# third-part dependency:
pandas==1.0.3
numpy==1.18.4
# tensorflow >>
tensorflow-datasets==2.0.0 # 可能依赖$pip install siphash
# tensorflow_hub==0.7.0 # 可以不用该库，transformers代替
# sentencepiece==0.1.85 # 可以不用该库，for bert tokenization.py
# pytorch >>
torch==1.5.0
torchvision>=0.6.0  # see https://github.com/pytorch/vision/releases
# ray-project >>
# e.g. pip install -U ray==0.8.4 -i https://pypi.tuna.tsinghua.edu.cn/simple
ray>=0.8.5
networkx>=2.4
cloudpickle>=1.4.1 # 从rayV0.8.4开始，在linux操作系统中使用streaming需安装cloudpickle
msgpack==1.0.0 # 从rayV0.8.4开始，在linux操作系统中使用streaming需安装msgpack解决linux下ray0.8.4程序启动报错：No module named 'msgpack'
# redis cluster: redis和redis-py-cluster冲突，可能需要先uninstall已安装高版本的redis, 然后再安装redis-py-cluster, 最后再$pip install -U redis==3.0.1
redis==3.0.1
redis-py-cluster==2.0.0
# self-research framework:
py-common-util>=0.1.7
# ###########################
# 机器学习算法库
# 1.numba (待定）
# 2.ta-lib, finta(https://github.com/peerchemist/finta)
deap==1.3.1 # 遗传算法
scikit_learn==0.22.2 # tpot库用到了scikit_learn
tpot==0.11.1 # 用遗传算法优化机器学习效果的自动机器学习库
#xgboost==0.90 # mac os上用$brew install xgboost命令手工安装
pygraphviz==1.5 # 生产环境不用安装，在mac osx上安装pygraphviz展示deap生成的个体图: pip3 install --install-option="--include-path=/usr/local/include/" --install-option="--library-path=/usr/local/lib/" pygraphviz
# ###########################
# for reinforcement learning(baselines可以参考：https://github.com/hill-a/stable-baselines)
# 手工安装tf2分支版本的gym baselines：$ mkdir -p ~/tmp/gym_baselines; touch ~/tmp/gym_baselines/install.txt; cd ~/tmp/gym_baselines; git clone -b tf2 https://github.com/openai/baselines.git; cd baselines/; python setup.py install --record ~/tmp/gym_baselines/install.txt
# 手工卸载gym baselines：sudo cat ~/tmp/gym_baselines/install.txt | xargs rm -rf
# gym==0.15.4
# opencv-python=4.1.1.26 #暂不安装
# for cython and build
cython==3.0a4 # https://cython.readthedocs.io/en/latest/
wheel==0.34.2
setuptools==46.1.3
# pybind11
pybind11==2.5.0
# 部署安装包到pypi
twine==3.1.1
# bert of huggingface
transformers==2.8.0 #可以暂不安装，等需要时候再安装
# robo-advisor
# cvxopt==1.2.4 #暂不安装
# ############################
# tushare==1.2.54 #生产环境不用安装该库
# beautifulsoup4==4.8.2 #抓取并解析html，生产环境不用安装该库

