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Project description
python_client
Version: 8.0.0
Table of Contents
syrtis-python-client
Version: 0.0.22
Table of Contents
Status & Compatibility
Maturity: Production-ready
Python Support: >=3.10
OS Support: Linux, macOS, Windows
Status: Actively maintained
Tests
This project uses pytest for testing and pytest-cov for code coverage analysis.
Installation
First, install the required testing dependencies:
.venv/bin/python -m pip install pytest pytest-cov
Basic Usage
Run all tests with coverage:
.venv/bin/python -m pytest --cov --cov-report=html
Common Commands
# Run tests with coverage for a specific module
.venv/bin/python -m pytest --cov=your_module
# Show which lines are not covered
.venv/bin/python -m pytest --cov=your_module --cov-report=term-missing
# Generate an HTML coverage report
.venv/bin/python -m pytest --cov=your_module --cov-report=html
# Combine terminal and HTML reports
.venv/bin/python -m pytest --cov=your_module --cov-report=term-missing --cov-report=html
# Run specific test file with coverage
.venv/bin/python -m pytest tests/test_file.py --cov=your_module --cov-report=term-missing
Viewing HTML Reports
After generating an HTML report, open htmlcov/index.html in your browser to view detailed line-by-line coverage information.
Coverage Threshold
To enforce a minimum coverage percentage:
.venv/bin/python -m pytest --cov=your_module --cov-fail-under=80
This will cause the test suite to fail if coverage drops below 80%.
Known Limitations & Roadmap
Current limitations and planned features are tracked in the GitHub issues.
See the project roadmap for upcoming features and improvements.
Useful Links
- Homepage: https://github.com/wexample/python-python-client
- Documentation: docs.wexample.com
- Issue Tracker: https://github.com/wexample/python-python-client/issues
- Discussions: https://github.com/wexample/python-python-client/discussions
- PyPI: pypi.org/project/syrtis-python-client
Tests
This project uses pytest for testing and pytest-cov for code coverage analysis.
Installation
First, install the required testing dependencies:
.venv/bin/python -m pip install pytest pytest-cov
Basic Usage
Run all tests with coverage:
.venv/bin/python -m pytest --cov --cov-report=html
Common Commands
# Run tests with coverage for a specific module
.venv/bin/python -m pytest --cov=your_module
# Show which lines are not covered
.venv/bin/python -m pytest --cov=your_module --cov-report=term-missing
# Generate an HTML coverage report
.venv/bin/python -m pytest --cov=your_module --cov-report=html
# Combine terminal and HTML reports
.venv/bin/python -m pytest --cov=your_module --cov-report=term-missing --cov-report=html
# Run specific test file with coverage
.venv/bin/python -m pytest tests/test_file.py --cov=your_module --cov-report=term-missing
Viewing HTML Reports
After generating an HTML report, open htmlcov/index.html in your browser to view detailed line-by-line coverage information.
Coverage Threshold
To enforce a minimum coverage percentage:
.venv/bin/python -m pytest --cov=your_module --cov-fail-under=80
This will cause the test suite to fail if coverage drops below 80%.
Known Limitations & Roadmap
Current limitations and planned features are tracked in the GitHub issues.
See the project roadmap for upcoming features and improvements.
Status & Compatibility
Maturity: Production-ready
Python Support: >=3.10
OS Support: Linux, macOS, Windows
Status: Actively maintained
Useful Links
- Homepage: https://github.com/wexample/python-python-client
- Documentation: docs.wexample.com
- Issue Tracker: https://github.com/wexample/python-python-client/issues
- Discussions: https://github.com/wexample/python-python-client/discussions
- PyPI: pypi.org/project/python_client
About us
Syrtis AI helps organizations turn artificial intelligence from an idea into reliable, measurable systems. We are a team of engineers and practitioners focused on implementing AI services inside real businesses — from strategy and architecture to deployment, integration, and long-term operations. Our goal is simple: deliver AI that works in production, fits your constraints, and earns its keep.
We build practical solutions that connect to existing tools, data, and processes, with an emphasis on security, performance, and governance. Whether it’s automating workflows, enhancing decision-making, or creating new product capabilities, Syrtis AI designs implementations that are maintainable, scalable, and aligned with business outcomes — not demos.
Syrtis AI promotes a culture of rigor and responsibility. Every delivery reflects a commitment to clear engineering, transparent communication, and trustworthy AI practices, so teams can adopt, operate, and evolve their AI services with confidence.
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