Python for mac 中包安装管理;Mac Python管理虚拟环境软件安装;Python包管理工具;python多版本管理(MacOS)php
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#去查看要更新pip目前的版本 $ pip -V # for Python 2 $ pip3 -V # for Python 3
#检查完后,要升级对应的版本 #第一种,若是失败,尝试第二种 $pip install --upgrade pip # for Python2 $pip3 install --upgrade pip # for Python3 #第二种 $ sudo easy_install --upgrade pip $ sudo easy_install --upgrade six #能够不实用这条
目录html5
前言java
一 管理虚拟环境软件node
1.1 Mac Python管理虚拟环境软件安装-Pyenv具体的流程python
1.2 Mac Python管理虚拟环境软件安装-Anaconda具体的流程mysql
1.3 Mac Python管理虚拟环境软件安装-pip具体的流程linux
二 探索的原由git
2.1 具体的问题(报错)程序员
2.2 先检查Python的安装与路径
2.3 安装包——Numpy
2.4 安装包——matplotlib
2.5 安装包——scipy
2.6 安装pandas
2.7 安装TensorFlow
前言
你们要在开发中,使用多个python版本的,强烈建议使用安装管理器和工具管理虚拟环境,否则就会出现如下一系列报错。所以会教你如何安装Python的 pandas等各种包。
安装brew,安装教程。咱们经过brew能够快捷方便的下载咱们须要的各种软件,包括pyenv,Anaconda,virtualenv(虚拟环境)等。咱们经过如下途径来完成python包的管理:
1. Anaconda:安装pandas、Python和SciPy最简单的方式是用Anaconda。Anaconda是关于Python数据分析和科学计算的分发包。
2. Miniconda
使用Anaconda会安装一百多个依赖包,若是想灵活控制安装的依赖包或带宽有限,使用Miniconda是个不错的选择。
Conda是个包管理器,Anaconda就是创建在它的基础上。Conda不仅跨平台还与语言无关,与pip和virtualenv相结合的做用类似。
Miniconda容许先建立包含Python的安装包,而后用conda安装其余的依赖包。
3. pip
pandas能够经过pip安装,但要安装相关的依赖包。
[plain] view plain copy
pip install pandas
4. 包管理器
能够用linux的包管理器进行安装,如
[plain] view plain copy
sudo apt-get install python-pandas
zypper in python-pandas
5. 源码安装
从源码安装须要安装最新的Cython,可用easy-install -U cython安装。源码位于http://github.com/pydata/pandas,安装过程为[plain] view plain copy
git clone git://github.com/pydata/pandas.git
cd pandas
python setup.py install
一 管理虚拟环境软件
1.1 Mac Python管理虚拟环境软件安装-Pyenv具体的流程
1 先安装管理软件pyenv
我的安装信息 87:~ jss$ brew install pyenv Updating Homebrew... ==> Auto-updated Homebrew! Updated 1 tap (homebrew/core). ==> Updated Formulae app-engine-java geth lorem radare2 bit getmail mapnik roswell calabash gtk+ node s-nail cayley gutenberg node@4 sassc conan gxml node@6 saxon diffuse heroku node@8 spigot django-completion igv nspr syncthing docfx jbake odpi tile38 flow jenkins onetime yaml-cpp fluent-bit just openimageio yarn flyway kerl php fn libsass plank ==> Installing dependencies for pyenv: autoconf, pkg-config, openssl, readline ==> Installing pyenv dependency: autoconf ==> Downloading https://homebrew.bintray.com/bottles/autoconf-2.69.high_sierra.b ######################################################################## 100.0% ==> Pouring autoconf-2.69.high_sierra.bottle.4.tar.gz ==> Caveats Emacs Lisp files have been installed to: /usr/local/share/emacs/site-lisp/autoconf ==> Summary 🍺 /usr/local/Cellar/autoconf/2.69: 71 files, 3.0MB ==> Installing pyenv dependency: pkg-config ==> Downloading https://homebrew.bintray.com/bottles/pkg-config-0.29.2.high_sier ######################################################################## 100.0% ==> Pouring pkg-config-0.29.2.high_sierra.bottle.tar.gz 🍺 /usr/local/Cellar/pkg-config/0.29.2: 11 files, 627.2KB ==> Installing pyenv dependency: openssl ==> Downloading https://homebrew.bintray.com/bottles/openssl-1.0.2n.high_sierra. ######################################################################## 100.0% ==> Pouring openssl-1.0.2n.high_sierra.bottle.tar.gz ==> Caveats A CA file has been bootstrapped using certificates from the SystemRoots keychain. To add additional certificates (e.g. the certificates added in the System keychain), place .pem files in /usr/local/etc/openssl/certs and run /usr/local/opt/openssl/bin/c_rehash This formula is keg-only, which means it was not symlinked into /usr/local, because Apple has deprecated use of OpenSSL in favor of its own TLS and crypto libraries. If you need to have this software first in your PATH run: echo 'export PATH="/usr/local/opt/openssl/bin:$PATH"' >> ~/.bash_profile For compilers to find this software you may need to set: LDFLAGS: -L/usr/local/opt/openssl/lib CPPFLAGS: -I/usr/local/opt/openssl/include For pkg-config to find this software you may need to set: PKG_CONFIG_PATH: /usr/local/opt/openssl/lib/pkgconfig ==> Summary 🍺 /usr/local/Cellar/openssl/1.0.2n: 1,792 files, 12.3MB ==> Installing pyenv dependency: readline ==> Downloading https://homebrew.bintray.com/bottles/readline-7.0.3_1.high_sierr ######################################################################## 100.0% ==> Pouring readline-7.0.3_1.high_sierra.bottle.tar.gz ==> Caveats This formula is keg-only, which means it was not symlinked into /usr/local, because macOS provides the BSD libedit library, which shadows libreadline. In order to prevent conflicts when programs look for libreadline we are defaulting this GNU Readline installation to keg-only.. For compilers to find this software you may need to set: LDFLAGS: -L/usr/local/opt/readline/lib CPPFLAGS: -I/usr/local/opt/readline/include ==> Summary 🍺 /usr/local/Cellar/readline/7.0.3_1: 46 files, 1.5MB ==> Installing pyenv ==> Downloading https://homebrew.bintray.com/bottles/pyenv-1.2.2.high_sierra.bot ######################################################################## 100.0% ==> Pouring pyenv-1.2.2.high_sierra.bottle.tar.gz 🍺 /usr/local/Cellar/pyenv/1.2.2: 593 files, 2.4MB
2 安装后添加环境变量,在terminal中输入
sudo vi ~/.bash_profile
3 填写的具体变量内容
(我的信息:修改后备份 export PATH=${PATH}:/usr/local/mysql/bin )
export PYENV_ROOT=/usr/local/var/pyenv
if which pyenv > /dev/null; then eval "$(pyenv init -)"; fi
4 使环境变量生效,须要使环境变量生效,运行命令
. ~/.bash_profile
#或者
source ~/.bash_profile
参考:
❌https://www.jianshu.com/p/972512527e9a -简书/Mac OSX下Python多版本管理器pyenv的安装及使用
http://blog.csdn.net/suyumingxiangguan/article/details/69942055 -csdn/Mac多Python版本共存,多个独立Python开发环境切换。
1.2 Mac Python管理虚拟环境软件安装-Anaconda具体的流程
a Anaconda简介
而后就是多方式安装包或者模块。其中优先conda,其次pip,再次https://www.lfd.uci.edu/~gohlke/pythonlibs/或者各类官网,最后本身编译
conda下载的是二进制,pip有的会下载源码编译
Anaconda软件集成了不少python的库,包括pandas,用python作数据分析的不少人都用这个
Anaconda 是一个用于科学计算的Python发行版,支持 Linux, Mac, Windows系统,提供了包管理与环境管理的功能,能够很方便地解决多版本python并存、切换以及各类第三方包安装问题。Anaconda利用工具/命令conda来进行package和environment的管理,而且已经包含了Python和相关的配套工具。 这里先解释下conda、anaconda这些概念的差异。是一个打包的集合,里面预装好了conda、某个版本的python、众多packages、科学计算工具等等,因此也称为Python的一种发行版。conda能够理解为一个工具,也是一个可执行命令,其核心功能是包管理与环境管理。包管理与pip的使用相似,环境管理则容许用户方便地安装不一样版本的python并能够快速切换。
参考:
http://blog.csdn.net/superdont/article/details/54233017 - csdn/Anaconda的安装与配置/镜像的配置
http://www.cnblogs.com/welhzh/p/6009246.html -cnblog/python 安装anaconda, numpy, pandas, matplotlib 等/terminal conda的操做与镜像的配置
https://www.zhihu.com/question/47003185 -知乎/如何优雅的安装Python的pandas?
https://www.jianshu.com/p/2f3be7781451 -简书/Anaconda使用总结
http://blog.csdn.net/cxsydjn/article/details/71057124 -csdn/Mac OS下 Anaconda Python2 和 Python3 配置/界面简介和python不一样版本安装
https://www.cnblogs.com/amanda-x/p/7739467.html -cnblogs/Anaconda安装与环境配置
1.3 Mac Python管理虚拟环境软件安装-pip具体的流程
1 优缺点
缺点:下载速度慢,20180308安装中,下载速度介于20-50kb/s
优势:方便简单,无需太多的安装与操做
2 查看已安装包列表
#适用于mac中python2.x 版本 pip list
#适用于mac中python3.x 版本 pip3 list
3 安装依赖包和模块
#适用于mac中python2.x 版本,xx是包名称 pip install xx
#适用于mac中python3.x 版本,xx是包名称 pip3 install xx
参考:
✅https://www.cnblogs.com/tensorflownews/p/7298646.html -cnbolg/在 Mac OS X 上安装 TensorFlow
https://www.jianshu.com/p/4646dedaaff5 -简书/Python安装与版本管理/pip使用沙盒使用
二 探索的原由
2.1 具体的问题(报错)
半路出家,调试代码中出现如下错误
Traceback (most recent call last): File "<stdin>", line 1, in <module>ModuleNotFoundError: No module named 'numpy'
Traceback (most recent call last): File "MLCNN.py", line 8, in <module> import matplotlib.pyplot as pltModuleNotFoundError: No module named 'matplotlib'
Traceback (most recent call last): File "MLCNN.py", line 9, in <module> import scipy.ioModuleNotFoundError: No module named 'scipy'
Traceback (most recent call last): File "MLCNN.py", line 11, in <module> import tensorflow as tfModuleNotFoundError: No module named 'tensorflow'
Traceback (most recent call last):
File "MLCNN.py", line 12, in <module>
import pandas as pd
ModuleNotFoundError: No module named 'pandas'
2.2 先检查Python的版本与路径
1 查看python版本
#注意:‘-V‘中‘V’为大写字母,只有一个‘-’ python -V
#注意:‘--version'中有两个‘-’ python --version
2 查看python安装位置
python3以上的版本 注意print的时候使用的是括号,python3如下版本的不须要括号
python -c "import sys; print (sys.executable)"
python -c "import os; print (os.sys.executable)" python -c "import os; path = os.sys.executable;folder=path[0 : path.rfind(os.sep)]; print folder"
2.3 安装包——Numpy(pip)
1 查看Numpy版本
python -c "import numpy; print (numpy.version.version)"
python3 -c "import numpy; print (numpy.__version__)"
2 查看Numpy安装路径
#python2.x版本 python -c "import numpy; print (numpy.__file__)"
python -c "import numpy; print (numpy.__file__)"
#python3.x版本 python3 -c "import numpy; print (numpy.__file__)"
python3 -c "import numpy; print (numpy.__file__)"
3 安装
$pip install --user numpy scipy matplotlib ipython jupyter pandas sympy nose --prefix=~/local
4 将package安装到指定目录:经过源码安装一个python包的时候,例如安装xlrd,目标路径为/usr/local/lib/python2.7/site-packages/
$ pip install -t /usr/local/lib/python2.7/site-packages/ xlrd
5 或者我已经测试成功的,网站为
$mac os x: Python 3 安装(scipy,numpy,matplotlib. . .)
2.4 安装包——matplotlib
方法一 使用Pip
先安装pip,参考标准pip安装指令
curl -O https://bootstrap.pypa.io/get-pip.py
安装到Python2.7
python get-pip.py
安装到Python3
python3 get-pip.py
安装Matplotlib
pip install matplotlib
报错:猜想多是由于多个版本形成的问题,个人目标安装是python36,最后在这个论坛里找到解决方法。
Requirement already satisfied: matplotlib in /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/pythonRequirement already satisfied: numpy>=1.5 in /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python (from matplotlib)Requirement already satisfied: python-dateutil in /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python (from matplotlib)Requirement already satisfied: tornado in ./Library/Python/2.7/lib/python/site-packages (from matplotlib)Requirement already satisfied: pyparsing>=1.5.6 in /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python (from matplotlib)Requirement already satisfied: nose in ./Library/Python/2.7/lib/python/site-packages (from matplotlib)Requirement already satisfied: singledispatch in ./Library/Python/2.7/lib/python/site-packages (from tornado->matplotlib)Requirement already satisfied: certifi in ./Library/Python/2.7/lib/python/site-packages (from tornado->matplotlib)Requirement already satisfied: backports_abc>=0.4 in ./Library/Python/2.7/lib/python/site-packages (from tornado->matplotlib)Requirement already satisfied: six in /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python (from singledispatch->tornado->matplotlib)
个人pip list
DEPRECATION: The default format will switch to columns in the future. You can use --format=(legacy|columns) (or define a format=(legacy|columns) in your pip.conf under the [list] section) to disable this warning.altgraph (0.10.2)appnope (0.1.0)backports-abc (0.5)backports.functools-lru-cache (1.5)backports.shutil-get-terminal-size (1.0.0)bdist-mpkg (0.5.0)bleach (2.1.2)bonjour-py (0.3)certifi (2018.1.18)configparser (3.5.0)cycler (0.10.0)decorator (4.2.1)entrypoints (0.2.3)enum34 (1.1.6)functools32 (3.2.3.post2)html5lib (1.0.1)ipykernel (4.8.2)ipython (5.5.0)ipython-genutils (0.2.0)ipywidgets (7.1.2)Jinja2 (2.10)jsonschema (2.6.0)jupyter (1.0.0)jupyter-client (5.2.2)jupyter-console (5.2.0)jupyter-core (4.4.0)lxml (4.1.1)macholib (1.5.1)Markdown (2.6.9)MarkupSafe (1.0)matplotlib (2.1.2)mistune (0.8.3)modulegraph (0.10.4)mpmath (1.0.0)nbconvert (5.3.1)nbformat (4.4.0)nose (1.3.7)notebook (5.4.0)numpy (1.14.1)pandas (0.22.0)pandocfilters (1.4.2)pathlib2 (2.3.0)pexpect (4.4.0)pickleshare (0.7.4)pip (9.0.1)prompt-toolkit (1.0.15)ptyprocess (0.5.2)py2app (0.7.3)Pygments (2.2.0)pyobjc-core (2.5.1)pyobjc-framework-Accounts (2.5.1)pyobjc-framework-AddressBook (2.5.1)pyobjc-framework-AppleScriptKit (2.5.1)pyobjc-framework-AppleScriptObjC (2.5.1)pyobjc-framework-Automator (2.5.1)pyobjc-framework-CFNetwork (2.5.1)pyobjc-framework-Cocoa (2.5.1)pyobjc-framework-Collaboration (2.5.1)pyobjc-framework-CoreData (2.5.1)pyobjc-framework-CoreLocation (2.5.1)pyobjc-framework-CoreText (2.5.1)pyobjc-framework-DictionaryServices (2.5.1)pyobjc-framework-EventKit (2.5.1)pyobjc-framework-ExceptionHandling (2.5.1)pyobjc-framework-FSEvents (2.5.1)pyobjc-framework-InputMethodKit (2.5.1)pyobjc-framework-InstallerPlugins (2.5.1)pyobjc-framework-InstantMessage (2.5.1)pyobjc-framework-LatentSemanticMapping (2.5.1)pyobjc-framework-LaunchServices (2.5.1)pyobjc-framework-Message (2.5.1)pyobjc-framework-OpenDirectory (2.5.1)pyobjc-framework-PreferencePanes (2.5.1)pyobjc-framework-PubSub (2.5.1)pyobjc-framework-QTKit (2.5.1)pyobjc-framework-Quartz (2.5.1)pyobjc-framework-ScreenSaver (2.5.1)pyobjc-framework-ScriptingBridge (2.5.1)pyobjc-framework-SearchKit (2.5.1)pyobjc-framework-ServiceManagement (2.5.1)pyobjc-framework-Social (2.5.1)pyobjc-framework-SyncServices (2.5.1)pyobjc-framework-SystemConfiguration (2.5.1)pyobjc-framework-WebKit (2.5.1)pyOpenSSL (0.13.1)pyparsing (2.2.0)python-dateutil (2.6.1)pytz (2018.3)pyzmq (17.0.0)qtconsole (4.3.1)scandir (1.7)scipy (0.13.0b1)Send2Trash (1.5.0)setuptools (18.5)simplegeneric (0.8.1)singledispatch (3.4.0.3)six (1.11.0)subprocess32 (3.2.7)sympy (1.1.1)terminado (0.8.1)testpath (0.3.1)tornado (4.5.3)traitlets (4.3.2)virtualenv (15.1.0)wcwidth (0.1.7)webencodings (0.5.1)widgetsnbextension (3.1.4)xattr (0.6.4)zope.interface (4.1.1)
执行的命令
python3 -m pip install --user --upgrade matplotlib
方法二 Macports
Python 2.7
sudo port install py27-pipsudo pip-2.7 install matplotlib
Python 3.6:
sudo port install py36-pipsudo pip-3.6 install matplotlib
2.5 安装包——scipy(pip)
python3 -m pip install scipy import scipy
测试一下
import scipy
2.6 安装pandas
1. Anaconda:安装pandas、Python和SciPy最简单的方式是用Anaconda。Anaconda是关于Python数据分析和科学计算的分发包。
2. Miniconda
使用Anaconda会安装一百多个依赖包,若是想灵活控制安装的依赖包或带宽有限,使用Miniconda是个不错的选择。
Conda是个包管理器,Anaconda就是创建在它的基础上。Conda不仅跨平台还与语言无关,与pip和virtualenv相结合的做用类似。
Miniconda容许先建立包含Python的安装包,而后用conda安装其余的依赖包。
3. Pypi
pandas能够经过pip安装,但要安装相关的依赖包。
[plain] view plain copy
pip install pandas
4. 包管理器
能够用linux的包管理器进行安装,如
[plain] view plain copy
sudo apt-get install python-pandas
zypper in python-pandas
5. 源码安装
从源码安装须要安装最新的Cython,可用easy-install -U cython安装。源码位于http://github.com/pydata/pandas,安装过程为
[plain] view plain copy
git clone git://github.com/pydata/pandas.git
cd pandas
python setup.py install
2.7 安装TensorFlow(pip)
#python2版本 pip install tensorflow
#python3版本 pip3 install tensorflow
安装成功后,若是仍然报错
Traceback (most recent call last):
File "MLCNN.py", line 10, in <module>
import tensorflow as tf
ModuleNotFoundError: No module named 'tensorflow'
解决方案1——卸载重装tensorflow(未解决)
(pip重装后测试无效果)
$ pip uninstall tensorflow
$ pip3 uninstall tensorflow
http://bbs.csdn.net/topics/392322815?list=lz -csdn/Python与TensorFlow安装遇到问题求助
http://blog.csdn.net/evaljy/article/details/70209957 -csdn/tensorflow在win上的安装常见错误及正确安装步骤(包含anaconda spyder)/报错集合
解决方案2——用Anaconda来进行激活使用(未解决)
首先安装Anaconda,安装成功后,建立一个conda环境
conda create -n tensorflow pip python = 2.7
conda create -n tensorflow pip python = 3.6 #或python = 3.3等
激活环境
source activate tensorflow
# (targetDirectory)$ Your prompt should change
在环境中安装Tensorflow
pip install --ignore-installed --upgrade \ https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.6.0-py2-none-any.whl #TensorFlow for Python 2.7的纯CPU版本
pip install --ignore-installed --upgrade \ https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.6.0-py3-none-any.whl #Python 3.4,3.5或3.6
参考:
https://www.tensorflow.org/install/install_mac -tensorflow官网
正确的安装方法
⭐️http://blog.csdn.net/u012373815/article/details/73555460 -csdn/mac/linux 安装tensorflow和安装Anaconda
tensorflow拓展学习
http://www.tensorflownews.com/category/course/ -tensorflownews/tensorflownews/我的网站
参考:
✅http://www.cnblogs.com/tensorflownews/p/7298646.html -cnblogs/在 Mac OS X 上安装 TensorFlow
参考:
https://jingyan.baidu.com/article/fec7a1e5ec30341190b4e7e5.html -Mac下如何安装配置Homebrew
http://blog.csdn.net/ybuiipl/article/details/60875304 -Linux/numpy的下载与安装教程——(解决No module named numpy问题)
https://www.cnblogs.com/klchang/p/4543032.html -python和numpy的版本、安装位置
https://www.zhihu.com/question/21731171 -安装Numpy
http://blog.csdn.net/ciyiquan5963/article/details/77531932 -Mac/MAC 使用pycharm出现ImportError: No module named numpy 解决方法
http://rstevens.iteye.com/blog/1214143 -安装python package到指定目录
http://blog.csdn.net/techfield/article/details/52618130 -多版本Python共存时pip给指定版本的python安装package的方法
https://www.jianshu.com/p/21bb9d06cf79 -[Mac] Python Numpy Scipy Matplotlib 快速安装
⭐️http://blog.topspeedsnail.com/archives/704 -mac os x: Python 3 安装(scipy,numpy,matplotlib. . .)
https://stackoverflow.com/questions/33888760/importerror-no-module-named-matplotlib -ImportError: No module named matplotlib
http://blog.csdn.net/a595130080/article/details/55506237 - tensorflow
2018-03-0809:00:00
2018-03-0821:17:12