Core Data Models

Relevant source files

The following files were used as context for generating this wiki page:

• src/flext_target_ldap/models.py
• src/flext_target_ldap/_models/sinks.py
• src/flext_target_ldap/settings.py
• src/flext_target_ldap/api.py
• src/flext_target_ldap/_models/__init__.py

The Core Data Models in flext-target-ldap provide a unified framework for representing, validating, and processing LDAP directory entries within a Singer-compatible ETL pipeline. These models bridge the gap between flat Singer source records and the hierarchical, attribute-heavy structure of LDAP directories.

The architecture follows the FLEXT ecosystem standards, utilizing nested domain classes for composition and rigorous validation. This ensures that data transformed for LDAP loading adheres to both structural requirements (like Distinguished Names) and business rules (like required object classes for specific entry types).

Sources: src/flext_target_ldap/models.py:15-28, src/flext_target_ldap/api.py:31-40

Unified LDAP Domain Models

The primary entry point for domain modeling is FlextTargetLdapModels, which consolidates LDAP target domain entities. It uses a nested class structure to organize different aspects of the LDAP ecosystem, such as entries, attribute mappings, and transformation rules.

TargetLdap Entry Model

The Entry model represents a complete LDAP object. It includes logic for calculating parent Distinguished Names (DNs) and Relative Distinguished Names (RDNs), as well as validating mandatory attributes based on object classes (e.g., sn and cn for person entries).

The diagram above illustrates the composition of the unified LDAP models.
Sources: src/flext_target_ldap/models.py:100-210

Field	Type	Description
distinguished_name	NonEmptyStr	The full LDAP DN (e.g., uid=jdoe,dc=example,dc=com).
object_classes	MutableSequence[str]	List of LDAP object classes; defaults to including top.
attributes	Mapping	Key-value pairs of LDAP attributes and their values.
entry_type	str	Categorization (user, group, ou, etc.).

Sources: src/flext_target_ldap/models.py:105-135

Sink Models and Stream Specialization

The project implements specialized "Sinks" that inherit from FlextTargetLdapBaseSink. These sinks encapsulate the logic for translating specific Singer streams into LDAP operations.

Sink Hierarchy

The sink hierarchy shows how specific entry types inherit common LDAP processing logic.
Sources: src/flext_target_ldap/_models/sinks.py:23-533, src/flext_target_ldap/api.py:65-85

Data Flow: Record to LDAP Entry

When a record is processed, the sink performs a series of transformations defined by the models:

1. DN Construction: The sink builds the Distinguished Name using settings like base_dn and user_rdn_attribute.
2. Attribute Mapping: Singer fields are mapped to LDAP attributes using the AttributeMapping rules.
3. Object Class Assignment: Standard classes (like inetOrgPerson for users) are merged with configured custom classes.
4. Persistence: The model determines whether to add a new entry or modify an existing one based on the update_existing_entries configuration.

Sources: src/flext_target_ldap/_models/sinks.py:326-440, src/flext_target_ldap/api.py:133-165

Configuration and Settings Models

The FlextTargetLdapSettings model handles the validation and normalization of target configurations. It includes a unique normalization step that flattens standard Singer JSON configuration into a structured connection object and operation parameters.

Key Configuration Options

Option	Type	Default	Description
base_dn	str	Required	The root DN for all operations.
create_missing_entries	bool	True	Whether to attempt an LDAP ADD if entry is missing.
update_existing_entries	bool	False	Whether to attempt an LDAP MODIFY if entry exists.
attribute_mapping	dict	{}	Map of Singer fields to LDAP attributes.
object_classes	list	['top']	Default object classes for new entries.

Sources: src/flext_target_ldap/settings.py:101-163

Processing Result Models

To track performance and errors across batches, the FlextTargetLdapProcessingResult model maintains mutable counters.

The diagram shows how the processing result tracks outcomes of LDAP operations.
Sources: src/flext_target_ldap/_models/sinks.py:67-75, src/flext_target_ldap/_models/sinks.py:270-324

Summary

The core data models in flext-target-ldap ensure that data integrity is maintained between ephemeral Singer streams and persistent LDAP directories. By centralizing validation in the Entry and AttributeMapping models and specializing processing logic in typed sinks (Users, Groups, OUs), the system provides a robust, extensible framework for directory synchronization.

Sources: src/flext_target_ldap/models.py:22-35, src/flext_target_ldap/api.py:31-45