ndca 4.0.0

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

NDCA

Nested Data Collection API
Version 4.0.0

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INFO

NDCA (Nested Data Collection API) is a fast, secure, and production-ready Python library for storing, reading, and manipulating nested structured data using a compact human-readable format.

NDCA is designed for reliability, atomic persistence, safe in-memory operations, and a simple but powerful API suitable for scripts, services, tools, and applications.

Version 4.0.0 improves the stability of the format, adds more utilities, better serialization, table features, CSV support, pagination helpers, hashing utilities, and stronger internal safety.

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FEATURES

Human readable data format
Nested object support
List support
Safe deep copy reads
Atomic file writing
Autosave file instances
Path based nested operations
Dictionary merging
List append and removal helpers
Increment and toggle helpers
Hash verified writes
Import and export helpers
CSV import and export
Table style data utilities
Pagination helpers
Production ready stability

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INSTALLATION

Install with pip.

pip install ndca

Or include the NDCA module directly in your project.

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NDCA FORMAT

NDCA uses a compact structured syntax for storing nested data.

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OBJECT FORMAT

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

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LIST FORMAT

(value1;value2;value3;)

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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()

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WRITE

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

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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

NDCA provides lightweight table features for structured row based data.

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CREATE TABLE

table_create(path, columns)

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INSERT ROW

table_insert(path, row)

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GET ROW

table_get_row(path, index)

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FIND ROWS

table_find(path, criteria)

Criteria can be a dictionary or callable.

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UPDATE ROW

table_update_row(path, index, updates)

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DELETE ROW

table_delete_row(path, index)

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TABLE INDEX

table_index(path, key, unique=False)

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SORT TABLE

table_sort(path, key, reverse=False)

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CSV EXPORT

table_to_csv(path, filename, include_header=True)

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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 4.0.0

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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 included in this project.