安装surprise推荐库遇到的坑

安装surprise推荐库遇到的坑

基于Windows系统的安装网络上有很多教程，不做说明，推荐安装anaconda3（不需要安装其他的环境什么的，简单易用），然后使用conda安装surprise库

基于Linux系统安装surprise库

可能会出现的问题：

首先说明尽量不要使用anaconda3来安装surprise，那会出现错误ImportError: cannot import name 'similarities'，具体原因可以参考surprise在Github上的issues，地址为https://github.com/NicolasHug/Surprise/issues/99

正确安装方法：

使用以下命令进行安装

# 基于python3的安装方法，Linux系统自带C++环境，所以不需要像Windows一样再安装C++环境

# 安装surprise需要先安装numpy库
pip3 install numpy

# 安装surprise库
pip3 install surprise

# 出现以下信息说明安装成功
Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (1.19.5)
Collecting surprise
  Downloading https://files.pythonhosted.org/packages/61/de/e5cba8682201fcf9c3719a6fdda95693468ed061945493dea2dd37c5618b/surprise-0.1-py2.py3-none-any.whl
Collecting scikit-surprise
  Downloading https://files.pythonhosted.org/packages/97/37/5d334adaf5ddd65da99fc65f6507e0e4599d092ba048f4302fe8775619e8/scikit-surprise-1.1.1.tar.gz (11.8MB)
     |████████████████████████████████| 11.8MB 5.4MB/s 
Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.7/dist-packages (from scikit-surprise->surprise) (1.0.1)
Requirement already satisfied: numpy>=1.11.2 in /usr/local/lib/python3.7/dist-packages (from scikit-surprise->surprise) (1.19.5)
Requirement already satisfied: scipy>=1.0.0 in /usr/local/lib/python3.7/dist-packages (from scikit-surprise->surprise) (1.4.1)
Requirement already satisfied: six>=1.10.0 in /usr/local/lib/python3.7/dist-packages (from scikit-surprise->surprise) (1.15.0)
Building wheels for collected packages: scikit-surprise
  Building wheel for scikit-surprise (setup.py) ... done
  Created wheel for scikit-surprise: filename=scikit_surprise-1.1.1-cp37-cp37m-linux_x86_64.whl size=1617536 sha256=96b70df989d0be57cebf2cc1402594bb551f915afc440e9178927d93ebfc9e0f
  Stored in directory: /root/.cache/pip/wheels/78/9c/3d/41b419c9d2aff5b6e2b4c0fc8d25c538202834058f9ed110d0
Successfully built scikit-surprise
Installing collected packages: scikit-surprise, surprise
Successfully installed scikit-surprise-1.1.1 surprise-0.1