced error handling, autosave, and improved list and dictionary utilities.

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FEATURES

• Human-readable nested data format
• Nested objects, lists, and tuples
• Safe deep copy operations
• Atomic file writing and autosave
• Path-based nested access
• Dictionary merging and inheritance
• Increment, toggle, and append/remove helpers
• Hash-verified writes
• Import/export and CSV support
• Table utilities with row indexing, sorting, and pagination
• Multi-level parent references
• Production-ready stability and error handling

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INSTALLATION

Install via pip by running the following command in your terminal:

pip install ndca

Alternatively, include NDCA directly in your project by copying the module files.

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NDCA FORMAT

Compact structured syntax for nested data.

OBJECT FORMAT

<[key]="value";[key2]=123;[key3]=true;>

LIST FORMAT

(value1;value2;value3;)

NESTED STRUCTURE

<[name]="Viren";[age]=12;[skills]=("Python";"Bash";"NDCA");[settings]=<[theme]="dark";[enabled]=true;>;>

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FORMAT RULES

• Objects start with < and end with >
• Keys are wrapped in [key]
• Key-value pairs are separated by =
• Each item ends with ;
• Lists use ( )
• Strings use " "
• Booleans are true and false
• Null values use null
• Nested structures are fully supported

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BASIC USAGE

from ndca import NDCA

store = NDCA()

store.write("user", '<[name]="Viren";[age]=12;>') store.write("config", '<[enabled]=true;[theme]="dark";>')

print(store.get("user"))

Output: <[name]="Viren";[age]=12;>

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FILE STORAGE

from ndca import file

db = file("data.ndca", autosave=True)

db.write("user.name", "Viren") db.write("user.age", 12)

print(db.get("user.name"))

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CORE DATA API

READ

• get(path, default=None)
• get_with_meta(path)
• exists(path)
• keys()
• keys_at(path)
• paths()

WRITE

• write(path, value)
• setdefault(path, value)
• update(path, dict_value)
• rename(path, new_name)

DELETE

• delete(path)
• clear_path(path)
• pop(path)
• wipe()

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LIST UTILITIES

• append(path, value)
• remove_from_list(path, value)
• paginate(path, page, per_page)

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DATA UTILITIES

• merge(other_dict)
• incr(path, amount)
• toggle(path)
• count_rows(path)

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IMPORT AND EXPORT

• export(filename)
• import_file(filename)
• dump()
• dumps()
• load(filename)
• loads(text)
• save(filename)

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HASH SAFE WRITES

• hash_write(filename)
  Writes the NDCA file with a verification hash to ensure integrity.

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TABLE UTILITIES

CREATE TABLE

• table_create(path, columns)

INSERT ROW

• table_insert(path, row)

GET ROW

• table_get_row(path, index)

FIND ROWS

• table_find(path, criteria)

UPDATE ROW

• table_update_row(path, index, updates)

DELETE ROW

• table_delete_row(path, index)

TABLE INDEX

• table_index(path, key, unique=False)

SORT TABLE

• table_sort(path, key, reverse=False)

CSV EXPORT

• table_to_csv(path, filename, include_header=True)

CSV IMPORT

• table_from_csv(path, filename, columns=None)

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PAGINATION

page = store.paginate("items", page=1, per_page=10)

print(page["items"]) print(page["total"])

Pagination returns: page
per_page
total
items

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VERSION

NDCA Version 5.0.0

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EXAMPLE DATA

<[user]=<[name]="Viren";[age]=12;>;[settings]=<[theme]="dark";[notifications]=true;>;[skills]=("Python";"Bash";"NDCA");>

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LICENSE

See the LICENSE file included in this project.