Settings Model & Validation

Relevant source files

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

• src/flext_tap_ldif/settings.py
• src/flext_tap_ldif/models.py
• src/flext_tap_ldif/_models/file_metadata.py
• src/flext_tap_ldif/_models/file_stream.py
• src/flext_tap_ldif/_models/record.py
• src/flext_tap_ldif/_models/entry.py
• pyproject.toml

The Settings Model & Validation system in flext-tap-ldif provides a robust, Pydantic-driven framework for managing runtime configuration and data integrity during LDIF file extraction. It ensures that environment variables and configuration files adhere to the expected schema before the Singer tap begins processing. The system relies on flext-core for its base settings logic and pydantic for strict type enforcement and validation.

This module encompasses not only the primary tap settings but also the internal data models used to represent LDIF entries, file metadata, and stream configurations. By centralizing validation in these models, the tap ensures that invalid data is caught early in the pipeline, maintaining high quality gates as defined in the project governance.

Sources: src/flext_tap_ldif/settings.py:15-18, src/flext_tap_ldif/models.py:20-25, README.md:38-40

Core Runtime Settings

The primary configuration interface is the FlextTapLdifSettings class. This class inherits from FlextSettingsBase and is responsible for loading settings with the FLEXT_TAP_LDIF_ environment variable prefix. It handles file paths, parsing behavior, and resource limits.

Configuration Parameters

Parameter	Type	Default	Description
file_path	str | None	None	Specific path to an LDIF file.
directory_path	str | None	None	Directory to scan for LDIF files.
file_pattern	str	*.ldif	Glob pattern for file discovery.
encoding	str	utf-8	Encoding used to read LDIF files.
strict_parsing	bool	True	Whether to fail on parsing errors.
max_file_size_mb	int	1024	Maximum allowed file size (min: 1).

Sources: src/flext_tap_ldif/settings.py:18-47

Path Normalization Logic

The settings model includes utility methods to convert raw string inputs into structured pathlib.Path objects, facilitating safer file operations.

    def normalized_file_path(self) -> Path | None:
        """Return `file_path` as `Path` when configured."""
        if self.file_path is None:
            return None
        return Path(self.file_path)

Sources: src/flext_tap_ldif/settings.py:49-53

Domain Model Architecture

The project uses a Multi-Resource Object (MRO) mixin pattern to compose its domain models. The FlextTapLdifModels class acts as a facade, aggregating models for entries, files, batches, and records.

Model Composition

The following diagram illustrates how the TapLdif domain namespace is assembled from various internal model mixins.

Data Validation Models

Validation is enforced through Pydantic EnforcedModel instances. These models utilize model_validator decorators to ensure consistency between different fields.

LDIF File Metadata Validation

The LdifFile model tracks the state and validity of a specific file. It ensures that file sizes are non-negative and paths are present.

Entry Structure Validation

LdifEntry models represent individual records within the LDIF. They enforce that a Distinguished Name (DN) is always present and automatically synchronize objectClass attributes with the specific object_classes field.

• DN Constraint: The dn field cannot be empty.
• Attribute Sync: If object_classes are provided, they are automatically injected into the attributes mapping under the key objectClass if not already present.

Sources: src/flext_tap_ldif/_models/entry.py:22-108

Singer Stream Configuration

The LdifStream model defines how LDIF data is mapped to Singer streams. It includes configuration for replication methods and filtering.

Field	Description	Constraints
stream_name	The name of the Singer stream.	Required
tap_stream_id	Unique ID for the tap stream.	Required
replication_method	Strategy for data extraction.	Defaults to FULL_TABLE
batch_size	Number of records per batch.	From constants
filter_object_classes	List of classes to include.	Optional sequence

Sources: src/flext_tap_ldif/_models/file_stream.py:15-88

Validation Reporting

Validation results are captured in the LdifValidationResult model, which provides a summary of processing success and identifies critical errors.

Summary Logic

Models provide computed properties to generate JSON-compatible summaries for CLI output or logging. For example, LdifValidationResult calculates a success_rate and checks for "critical" severity in error lists.
Sources: src/flext_tap_ldif/_models/record.py:53-83