Error Handling & Diagnostics
Relevant source files
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Error handling and diagnostics in flext-target-ldif are designed to ensure data integrity during the conversion of Singer records to LDAP Data Interchange Format (LDIF). The system employs a combination of strict configuration validation, functional result wrappers for operational safety, and specific exception classes to manage failures in file I/O, DN generation, and data transformation.
The architecture leverages the flext-core result pattern, where operations return a Result object containing success status, values, or error details. This prevents unhandled exceptions from crashing the Singer target while providing granular logging and diagnostics for troubleshooting malformed records or environment issues.
Sources: src/flext_target_ldif/writer.py:28-32, src/flext_target_ldif/models.py:126-150
Exception Hierarchy & Safe Exceptions
The project defines specialized exception types to categorize failures, particularly within the writer module. A tuple of "safe exceptions" is maintained to identify errors that should be caught and converted into diagnostic results rather than causing immediate process termination.
| Exception Class | Description | Source |
|---|---|---|
FlextTargetLdifWriterError | Base exception for all LDIF writer-specific failures. | src/flext_target_ldif/errors.py |
_WRITER_SAFE_EXCEPTIONS | A tuple containing Singer safe exceptions and FlextTargetLdifWriterError. | src/flext_target_ldif/writer.py:28-32 |
Operational Safety Flow
Operational safety is achieved by wrapping risky calls (like file opening or record writing) in try-except blocks that reference these safe exceptions.
Validation & Business Rules
Diagnostics begin with rigorous validation of input configurations and data entries. The FlextTargetLdif target class performs pre-flight checks on settings, while the models define business rules for LDIF entities.
Configuration Validation
The target validates critical settings such as output_path and dn_template. Missing or empty values trigger immediate ValueError diagnostics.
Sources: src/flext_target_ldif/target.py:72-105, tests/unit/test_target.py:82-95
Entry Business Rules
The LdifEntry and LdifFile models include validate_business_rules methods to verify structural integrity.
| Entity | Validation Rule | Diagnostic Message |
|---|---|---|
LdifEntry | DN must contain = and , | "DN must contain attribute=value pairs separated by commas" |
LdifEntry | Must have object classes | "Entry must have at least one object class" |
LdifEntry | Must have attributes | "Entry must have at least one attribute" |
LdifFile | Entry count match | "Entry count mismatch: {expected} vs {actual}" |
| Sources: src/flext_target_ldif/models.py:126-150, src/flext_target_ldif/models.py:202-218 |
Writer Diagnostics
The FlextTargetLdifWriter manages the state of LDIF generation and provides diagnostics for three primary failure points: File I/O, DN generation, and record conversion.
DN Generation Failures
If a record lacks the fields required by the dn_template, the writer raises a FlextTargetLdifWriterError with specific field information.
Sources: src/flext_target_ldif/writer.py:149-154, tests/unit/test_writer.py:326-338
Record Conversion Logic
During conversion, the writer identifies and logs invalid records without halting the entire batch.
Utility-Based Diagnostics
The FlextTargetLdifUtilities class provides static methods for validating LDIF formats and building DNs, returning Result objects for consistent diagnostic handling.
validate_ldif_entry: Checks if an entry starts with a valid "dn:" prefix and contains data.build_ldif_dn: Validates that all placeholders in a template are resolved and the resulting string matches LDAP DN regex patterns.split: UsesPATTERN_LDAP_DN_REto validate DN syntax.
Sources: src/flext_target_ldif/utilities.py:87-106, src/flext_target_ldif/utilities.py:118-144
Data Transformer Diagnostics
The RecordTransformer normalizes values for LDAP. Diagnostic logic here includes checking for valid email formats and phone number characters, returning empty strings or standardized formats instead of throwing errors to maintain stream continuity.
Sources: src/flext_target_ldif/utilities.py:213-235
Conclusion
Error handling and diagnostics in flext-target-ldif prioritize resilience and clarity. By utilizing a result-oriented pattern and centralized validation rules in FlextTargetLdifModels, the system ensures that developers receive precise diagnostic information when records fail to meet LDIF standards, while maintaining the overall stability of the Singer data pipeline.