Feature Comparison: rustest vs pytest¶

Quick answer: Most pytest code works with rustest. Change your imports, get massive speedups.

This page provides a complete feature-by-feature comparison so you can see exactly what's supported, what's planned, and what's intentionally excluded.

Feature Comparison Table¶

Legend: - ✅ Fully supported - 🚧 Planned or in progress - ⚠️ Partial support - ❌ Not planned

Philosophy¶

Rustest implements the 20% of pytest features that cover 80% of use cases, with a focus on raw speed and simplicity.

When to Use rustest¶

✅ Use rustest when:

• You want faster test execution (8.5× average speedup, up to 19×)
• You want predictable gains: ~3–4× on tiny suites, ~5–8× once you reach a few hundred tests, and 11–19× on thousand-test workloads
• You use standard pytest features (fixtures, parametrization, marks)
• You want a simple, focused testing tool
• You value fast CI/CD feedback loops
• You're writing new tests and want modern tooling
• You test markdown documentation

When to Use pytest¶

✅ Use pytest when:

• You need pytest plugins (pytest-django, pytest-cov, etc.) - see plugin migration guide
• You rely on advanced pytest features (hooks, custom collectors)
• You have complex existing pytest infrastructure
• You need detailed assertion introspection
• You require specific output formats (JUnit XML, HTML reports)

Migration from pytest¶

Easy Migration¶

Most pytest test suites can switch to rustest with minimal changes:

# pytest code
from pytest import fixture, parametrize, mark, approx, raises

@fixture
def database():
    return setup_database()

@parametrize("value,expected", [(1, 2), (2, 4)])
def test_double(value, expected):
    assert value * 2 == expected

# rustest code - identical!
from rustest import fixture, parametrize, mark, approx, raises

@fixture
def database():
    return setup_database()

@parametrize("value,expected", [(1, 2), (2, 4)])
def test_double(value, expected):
    assert value * 2 == expected

What Stays the Same¶

• Test discovery patterns
• Fixture syntax and scopes
• Parametrization syntax
• Mark syntax
• Exception testing with raises()
• Numeric comparison with approx()
• Test class structure

What Changes¶

Import Statements¶

# pytest
import pytest
from pytest import fixture, parametrize

# rustest
import rustest
from rustest import fixture, parametrize

Running Tests¶

# pytest
pytest tests/

# rustest
rustest tests/

Configuration¶

pytest uses pytest.ini or pyproject.toml:

# pytest config
[tool.pytest.ini_options]
testpaths = ["tests"]

rustest uses command-line arguments (no config file yet):

rustest tests/

Compatibility Layer¶

For gradual migration, you can use both in the same project:

# tests/conftest.py
try:
    from rustest import fixture, parametrize, mark
except ImportError:
    from pytest import fixture, mark
    from pytest import param as parametrize

Feature Deep Dive¶

Fixtures¶

Both support the same fixture features:

# Works identically in both
from rustest import fixture  # or from pytest import fixture

@fixture(scope="session")
def database():
    db = setup()
    yield db
    db.cleanup()

Rustest advantage: Faster fixture resolution due to Rust-based dependency graph.

Parametrization¶

Both use the same syntax:

# Works identically in both
from rustest import parametrize  # or from pytest import parametrize

@parametrize("x,y", [(1, 2), (3, 4)], ids=["first", "second"])
def test_values(x, y):
    assert x < y

Rustest advantage: Much faster with large parameter sets (see Performance).

Marks¶

Both support custom marks:

# Works identically in both
from rustest import mark  # or from pytest import mark

@mark.slow
@mark.integration
def test_expensive():
    pass

pytest advantage: Can filter by marks with -m "slow". Rustest has this planned but not yet implemented.

Assertion Helpers¶

Both provide approx() and raises():

# Works identically in both
from rustest import approx, raises  # or from pytest import approx, raises

def test_comparison():
    assert 0.1 + 0.2 == approx(0.3)

    with raises(ValueError, match="invalid"):
        raise ValueError("invalid input")

Test Classes¶

Both support the same class structure:

# Works identically in both
class TestMath:
    @fixture(scope="class")
    def calculator(self):
        return Calculator()

    def test_add(self, calculator):
        assert calculator.add(2, 3) == 5

Performance Comparison¶

See the Performance page for detailed benchmarks.

Summary: - ~2.1x faster on typical test suites - ~24x faster on heavily parametrized tests - Scales better with larger test suites

Ecosystem¶

pytest Ecosystem¶

• Huge plugin ecosystem: hundreds of plugins
• Wide adoption: industry standard
• Extensive documentation: many tutorials and guides
• IDE integration: built into most Python IDEs

rustest Ecosystem¶

• No plugins: focused on core functionality
• Growing adoption: new but actively developed
• Modern documentation: clean, comprehensive docs
• Standard IDE support: works with any Python IDE

Future Roadmap¶

Planned rustest features to increase pytest compatibility:

• 🚧 Mark-based filtering (-m)
• 🚧 JUnit XML output
• 🚧 Parallel test execution
• 🚧 HTML reports

Features not planned:

• ❌ Plugin system (by design)
• ❌ Hooks (by design)
• ❌ Custom collectors (by design)

Conclusion¶

Choose rustest if you want: - Fast test execution - Simple, focused tooling - Modern development experience - Standard pytest patterns

Stick with pytest if you need: - Plugin ecosystem - Advanced customization - Specific output formats - Maximum compatibility

Both are excellent tools! Rustest aims to complement pytest by providing a faster alternative for common use cases.

See Also¶

• Pytest Plugins - Migration guide for popular pytest plugins
• Performance - Detailed performance analysis
• Getting Started - Try rustest
• Development - Contribute to rustest