0.3.0

taxpres.py - Taxonomy Presentation Processing Module

This module provides functionality for processing XBRL taxonomy presentation linkbases and
extracting structured concept information. It helps organize concepts into statements and
validates segment/dimension information.

Key Classes:

TaxonomyPresentation
Main class that processes taxonomy presentation networks and organizes concepts into
primary statements and disclosures.

Key Functions:

get_presentation_networks(taxonomy)
Extracts presentation networks from a taxonomy by examining linkbases and base sets.

get_network_details(tax, network, reporter)
Processes a presentation network to extract concept details and relationships.

get_child_concepts(reporter, network, concept, taxonomy, visited=None)
Recursively extracts child concepts from a presentation network hierarchy.

process_children(reporter, network, parent, concepts, grandparent_qname)
Helper function to process child concepts in a presentation network.

ins_facts(xid, tax)
Extracts facts from an XBRL instance document and organizes them based on the
presentation structure.

Example Usage:

Create a TaxonomyPresentation instance

t_pres = TaxonomyPresentation(taxonomy, reporter)

Get facts from an instance document

fact_df = ins_facts(xbrl_instance, taxonomy)

Access statement information

print(t_pres.statement_concepts) # Concepts in primary statements
print(t_pres.disclosure_concepts) # Concepts in disclosures
print(t_pres.statement_dimensions) # Allowed dimensions per statement

Classes:

TaxonomyPresentation:
Attributes:
tax: The taxonomy object being processed
reporter: TaxonomyReporter instance for label handling
concept_df: DataFrame containing all concepts
allowed_segments_by_statement: Dict mapping statements to allowed segments
concept_dict: Dict containing all concepts
statement_concepts: Dict containing primary statement concepts
disclosure_concepts: Dict containing disclosure concepts
statement_dimensions: Dict containing allowed dimensions per statement
so_name: Name of Statement of Operations
fp_name: Name of Financial Position statement
cf_name: Name of Cash Flow statement

Methods:
    populate_concept_df(): Creates DataFrame from concept dictionaries
    _is_primary_statement(role_name): Determines if a role represents a primary statement
    _process_network_dimensions(network, statement_name): Processes dimensions in a network
    _validate_segment(segment_data, statement_name): Validates segment data against statement
    _process_taxonomy(): Main method to process taxonomy and build concept dictionaries
    is_valid_concept(concept_qname): Checks if a concept exists in presentation
    get_concept_info(concept_qname): Gets detailed information about a concept
    is_valid_segment(concept_qname, segment_data, statement_name): Validates segment data

Notes:

• The module assumes a standard XBRL taxonomy structure with presentation linkbases
• Primary statements are identified using keyword matching in role names
• Segment validation supports both axis/member and dimension/member terminology
• Period types and other attributes are obtained from the concept definitions