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Getting Started with xbrl-forge

xbrl-forge is a Python package designed to streamline the creation of XBRL (eXtensible Business Reporting Language) files. This guide will walk you through its primary functions and how to use them effectively.

Table of Contents

  1. Installation
  2. Key Functions
  3. Example Workflow
  4. Conclusion

Installation

Pyhton 3 is needed.

To use xbrl-forge, install it via pip:

pip install xbrl-forge

Key Functions

validate_input_data

Description

This function ensures that the input data is formatted correctly and adheres to the necessary structure for creating XBRL files.

The input data schema is available with descriptions of every key and value here.

Parameters

  • data (dict): The input data to be validated.

Returns

The function will not return anything. It will throw an error if the data is not correct according to the schemas.

Usage

from xbrl_forge import validate_input_data

validate_input_data(data)

load_input_data

Description

This function loads and preprocesses input data, preparing it for XBRL file generation.

Parameters

  • data (dict): The raw input data.

Returns

  • InputData: A python object resembing the necessary structure and functions.

Usage

from xbrl_forge import load_input_data

data = load_input_data(data)

create_xbrl

Description

Generates an XBRL file based on the validated input data.

Parameters

  • input_data_list (List of InputData Objects): The input data to be transformed into an XBRL file.
  • styles (str): Optional CSS information stored in a string.

Returns

  • File (a custom File object): An object that containes the xbrl structures ready for saving. It can save and package the information via the object functions save_files(folder_path) and create_package(folder_path).

Usage

from xbrl_forge import create_xbrl

results = create_xbrl([loaded_data_a, loaded_data_b], style="body { padding: 5px; }")

Example Workflow

Here is a complete example that ties the key functions together:

from xbrl_forge import create_xbrl, validate_input_data, load_input_data

# lets say we have 2 data jsons from 2 different systems, data_a and data_b

# validate both data sets
validate_input_data(data_a)
validate_input_data(data_b)

# load data objects
loaded_data_a = load_input_data(data_a)
loaded_data_b = load_input_data(data_b)

# run generation
results = create_xbrl([loaded_data_a, loaded_data_b])

# save either the files
results.save_files("result_folder")
# or the package
results.create_package("result_folder")

Conclusion

The xbrl-forge package simplifies the process of working with XBRL files by providing tools to validate the input, preprocess, and generate XBRL documents. By following this guide, you can integrate these functions into your workflow and streamline your reporting processes.

For more details, check the official documentation or raise issues for support.