Working with Inline Data tables in Python

Inline data handling for tables embedded directly in resource definitions.

Installation

pip install fairspec

Getting Started

The Inline plugin provides:

• load_inline_table - Load tables from inline data
• InlinePlugin - Plugin for framework integration

For example:

from fairspec import load_inline_table, Resource

table = load_inline_table(Resource(data=[
    {"id": 1, "name": "Alice"},
    {"id": 2, "name": "Bob"},
]))

Basic Usage

Object Format Data

The most common format is an array of objects:

from fairspec import load_inline_table, Resource

table = load_inline_table(Resource(data=[
    {"id": 1, "name": "english", "native": "English"},
    {"id": 2, "name": "chinese", "native": "\u4e2d\u6587"},
    {"id": 3, "name": "spanish", "native": "Espa\u00f1ol"},
]))

Array Format Data

You can also use array-of-arrays format with the first row as headers:

from fairspec import load_inline_table, Resource

table = load_inline_table(Resource(data=[
    ["id", "name", "native"],
    [1, "english", "English"],
    [2, "chinese", "\u4e2d\u6587"],
    [3, "spanish", "Espa\u00f1ol"],
]))

Advanced Features

With Table Schema

Provide a Table Schema for type validation and conversion:

from fairspec import load_inline_table, Resource
from fairspec_metadata import TableSchema, IntegerColumnProperty, StringColumnProperty, BooleanColumnProperty

table = load_inline_table(Resource(
    data=[
        {"id": 1, "name": "english", "active": True},
        {"id": 2, "name": "chinese", "active": False},
    ],
    tableSchema=TableSchema(properties={
        "id": IntegerColumnProperty(),
        "name": StringColumnProperty(),
        "active": BooleanColumnProperty(),
    }),
))

Mixed with File Data

Inline data can be used alongside file-based resources in datasets:

from fairspec import load_inline_table, load_csv_table, Resource

# Load inline reference data
languages = load_inline_table(Resource(
    name="languages",
    data=[
        {"id": 1, "name": "english"},
        {"id": 2, "name": "chinese"},
    ],
))

# Load main data from file
users = load_csv_table(Resource(name="users", data="users.csv"))

Resource Metadata

You can include metadata with inline data resources:

from fairspec import load_inline_table, Resource
from fairspec_metadata import TableSchema, StringColumnProperty

table = load_inline_table(Resource(
    name="countries",
    title="Country Reference Data",
    description="ISO country codes and names",
    data=[
        {"code": "US", "name": "United States"},
        {"code": "CN", "name": "China"},
        {"code": "ES", "name": "Spain"},
    ],
    tableSchema=TableSchema(properties={
        "code": StringColumnProperty(),
        "name": StringColumnProperty(),
    }),
))