simple-error-log 0.8.0

A python package containing classes for logging errors

Simple Error Log

A lightweight Python library for structured error logging with location context. Collect, organize, and serialize errors with severity levels and rich location metadata—perfect for validation systems, data pipelines, and document processing.

Features

• Zero dependencies - Pure Python standard library
• Multiple severity levels - ERROR, WARNING, INFO, DEBUG
• Location tracking - Grid coordinates, document sections, class methods, or custom locations
• Exception capture - Full traceback and call stack preservation
• Structured extras - Attach machine-readable payloads alongside the human message
• Flexible output - Dictionary (JSON-serializable) or formatted strings
• Error aggregation - Merge, filter, and query error collections

Installation

pip install simple_error_log

Requires Python 3.10+

Quick Start

from simple_error_log import Errors, DocumentSectionLocation, GridLocation

# Create an error collection
errors = Errors()

# Log errors with locations
location = DocumentSectionLocation("2.1", "Data Validation")
errors.error("Missing required field: email", location)

# Different severity levels
errors.warning("Deprecated format detected")
errors.info("Processing started")
errors.debug("Parsed 150 records")

# Log exceptions with full context
try:
    process_data()
except Exception as e:
    errors.exception("Processing failed", e, location)

# Export errors
print(errors.dump())  # Formatted string output
data = errors.to_dict()  # JSON-serializable dict

Core Classes

Errors

The main collection class for managing multiple errors.

from simple_error_log import Errors

errors = Errors()

# Add errors at different levels
errors.error("Critical failure")
errors.warning("Non-critical issue")
errors.info("Informational message")
errors.debug("Debug details")

# Log exceptions with traceback
try:
    risky_operation()
except Exception as e:
    errors.exception("Operation failed", e)

# Query the collection
errors.count()        # Total number of logged items
errors.error_count()  # Only ERROR-level items

# Export with level filtering
errors.to_dict(Errors.ERROR)    # Only errors
errors.to_dict(Errors.WARNING)  # Errors and warnings
errors.dump(Errors.DEBUG)       # Everything, formatted

# Merge collections
combined = errors1.merge(errors2)  # Sorted by timestamp

# Clear all errors
errors.clear()

Error

Represents a single error with metadata.

from simple_error_log import Error, GridLocation

error = Error(
    message="Invalid value at position",
    location=GridLocation(row=5, column=3),
    level=Error.WARNING,
    error_type="validation"
)

print(error)           # Formatted string
error.to_dict()        # Dictionary representation
error.timestamp        # When it was created

Severity Levels:

• Error.ERROR (40) - Critical errors
• Error.WARNING (30) - Warnings
• Error.DEBUG (20) - Debug information
• Error.INFO (10) - Informational messages

Structured Extras

Every logging method accepts an optional extra dict for machine-readable context that downstream consumers shouldn't have to parse out of the message string. It pairs naturally with error_type as a filter tag.

from simple_error_log import Errors, GridLocation

errors = Errors()

errors.warning(
    "Normalised phase label",
    location=GridLocation(row=4, column=2),
    error_type="normalisation",
    extra={"source": "Phase III", "normalised": "Phase 3"},
)

# Available on every level plus exception()
errors.error("Invalid code", error_type="lookup", extra={"code": "X99"})
errors.info("Batch complete", extra={"records": 1500, "elapsed_ms": 842})

The payload round-trips through to_dict() under the "extra" key.

Location Classes

GridLocation

For grid or table-based positions:

from simple_error_log import GridLocation

loc = GridLocation(row=10, column=5)
print(loc)        # "[10, 5]"
loc.to_dict()     # {"row": 10, "column": 5}

DocumentSectionLocation

For document sections:

from simple_error_log import DocumentSectionLocation

loc = DocumentSectionLocation("3.2", "Methodology")
print(loc)        # "[3.2 Methodology]"
loc.to_dict()     # {"section_number": "3.2", "section_title": "Methodology"}

KlassMethodLocation

For class methods:

from simple_error_log import KlassMethodLocation

loc = KlassMethodLocation("DataParser", "validate")
print(loc)        # "DataParser.validate"
loc.to_dict()     # {"class_name": "DataParser", "method_name": "validate"}

Custom Locations

Create your own by subclassing ErrorLocation:

from simple_error_log import ErrorLocation

class FileLocation(ErrorLocation):
    def __init__(self, filename: str, line: int):
        self.filename = filename
        self.line = line

    def to_dict(self) -> dict:
        return {"filename": self.filename, "line": self.line}

    def __str__(self) -> str:
        return f"{self.filename}:{self.line}"

Example: Data Validation Pipeline

from simple_error_log import Errors, GridLocation

def validate_spreadsheet(data: list[list]) -> Errors:
    errors = Errors()

    for row_idx, row in enumerate(data):
        for col_idx, cell in enumerate(row):
            location = GridLocation(row_idx, col_idx)

            if cell is None:
                errors.error("Empty cell not allowed", location)
            elif isinstance(cell, str) and len(cell) > 255:
                errors.warning("Cell content exceeds recommended length", location)

    return errors

# Usage
errors = validate_spreadsheet(my_data)

if errors.error_count() > 0:
    print("Validation failed:")
    print(errors.dump(Errors.ERROR))
else:
    print(f"Validation passed with {errors.count()} warnings")

Output Formats

dump() - Formatted String

error: Missing required field
  location: [2.1 Data Validation]
  timestamp: 2024-01-15 10:30:45

warning: Deprecated format detected
  timestamp: 2024-01-15 10:30:46

to_dict() - JSON-Serializable

[
    {
        "message": "Missing required field",
        "level": "error",
        "error_type": "",
        "location": {"section_number": "2.1", "section_title": "Data Validation"},
        "timestamp": "2024-01-15T10:30:45"
    }
]

Development

Running Tests

pip install pytest pytest-cov
pytest

Building the Package

pip install build twine
python -m build
twine upload dist/*

License

MIT