爬虫 (三) anaconda3 入门

我们知道安装 anaconda3 之后会出现一下几个东东,我们来简单的了解下

1. Anaconda Navigtor :用于管理工具包和环境的图形用户界面,后续涉及的众多管理命令也可以在 Navigator 中手工实现

2. Jupyter notebook :基于web的交互式计算环境,可以编辑易于人们阅读的文档,用于展示数据分析的过程

3. spyder :一个使用Python语言、跨平台的、科学运算集成开发环境

4. qtconsole :一个可执行 IPython 的仿终端图形界面程序,相比 Python Shell 界面,qtconsole 可以直接显示代码生成的图形,实现多行代码输入执行,以及内置许多有用的功能和函数

01

conda –version

上面这个命令主要用于查询 anaconda3 的版本号,现在让我们按住键盘 (Win + R),回车(enter),便会出现一个控制台,我们输入 conda –version

conda --version

02

activate

activate 能将我们引入anaconda设定的虚拟环境中, 如果你后面什么参数都不加那么会进入anaconda自带的base环境,

你可以输入python试试, 这样会进入base环境的python解释器, 如果你把原来环境中的python环境去除掉会更能体会到, 这个时候在命令行中使用的已经不是你原来的python而是base环境下的python.而命令行前面也会多一个(base) 说明当前我们处于的是base环境下

03

conda create -n learn python=3

conda create -n learn python=3

我们当然不满足一个base环境, 我们应该为自己的程序安装单独的虚拟环境.

创建一个名称为learn的虚拟环境并指定python版本为3(这里conda会自动找3中最新的版本下载)

04

conda activate learn

切换环境

conda activate learn

推出环境

conda deactivate

05

conda env list

conda env list

去查看所有的环境

现在的learn环境除了python自带的一些官方包之外是没有其他包的, 一个比较干净的环境我们可以试试

06

conda install package

conda install requests

or

pip install requests

07

conda list

要查看当前环境中所有安装了的包可以用

07

conda env export > environment.yaml

如果想要导出当前环境的包信息可以用

conda env export > environment.yaml
name: base  channels:    - defaults  dependencies:    - _ipyw_jlab_nb_ext_conf=0.1.0=py37_0    - alabaster=0.7.12=py37_0    - anaconda=2019.10=py37_0    - anaconda-client=1.7.2=py37_0    - anaconda-navigator=1.9.7=py37_0    - anaconda-project=0.8.3=py_0    - asn1crypto=1.0.1=py37_0    - astroid=2.3.1=py37_0    - astropy=3.2.1=py37he774522_0    - atomicwrites=1.3.0=py37_1    - attrs=19.2.0=py_0    - babel=2.7.0=py_0    - backcall=0.1.0=py37_0    - backports=1.0=py_2    - backports.functools_lru_cache=1.5=py_2    - backports.os=0.1.1=py37_0    - backports.shutil_get_terminal_size=1.0.0=py37_2    - backports.tempfile=1.0=py_1    - backports.weakref=1.0.post1=py_1    - beautifulsoup4=4.8.0=py37_0    - bitarray=1.0.1=py37he774522_0    - bkcharts=0.2=py37_0    - blas=1.0=mkl    - bleach=3.1.0=py37_0    - blosc=1.16.3=h7bd577a_0    - bokeh=1.3.4=py37_0    - boto=2.49.0=py37_0    - bottleneck=1.2.1=py37h452e1ab_1    - bzip2=1.0.8=he774522_0    - ca-certificates=2019.8.28=0    - certifi=2019.9.11=py37_0    - cffi=1.12.3=py37h7a1dbc1_0    - chardet=3.0.4=py37_1003    - click=7.0=py37_0    - cloudpickle=1.2.2=py_0    - clyent=1.2.2=py37_1    - colorama=0.4.1=py37_0    - comtypes=1.1.7=py37_0    - conda=4.7.12=py37_0    - conda-build=3.18.9=py37_3    - conda-env=2.6.0=1    - conda-package-handling=1.6.0=py37h62dcd97_0    - conda-verify=3.4.2=py_1    - console_shortcut=0.1.1=3    - contextlib2=0.6.0=py_0    - cryptography=2.7=py37h7a1dbc1_0    - curl=7.65.3=h2a8f88b_0    - cycler=0.10.0=py37_0    - cython=0.29.13=py37ha925a31_0    - cytoolz=0.10.0=py37he774522_0    - dask=2.5.2=py_0    - dask-core=2.5.2=py_0    - decorator=4.4.0=py37_1    - defusedxml=0.6.0=py_0    - distributed=2.5.2=py_0    - docutils=0.15.2=py37_0    - entrypoints=0.3=py37_0    - et_xmlfile=1.0.1=py37_0    - fastcache=1.1.0=py37he774522_0    - filelock=3.0.12=py_0    - flask=1.1.1=py_0    - freetype=2.9.1=ha9979f8_1    - fsspec=0.5.2=py_0    - future=0.17.1=py37_0    - get_terminal_size=1.0.0=h38e98db_0    - gevent=1.4.0=py37he774522_0    - glob2=0.7=py_0    - greenlet=0.4.15=py37hfa6e2cd_0    - h5py=2.9.0=py37h5e291fa_0    - hdf5=1.10.4=h7ebc959_0    - heapdict=1.0.1=py_0    - html5lib=1.0.1=py37_0    - icc_rt=2019.0.0=h0cc432a_1    - icu=58.2=ha66f8fd_1    - idna=2.8=py37_0    - imageio=2.6.0=py37_0    - imagesize=1.1.0=py37_0    - importlib_metadata=0.23=py37_0    - intel-openmp=2019.4=245    - ipykernel=5.1.2=py37h39e3cac_0    - ipython=7.8.0=py37h39e3cac_0    - ipython_genutils=0.2.0=py37_0    - ipywidgets=7.5.1=py_0    - isort=4.3.21=py37_0    - itsdangerous=1.1.0=py37_0    - jdcal=1.4.1=py_0    - jedi=0.15.1=py37_0    - jinja2=2.10.3=py_0    - joblib=0.13.2=py37_0    - jpeg=9b=hb83a4c4_2    - json5=0.8.5=py_0    - jsonschema=3.0.2=py37_0    - jupyter=1.0.0=py37_7    - jupyter_client=5.3.3=py37_1    - jupyter_console=6.0.0=py37_0    - jupyter_core=4.5.0=py_0    - jupyterlab=1.1.4=pyhf63ae98_0    - jupyterlab_server=1.0.6=py_0    - keyring=18.0.0=py37_0    - kiwisolver=1.1.0=py37ha925a31_0    - krb5=1.16.1=hc04afaa_7    - lazy-object-proxy=1.4.2=py37he774522_0    - libarchive=3.3.3=h0643e63_5    - libcurl=7.65.3=h2a8f88b_0    - libiconv=1.15=h1df5818_7    - liblief=0.9.0=ha925a31_2    - libpng=1.6.37=h2a8f88b_0    - libsodium=1.0.16=h9d3ae62_0    - libssh2=1.8.2=h7a1dbc1_0    - libtiff=4.0.10=hb898794_2    - libxml2=2.9.9=h464c3ec_0    - libxslt=1.1.33=h579f668_0    - llvmlite=0.29.0=py37ha925a31_0    - locket=0.2.0=py37_1    - lxml=4.4.1=py37h1350720_0    - lz4-c=1.8.1.2=h2fa13f4_0    - lzo=2.10=h6df0209_2    - m2w64-gcc-libgfortran=5.3.0=6    - m2w64-gcc-libs=5.3.0=7    - m2w64-gcc-libs-core=5.3.0=7    - m2w64-gmp=6.1.0=2    - m2w64-libwinpthread-git=5.0.0.4634.697f757=2    - markupsafe=1.1.1=py37he774522_0    - matplotlib=3.1.1=py37hc8f65d3_0    - mccabe=0.6.1=py37_1    - menuinst=1.4.16=py37he774522_0    - mistune=0.8.4=py37he774522_0    - mkl=2019.4=245    - mkl-service=2.3.0=py37hb782905_0    - mkl_fft=1.0.14=py37h14836fe_0    - mkl_random=1.1.0=py37h675688f_0    - mock=3.0.5=py37_0    - more-itertools=7.2.0=py37_0    - mpmath=1.1.0=py37_0    - msgpack-python=0.6.1=py37h74a9793_1    - msys2-conda-epoch=20160418=1    - multipledispatch=0.6.0=py37_0    - navigator-updater=0.2.1=py37_0    - nbconvert=5.6.0=py37_1    - nbformat=4.4.0=py37_0    - networkx=2.3=py_0    - nltk=3.4.5=py37_0    - nose=1.3.7=py37_2    - notebook=6.0.1=py37_0    - numba=0.45.1=py37hf9181ef_0    - numexpr=2.7.0=py37hdce8814_0    - numpy=1.16.5=py37h19fb1c0_0    - numpy-base=1.16.5=py37hc3f5095_0    - numpydoc=0.9.1=py_0    - olefile=0.46=py37_0    - openpyxl=3.0.0=py_0    - openssl=1.1.1d=he774522_2    - packaging=19.2=py_0    - pandas=0.25.1=py37ha925a31_0    - pandoc=2.2.3.2=0    - pandocfilters=1.4.2=py37_1    - parso=0.5.1=py_0    - partd=1.0.0=py_0    - path.py=12.0.1=py_0    - pathlib2=2.3.5=py37_0    - patsy=0.5.1=py37_0    - pep8=1.7.1=py37_0    - pickleshare=0.7.5=py37_0    - pillow=6.2.0=py37hdc69c19_0    - pip=19.2.3=py37_0    - pkginfo=1.5.0.1=py37_0    - pluggy=0.13.0=py37_0    - ply=3.11=py37_0    - powershell_shortcut=0.0.1=2    - prometheus_client=0.7.1=py_0    - prompt_toolkit=2.0.10=py_0    - psutil=5.6.3=py37he774522_0    - py=1.8.0=py37_0    - py-lief=0.9.0=py37ha925a31_2    - pycodestyle=2.5.0=py37_0    - pycosat=0.6.3=py37hfa6e2cd_0    - pycparser=2.19=py37_0    - pycrypto=2.6.1=py37hfa6e2cd_9    - pycurl=7.43.0.3=py37h7a1dbc1_0    - pyflakes=2.1.1=py37_0    - pygments=2.4.2=py_0    - pylint=2.4.2=py37_0    - pyodbc=4.0.27=py37ha925a31_0    - pyopenssl=19.0.0=py37_0    - pyparsing=2.4.2=py_0    - pyqt=5.9.2=py37h6538335_2    - pyreadline=2.1=py37_1    - pyrsistent=0.15.4=py37he774522_0    - pysocks=1.7.1=py37_0    - pytables=3.5.2=py37h1da0976_1    - pytest=5.2.1=py37_0    - pytest-arraydiff=0.3=py37h39e3cac_0    - pytest-astropy=0.5.0=py37_0    - pytest-doctestplus=0.4.0=py_0    - pytest-openfiles=0.4.0=py_0    - pytest-remotedata=0.3.2=py37_0    - python=3.7.4=h5263a28_0    - python-dateutil=2.8.0=py37_0    - python-libarchive-c=2.8=py37_13    - pytz=2019.3=py_0    - pywavelets=1.0.3=py37h8c2d366_1    - pywin32=223=py37hfa6e2cd_1    - pywinpty=0.5.5=py37_1000    - pyyaml=5.1.2=py37he774522_0    - pyzmq=18.1.0=py37ha925a31_0    - qt=5.9.7=vc14h73c81de_0    - qtawesome=0.6.0=py_0    - qtconsole=4.5.5=py_0    - qtpy=1.9.0=py_0    - requests=2.22.0=py37_0    - rope=0.14.0=py_0    - ruamel_yaml=0.15.46=py37hfa6e2cd_0    - scikit-image=0.15.0=py37ha925a31_0    - scikit-learn=0.21.3=py37h6288b17_0    - scipy=1.3.1=py37h29ff71c_0    - seaborn=0.9.0=py37_0    - send2trash=1.5.0=py37_0    - setuptools=41.4.0=py37_0    - simplegeneric=0.8.1=py37_2    - singledispatch=3.4.0.3=py37_0    - sip=4.19.8=py37h6538335_0    - six=1.12.0=py37_0    - snappy=1.1.7=h777316e_3    - snowballstemmer=2.0.0=py_0    - sortedcollections=1.1.2=py37_0    - sortedcontainers=2.1.0=py37_0    - soupsieve=1.9.3=py37_0    - sphinx=2.2.0=py_0    - sphinxcontrib=1.0=py37_1    - sphinxcontrib-applehelp=1.0.1=py_0    - sphinxcontrib-devhelp=1.0.1=py_0    - sphinxcontrib-htmlhelp=1.0.2=py_0    - sphinxcontrib-jsmath=1.0.1=py_0    - sphinxcontrib-qthelp=1.0.2=py_0    - sphinxcontrib-serializinghtml=1.1.3=py_0    - sphinxcontrib-websupport=1.1.2=py_0    - spyder=3.3.6=py37_0    - spyder-kernels=0.5.2=py37_0    - sqlalchemy=1.3.9=py37he774522_0    - sqlite=3.30.0=he774522_0    - statsmodels=0.10.1=py37h8c2d366_0    - sympy=1.4=py37_0    - tbb=2019.4=h74a9793_0    - tblib=1.4.0=py_0    - terminado=0.8.2=py37_0    - testpath=0.4.2=py37_0    - tk=8.6.8=hfa6e2cd_0    - toolz=0.10.0=py_0    - tornado=6.0.3=py37he774522_0    - tqdm=4.36.1=py_0    - traitlets=4.3.3=py37_0    - unicodecsv=0.14.1=py37_0    - urllib3=1.24.2=py37_0    - vc=14.1=h0510ff6_4    - vs2015_runtime=14.16.27012=hf0eaf9b_0    - wcwidth=0.1.7=py37_0    - webencodings=0.5.1=py37_1    - werkzeug=0.16.0=py_0    - wheel=0.33.6=py37_0    - widgetsnbextension=3.5.1=py37_0    - win_inet_pton=1.1.0=py37_0    - win_unicode_console=0.5=py37_0    - wincertstore=0.2=py37_0    - winpty=0.4.3=4    - wrapt=1.11.2=py37he774522_0    - xlrd=1.2.0=py37_0    - xlsxwriter=1.2.1=py_0    - xlwings=0.15.10=py37_0    - xlwt=1.3.0=py37_0    - xz=5.2.4=h2fa13f4_4    - yaml=0.1.7=hc54c509_2    - zeromq=4.3.1=h33f27b4_3    - zict=1.0.0=py_0    - zipp=0.6.0=py_0    - zlib=1.2.11=h62dcd97_3    - zstd=1.3.7=h508b16e_0  prefix: D:Anaconda3

导入信息

conda env create -f environment.yaml

08

more

activate // 切换到base环境    activate learn // 切换到learn环境    conda create -n learn python=3 // 创建一个名为learn的环境并指定python版本为3(的最新版本)    conda env list // 列出conda管理的所有环境    conda list // 列出当前环境的所有包    conda install requests 安装requests包    conda remove requests 卸载requets包    conda remove -n learn --all // 删除learn环境及下属所有包    conda update requests 更新requests包    conda env export > environment.yaml // 导出当前环境的包信息    conda env create -f environment.yaml // 用配置文件创建新的虚拟环境

08

与 pyCharm 链接

在工作环境中我们会集成开发环境去编码, 这里推荐JB公司的pycharm, 而pycharm也能很方便的和anaconda的虚拟环境结合

Setting => Project => Project Interpreter 里面修改 Project Interpreter , 点击齿轮标志再点击Add Local为你某个环境的python.exe解释器就行了

比如你要在learn环境中编写程序, 那么就修改为D:SoftwareAnacondaenvslearn, 可以看到这时候下面的依赖包也变成了learn环境中的包了.接下来我们就可以在pycharm中愉快的编码了.

结语

现在你是不是发现用上anaconda就可以十分优雅简单的解决上面所提及的单个python环境所带来的弊端了呢, 而且也明白了其实这一切的实现并没有那么神奇.

当然anaconda除了包管理之外还在于其丰富数据分析包, 不过那就是另一个内容了, 我们先学会用anaconda去换一种方法管里自己的开发环境, 这已经是一个很大的进步了