mirror of
https://github.com/NicolasBohn/NexQuant.git
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TPTBusiness
953fb2d278
New test infrastructure:
1. pytest + pytest-cov installed
- requirements.txt updated
- pytest.ini configured
- .coveragerc for coverage
2. Test suite created (97 tests):
- test_backtest_engine.py (32 tests)
* BacktestMetrics: IC, Sharpe, Drawdown, Win Rate
* FactorBacktester: run_backtest, JSON export
* Edge cases: NaN, empty, insufficient data
- test_results_db.py (33 tests)
* ResultsDatabase: CRUD operations
* Queries: get_top_factors, get_aggregate_stats
* Database cleanup
- test_risk_management.py (32 tests)
* CorrelationAnalyzer: Matrix, uncorrelated factors
* PortfolioOptimizer: Mean-Variance, Risk Parity
* AdvancedRiskManager: Limit checks
3. Fixtures (conftest.py):
- 22 reusable test fixtures
- Mock data for all scenarios
- Sample factors, returns, equity curves
4. Coverage: 98.77% (target: >80%)
- BacktestMetrics: 100%
- FactorBacktester: 100%
- ResultsDatabase: 95.92%
- CorrelationAnalyzer: 100%
- PortfolioOptimizer: 100%
- AdvancedRiskManager: 100%
5. Documentation:
- test/backtesting/README.md
- How to run tests
- Generate coverage reports
Run tests:
pytest test/backtesting/ -v
Coverage report:
pytest test/backtesting/ --cov=rdagent/components/backtesting --cov-report=html
90 lines
1.3 KiB
Plaintext
90 lines
1.3 KiB
Plaintext
# Requirements for runtime.
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pydantic-settings
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python-Levenshtein
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scikit-learn
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filelock
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loguru
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fire
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fuzzywuzzy
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openai
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litellm>=1.73 # to support `from litellm import get_valid_models`
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azure.identity
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pyarrow
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rich
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tqdm
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typer
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numpy # we use numpy as default data format. So we have to install numpy
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pandas # we use pandas as default data format. So we have to install pandas
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pandarallel # parallelize pandas
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matplotlib
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langchain
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langchain-community
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tiktoken
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pymupdf # Extract shotsreens from pdf
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# PDF related
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pypdf
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azure-ai-formrecognizer
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# factor implementations
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tables
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# CI Fix Tool
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tree-sitter-python
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tree-sitter
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python-dotenv
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# infrastructure related.
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docker
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# crawler related
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webdriver-manager
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# demo related
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streamlit>=1.47 # to support input_c.text_area(..., height="content", ...)
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plotly
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st-theme
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randomname
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flask
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flask-cors
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networkx
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# kaggle crawler
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selenium
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kaggle
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nbformat # also used for notebook conversion
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# tool
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setuptools-scm
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seaborn
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azure.ai.inference
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# data folder desc
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humanize
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genson
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# mlflow
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mlflow
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azureml-mlflow
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types-pytz
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# Agent
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pydantic-ai-slim[mcp,openai,prefect]
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nest-asyncio
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# visualize SFT train
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tensorboard # tensorboard --logdir git_ignore_folder/RD-Agent_workspace
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prefect
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# HuggingFace datasets
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datasets
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# DuckDuckGo search
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duckduckgo-search
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# Testing
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pytest
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pytest-cov |