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TPTBusiness
d12430427d
- MLTrainer class with feature matrix builder from top factors by IC - LightGBM training with time-series split (80/20) and early stopping - Feature importance analysis (gain-based) with ranking - Model persistence: model.txt + metadata.json + feature_importance.json + CSV - Feedback generation for factor generation loop - Model loading from disk - Full pipeline: load factors -> train -> save -> generate feedback - 46 unit tests covering all features - lightgbm and scipy added to requirements.txt
106 lines
1.7 KiB
Plaintext
106 lines
1.7 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
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# Parameter Optimization
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optuna>=3.5.0
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# News & Data (Polymarket, ForexFactory, CryptoPanic)
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beautifulsoup4>=4.12.0
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# ML Training Pipeline
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lightgbm>=3.3.0
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scipy>=1.9.0
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# RL Trading (optional - system works without these)
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# Install for full RL training: pip install stable-baselines3[extra] gymnasium
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# Without these, RL trading uses simple momentum fallback
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# stable-baselines3[extra]>=2.0.0
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# gymnasium>=0.29.0 |