anaconda虚拟环境安装cvxpy报错

通过终端激活虚拟环境，命令：pip install cvxpy
出错结果

C:\Users\CQUT>activate tensorflow(tensorflow) C:\Users\CQUT>pip install cvxpy
Collecting cvxpyDownloading http://pypi.doubanio.com/packages/7b/1a/48a8fad5e845c5b1a8bb3c718ff5b2f08a7cc61cf7111cd9fd6865ce386e/cvxpy-1.1.15-cp36-cp36m-win_amd64.whl (846kB)100% |████████████████████████████████| 849kB 6.8MB/s
Requirement already satisfied: numpy>=1.15 in d:\users\cqut\anaconda3\envs\tensorflow\lib\site-packages (from cvxpy)
Requirement already satisfied: osqp>=0.4.1 in d:\users\cqut\anaconda3\envs\tensorflow\lib\site-packages (from cvxpy)
Requirement already satisfied: scipy>=1.1.0 in d:\users\cqut\anaconda3\envs\tensorflow\lib\site-packages (from cvxpy)
Collecting ecos>=2 (from cvxpy)Downloading http://pypi.doubanio.com/packages/09/3c/3a3165d7f1bd0b7a06ba4df4962ac3f1f88079252eb77b6da8ebd8de07b9/ecos-2.0.7.post1-cp36-cp36m-win_amd64.whl (67kB)100% |████████████████████████████████| 71kB 23.6MB/s
Collecting scs>=1.1.6 (from cvxpy)Downloading http://pypi.doubanio.com/packages/5f/f3/7e11e9c0dc22c2bf2e8b4be1ade4fb8055dbe9ea29fd9bda455844b9d7ca/scs-2.1.4.tar.gz (6.6MB)100% |████████████████████████████████| 6.6MB 25.4MB/s
Requirement already satisfied: qdldl in d:\users\cqut\anaconda3\envs\tensorflow\lib\site-packages (from osqp>=0.4.1->cvxpy)
Building wheels for collected packages: scsRunning setup.py bdist_wheel for scs ... errorFailed building wheel for scsRunning setup.py clean for scs
Failed to build scs
Installing collected packages: ecos, scs, cvxpyRunning setup.py install for scs ... error
Exception:
Traceback (most recent call last):File "D:\Users\CQUT\anaconda3\envs\tensorflow\lib\site-packages\pip\compat\__init__.py", line 73, in console_to_strreturn s.decode(sys.__stdout__.encoding)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xc3 in position 4: invalid continuation byteDuring handling of the above exception, another exception occurred:Traceback (most recent call last):File "D:\Users\CQUT\anaconda3\envs\tensorflow\lib\site-packages\pip\basecommand.py", line 215, in mainstatus = self.run(options, args)File "D:\Users\CQUT\anaconda3\envs\tensorflow\lib\site-packages\pip\commands\install.py", line 342, in runprefix=options.prefix_path,File "D:\Users\CQUT\anaconda3\envs\tensorflow\lib\site-packages\pip\req\req_set.py", line 784, in install**kwargsFile "D:\Users\CQUT\anaconda3\envs\tensorflow\lib\site-packages\pip\req\req_install.py", line 878, in installspinner=spinner,File "D:\Users\CQUT\anaconda3\envs\tensorflow\lib\site-packages\pip\utils\__init__.py", line 676, in call_subprocessline = console_to_str(proc.stdout.readline())File "D:\Users\CQUT\anaconda3\envs\tensorflow\lib\site-packages\pip\compat\__init__.py", line 75, in console_to_strreturn s.decode('utf_8')
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xc3 in position 4: invalid continuation byte
You are using pip version 9.0.1, however version 21.3 is available.
You should consider upgrading via the 'python -m pip install --upgrade pip' command.

而且，命令conda install cvxpy 也报错出现在当前的channels中找不到这个包

解决办法：
用以下命令查找我们需要的包

anaconda search -t conda cvxpy

输出结果

Using Anaconda API: https://api.anaconda.org
Packages:Name                      |  Version | Package Types   | Platforms       | Builds------------------------- |   ------ | --------------- | --------------- | ----------GlaxoSmithKline/cvxpy     |   0.4.10 | conda           | linux-64        | py36_0, py35_0, py27_0Ramcha24/cvxpy            |    0.3.7 | conda           | linux-64, win-32, osx-64, linux-32, win-64 | py35_0, py27_0: A domain-specific language for modeling convex optimization problems in Python.ajones/cvxpy              |    0.4.3 | conda           | linux-64, win-64 | py35_0applebruce/cvxpy          |    0.2.7 | conda           | win-64          | np18py27_0auto/cvxpy                |      0.1 | conda           | linux-32        | py27_0: A domain-specific language for modeling convex optimization problems in Python.brittainhard/cvxpy        |   0.4.10 | conda           | linux-64        | py35he7afc33_0, py36h3a9921c_0, py27hfe8f223_0: A domain-specific language for modeling convex optimization problems in Python.conda-forge/cvxpy         |   1.1.15 | conda           | linux-ppc64le, osx-arm64, linux-64, linux-aarch64, osx-64, win-64 | py36h90709c0_0, py36h0a44026_1000, py36h0a44026_1001, py37hfc679d8_1, py37hfc679d8_0, py38h50d1736_1, py38h50d1736_0, py36h79c6626_0, py36h79c6626_1, py38h950e882_0, py38h950e882_1, py36ha15d459_1, py36hd724563_0, py36hd724563_1, py35hfc679d8_0, py37h1834ac0_0, py37h1834ac0_1, py38h578d9bd_0, py38h578d9bd_1, py37h6538335_2, py37hd9ded2f_0, py37hd9ded2f_1, py36h77c77ec_0, py39hf3d152e_0, py39hf3d152e_1, py37h89c1867_0, py37h89c1867_1, py38h24f1f5d_0, py38h6538335_2, py38h6538335_0, py36hbd05846_0, py38hc84c608_0, py37hb809cae_0, py36ha77a9a5_0, py36ha77a9a5_1, py37hb809cae_1, py27h0a44026_1000, py27h0a44026_1001, py39hcbf5309_0, py39hcbf5309_1, py37h6de7cb9_0, py37h6de7cb9_1, py37h570ac47_1, py37h570ac47_0, py36h5fab9bb_0, py36h5fab9bb_1, py37hdadc0f0_0, py36hd000896_0, py37h0a44026_1001, py37h0a44026_1000, py36he1b5a44_1, py36he1b5a44_0, py36hd000896_1, py39h6e9494a_0, py39h6e9494a_1, py37h6538335_1, py37h6538335_0, py37hf484d3e_1000, py37hf484d3e_1001, py37hb209c28_2, py38hc84c608_1, py37h4bcbb9b_0, py37h5186d4c_1, py37h5186d4c_0, py36h003fed8_1, py36h003fed8_0, py27h4a8c4bd_2, py36h831f99a_0, py36h831f99a_1, py36ha15d459_0, py37h4bcbb9b_1, py36hf484d3e_1, py36hf484d3e_0, py36hfc679d8_0, py36hfc679d8_1, py36h6538335_0, py36h6538335_1, py36h6538335_2, py36hf8241e8_0, py36h0130604_1, py36h0130604_0, py37h4a8c4bd_0, py36h4a8c4bd_0, py37h4a8c4bd_2, py38hb209c28_2, py38h2063c64_1, py38h2063c64_0, py36h6de7cb9_1, py36h6de7cb9_0, py38h8e8fcc4_0, py38h8e8fcc4_1, py36h0a44026_0, py36h0a44026_1, py37h9c2f6ca_1, py36h2e20a7f_0, py37h9c2f6ca_0, py37h63f7a3c_0, py38haa244fe_0, py38haa244fe_1, py27hfc679d8_0, py27hfc679d8_1, py27h0a44026_0, py27h0a44026_1, py38he1b5a44_0, py38he1b5a44_2, py27hf484d3e_1001, py27hf484d3e_1000, py27hf484d3e_1, py27hf484d3e_0, py36hf484d3e_1001, py39hdf13c20_1, py39hdf13c20_0, py37h1c9c24e_0, py37he1b5a44_2, py37he1b5a44_0, py37he1b5a44_1, py27h6de7cb9_1, py27h6de7cb9_0, py38h4a8c4bd_2, py38h4a8c4bd_0, py38h7ae7562_0, py38h7ae7562_1, py36h176e57e_1, py36h176e57e_0, py36he7c05b7_0, py39ha65689a_0, py39ha65689a_1, py37h3340039_0, py37h3340039_1, py37h0a44026_1, py37h0a44026_0, py37hf484d3e_0, py37hf484d3e_1, py37h03978a9_1, py37h03978a9_0, py37hf985489_1, py37hf985489_0, py36hb209c28_2, py36h2e20a7f_1, py36h704843e_0, py36h704843e_1, py38h150bfb4_1, py38h150bfb4_0, py38hb99c5c2_0, py36hf484d3e_1000, py36h27176af_0, py38h11c0d25_0, py36h5dafb3c_1, py36h5dafb3c_0, py27he1b5a44_1, py27he1b5a44_0, py27he1b5a44_2, py27h4a8c4bd_0, py36he1b5a44_2, py36h4a8c4bd_2, py36h90709c0_1, py37h4c0cbd9_0: A Python-embedded modeling language for convex optimization problemsconda-forge/cvxpy-base    |   1.1.15 | conda           | linux-ppc64le, osx-arm64, linux-64, linux-aarch64, osx-64, win-64 | py36h7083def_0, py38hcb8c335_0, py37h157fc04_0, py37h157fc04_1, py36h0a44026_1000, py36h0a44026_1001, py37hfc679d8_1, py37hfc679d8_0, py36h01e7d0c_1, py36h01e7d0c_0, py38h43a58ef_0, py38h950e882_0, py37hdc94413_0, py37hdc94413_1, py38h9b9bf68_0, py36he38d939_0, py36he38d939_1, py36hd724563_0, py37h33eeba9_1, py37h010c265_1, py39hde0f152_0, py37h9fdb41a_0, py39h7b4a2eb_1, py39h7b4a2eb_0, py36h77a88e9_0, py37h1834ac0_0, py38h51da96c_1, py37hff173d8_0, py37he1dd5e6_0, py37h6538335_2, py36hb2ee36f_0, py36hcc50265_1, py38hf2e80fd_0, py37h94625e5_0, py36hcc50265_0, py36h18adda2_0, py36h81ad375_0, py36h81ad375_1, py37h9386db6_0, py36h215fddc_0, py36h3083d40_0, py38h6538335_2, py37h40f5888_0, py38h6538335_0, py38he6e81aa_0, py38he6e81aa_1, py37h40f5888_1, py36hbd05846_0, py38hc84c608_0, py37h5b83a90_0, py37hb809cae_0, py27h4a8c4bd_0, py37h219a48f_0, py27h0a44026_1000, py27h0a44026_1001, py36h1dd77cb_0, py37ha200abb_0, py36he43235d_0, py37h6de7cb9_0, py37h6de7cb9_1, py39h4d6be9b_0, py37h570ac47_0, py37h414f9d2_0, py39ha3b3222_0, py38h9529b5f_0, py37h0a44026_1001, py37h0a44026_1000, py36he1b5a44_1, py36he1b5a44_0, py38he9f00de_1, py37h6538335_1, py37h6538335_0, py37hf484d3e_1000, py37hf484d3e_1001, py37he8f5f7f_0, py38ha53d530_0, py36he8b1a61_0, py37hb209c28_2, py39h089d6f7_1, py36h284efc9_0, py36h284efc9_1, py37h7bc7096_0, py38h768f383_0, py37h0b113e5_0, py38h6be0db6_0, py36hcf32051_0, py36h003fed8_0, py37h4899282_0, py27h4a8c4bd_2, py36h831f99a_0, py38h251f6bf_0, py36hf484d3e_1, py36hf484d3e_0, py36hfc679d8_0, py36hfc679d8_1, py38h64fa5dd_1, py37h94625e5_1, py38h1abd341_0, py37h7d02bce_0, py36hcc1bba6_1, py36hcc1bba6_0, py36h6538335_0, py36h6538335_1, py36h6538335_2, py36h8db7ee2_0, py36h0130604_0, py37h4a8c4bd_0, py36h4a8c4bd_0, py37h4a8c4bd_2, py38hb209c28_2, py37hb23ed4d_0, py36h72eec15_0, py38h60cbd38_0, py37h9ee2552_1, py37h9ee2552_0, py38h51da96c_0, py37h6d0141a_0, py36h6de7cb9_1, py36h6de7cb9_0, py36hfdae8ee_1, py36hfdae8ee_0, py38h8e8fcc4_0, py38h64fa5dd_0, py38h9b9bf68_1, py37h3bbf574_0, py36h2be6da3_1, py36h0a44026_0, py36h0a44026_1, py38h1f261ad_0, py37h63f7a3c_0, py36h830a2c2_0, py36h830a2c2_1, py27hfc679d8_0, py27hfc679d8_1, py27h0a44026_0, py27h0a44026_1, py37h90003fb_0, py38he1b5a44_0, py39h7f752ed_0, py38he1b5a44_2, py38h5d928e2_0, py27hf484d3e_1001, py27hf484d3e_1000, py27hf484d3e_1, py27hf484d3e_0, py36hf484d3e_1001, py37h9fdb41a_1, py36hf484d3e_1000, py37he1b5a44_2, py37he1b5a44_0, py37he1b5a44_1, py27h6de7cb9_1, py27h6de7cb9_0, py38h1588c1c_0, py37h08fd248_0, py37h08fd248_1, py36h1f72e70_1, py38h4a8c4bd_2, py38h4a8c4bd_0, py36hd2ac9e4_0, py38h7ae7562_0, py36h8db7ee2_1, py38hb77cc89_0, py37h3bbf574_1, py37h0a44026_1, py37h3340039_0, py37h0da4684_0, py36h7c3b610_1, py36h7c3b610_0, py39h2e25243_1, py39h2e25243_0, py36hcf32051_1, py37h0da4684_1, py37h0a44026_0, py37hf484d3e_0, py37hf484d3e_1, py38h3777fb4_0, py37h083aec9_0, py36h0cdc3f0_0, py37h7a63c39_0, py36h7bbf041_0, py36h84e8a9e_0, py36h84a794e_0, py38h5fc983b_1, py38h5fc983b_0, py37he1dd5e6_1, py36hd7f5668_0, py39ha4bedbf_0, py39ha4bedbf_1, py36hb209c28_2, py38hc5bc63f_1, py38hc5bc63f_0, py38h4c96930_1, py38h4c96930_0, py36h0cd6c39_1, py38h36e2a69_1, py38h36e2a69_0, py38hb99c5c2_0, py38hcb8c335_1, py36h0cd6c39_0, py27he1b5a44_1, py27he1b5a44_0, py39hde0f152_1, py27he1b5a44_2, py36ha63b481_0, py36ha63b481_1, py36he1b5a44_2, py36h4a8c4bd_2, py36h4772d2b_0: A Python-embedded modeling language for convex optimization problemscvxgrp/cvxpy              |  1.1.0a4 | conda           | linux-64, win-64, noarch, osx-64 | py37_0, py27_0, py36_0, py36hff9b014_0, py27hf9d7886_0, py_0, py35_0: A domain-specific language for modeling convex optimization problems in Python.dougal/cvxpy              |          | conda           | osx-64          | np18py27_0, np17py27_0, np112py35_0dseuss/cvxpy              |    0.4.9 | conda           | linux-64, noarch, linux-32, osx-64 | py_0, nomkl, py35_0elvo/cvxpy                |   0.4.11 | conda           | linux-64        | py36_0: A domain-specific language for modeling convex optimization problems in Python.omnia/cvxpy               |    0.4.8 | conda           | linux-64, win-32, win-64, osx-64 | np18py33_0, py27_0, py33_0, py34_0, np19py33_0, np19py34_0, np18py27_0, np18py34_0, py36_0, np19py27_0, py35_0: A domain-specific language for modeling convex optimization problems in Python.rjmurray/cvxpy            |   1.0.23 | conda           | linux-64, osx-64, win-64 | py37_0, py36_0, py35_0, py27_0: A domain-specific language for modeling convex optimization problems in Python.sebp/cvxpy                |   1.0.31 | conda           | linux-64, win-64, osx-64 | py36h08c4464_0, py37_0, py35h706afa7_0, py34_2, py34_1, py34_0, py36_0, py38_0, py35hc0c2b60_0, py35h5c89f6d_0, py36h126ee5d_0, py36h7bc49e1_0, py35h0ec0023_0, py35_2, py35_0, py35_1: A domain-specific language for modeling convex optimization problems in Python.sebp/cvxpy-base           |   1.0.31 | conda           | linux-64, osx-64, win-64 | py36hf484d3e_0, py36h0a44026_0, py38h6de7cb9_0, py37h6de7cb9_0, py38hf484d3e_0, py36h6de7cb9_0, py36h6538335_0, py37h6538335_0, py37h0a44026_0, py37hf484d3e_0, py38h6538335_0: A domain-specific language for modeling convex optimization problems in Python.sotera/cvxpy              |    0.3.1 | conda           | linux-64        | py27_0: A domain-specific language for modeling convex optimization problems in Python.stevend2/CVXPY            |    0.4.6 | conda           | osx-64          | py35_0, py27_0: A Python-embedded modeling language for convex optimizationtravis/cvxpy              |      0.1 | conda           | linux-64        | py27_0: http://github.com/cvxgrp/cvxpy/
Found 19 packagesRun 'anaconda show <USER/PACKAGE>' to get installation details

得到如上结果得到一个可以用的包，接下来我们去获取其下载地址（找到对应的版本包）：
以 ***conda-forge/cvxpy | 1.1.15 | conda | linux-ppc64le, osx-arm64, linux-64, linux-aarch64, osx-64, win-64 |***为例
输入命令

anaconda show conda-forge/cvxpy

出现如下结果

Using Anaconda API: https://api.anaconda.org
Name:    cvxpy
Summary: A Python-embedded modeling language for convex optimization problems
Access:  public
Package Types:  conda
Versions:+ 1.0.6+ 1.0.8+ 1.0.10+ 1.0.12+ 1.0.14+ 1.0.15+ 1.0.24+ 1.0.25+ 1.0.21+ 1.0.27+ 1.0.28+ 1.0.29+ 1.0.31+ 1.1.0+ 1.1.1+ 1.1.3+ 1.1.4+ 1.1.5+ 1.1.6+ 1.1.7+ 1.1.8+ 1.1.10+ 1.1.11+ 1.1.12+ 1.1.13+ 1.1.14+ 1.1.15To install this package with conda run:conda install --channel https://conda.anaconda.org/conda-forge cvxpy

最后根据链接下载安装：

conda install --channel https://conda.anaconda.org/conda-forge cvxpy

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