Anaconda package for python

Installing conda packages#

You can install the conda package manager with Anaconda Distribution or Miniconda . From there, you have several ways in which you can get packages to use in your conda environments:

• Over 250 packages are automatically installed with Anaconda.
• Over 7,500 additional open-source packages (including R) can be individually installed from the Anaconda repository with the conda install command.
• Thousands of other packages are available from Anaconda.org.
• You can download other packages using the pip install command that is installed with Anaconda. Pip packages provide many of the features of conda packages and in some cases they can work together. However, the preference should be to install the conda package if it is available.
• You can also make your own custom packages using the conda build command, and you can share them with others by uploading them to Anaconda.org, PyPI, or other repositories.

For more information about using the conda package manager in Anaconda Prompt (terminal on Linux or macOS), see the conda documentation.

You can also use the graphical interface Anaconda Navigator to install conda packages with just a few clicks.

Open an Anaconda Prompt (terminal on Linux or macOS) and follow these instructions.

Installing a conda package#

conda install package-name 

Installing specific versions of conda packages#

Include the desired version number or its prefix after the package name:

conda install package-name=2.3.4 

To specify only a major version, run:

conda install package-name=2 

These commands install into the environment that is currently active. To install into a named environment, run:

conda install package-name=2.3.4 -n some-environment 

If the package is specific to a Python version, conda uses the version installed in the current or named environment. For details on versions, dependencies and channels, see Conda FAQ and Conda Troubleshooting.

Installing packages on a non-networked (air-gapped) computer#

To directly install a conda package from your local computer, run:

conda install /package-path/package-filename.tar.bz2 

Conda installs packages into the anaconda/pkgs directory.

To install a .tar file containing many conda packages, run the following command:

conda install /packages-path/packages-filename.tar 

If conda cannot find the file, try using an absolute path name instead of a relative path name.

Installing packages directly from the file does not resolve dependencies. If your installed package does not work, it may have missing dependencies that need to be resolved manually.

Configuring a shared package cache

Using R language with Anaconda

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Conda

Conda is an open-source package and environment management system that runs on Windows, macOS, and Linux. Conda quickly installs, runs, and updates packages and their dependencies. It also easily creates, saves, loads, and switches between environments on your local computer. It was created for Python programs, but it can package and distribute software for any language.

Anaconda Navigator

Our desktop application lets you easily manage integrated applications, packages, and environments without using the command line.

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Python Anaconda Packages as One solution for all Data Science Problem

Data Science is already in full swing . Lots of libraries and their proper documentation is big advantage for every data scientist . As you know , Every coin has two phases . So if there are advantages then there must be disadvantages . Every data science project is consist of so many libraries . The pain area for every data scientist is to install every API one by one . If there is any update , we have to manually track it . This consumes lot of time in setting up the machines . Python Anaconda Packages comes as a solution for all these pain area . There will be single download of Python anaconda packages . This will work as One solution for all Data Science Problem . Anaconda is open source Data Science Platform . Conda is a package manager under this .

This article contains all essentials information about Python Anaconda Packages . Hey , One thing I forgot to mention . Before starting if are having doubt like What is Machine Learning and why we use it ? If there are so many alternative as programming language , Why should we choose python ? Okay ! if I choose python how to learn it ?

In that case , Do not worry , We are here with some fundamental article for basic under on data science . you can use above links for reaching to them .

How to Download Python Anaconda packages –

The first task before staring machine learning with ANACONDA is to download and install it . Here is the link for download and install Anaconda .Once you have the set up you can install it by clicking next . Make sure you have to select the check box which will ask you to auto set environment variable and system path in you local machine .If you do it , You will not have to externally add system path for python and anaconda. Hey congratulation on your set up .

I know you are thinking , What else to do in setting up machine further ? Man ! you are done, its really completed . Your expressions are realizing me the power of Python anaconda packages . Easy to set up and easy to use Right!

Anaconda Silent features –

1. IDEs with Anaconda-

There is again a surprise for you . You need not to separate install IDE for Anaconda . ANACONDA packages itself contain a IDE name SPYDER ( Scientific Python Development Environment) . SPYDER is interactive tool for testing , debugging and editing for python script .If you want to explore more on SPYDER , You need not to go anywhere just start SPYDER from console go to help section . You will find what you want .

I think this section of the article , is full of surprise for you . If you love any other IDE like Eclipse or you want to write code on sublime text . You can integrate it with Python Anaconda Packages .I think you want to learn more about IDEs Integration . I will recommend you to refer Anaconda IDEs Integration details .

This documentation will help you to answer all queries related to Integration of Anaconda with your favorite IDE. Apart from this , There are so many cloud platform like AWS ( Amazon Web Services) , Microsoft Azure also allow you to integrate Anaconda with them .

Well if you want to learn more about Best Python IDE for data scientist , Please refer this article .

2.Interactive Computation with IPython-

IPython is famous by the name of Jupyter Notebook these days .This gives you a freedom to write text between your code . Anaconda python packages by default contains it . Just go and launch IPython , After launching it, do not close the command prompt because it will work as a server . In few version, Ipython itself open a client tab on the default browser .In rest versions , The command window will give you an address with port . Just copy in browser and start coding and computation with Ipython .Anyways you can refer official website for IPython for more details .

3.Lighter Anaconda Package Manager –

In case , You do not have too much space or having less time to install complete Anaconda package .Which is a complete bundle , In this situation Miniconda will be the best for you. Miniconda is a lighter version of Anaconda .

Miniconda comes only with python and conda (Default Package Manager of Anaconda) where Anaconda has several other packages . You can install these packages from outside as per requirement .

4. Others Python Anaconda Packages –

If you guys are doing any data science project in python . You must need NumPy Library and SciPy Library for numerical computation . For plotting your data , you will also need MatPlotLib library in python .How can we forget Pandas for data structure handling . Here you can get more details on python machine learning libraries .

Finally , We have Python Anaconda Packages in which we need not to install these packages separately , One Anaconda for all solutions .

5. Feel the Magic of Anaconda with R and Scala –

If you are R programmer or Scala Developer and love to code with Anaconda packages , You can also access it . If I say Scala , I directly or indirectly touch java . Different communities have different view on Python Vs R for data science . It is a open ended question .As per my opinion ” IT IS PROJECT BASED” ,Frankly speaking , there are so many factors to effect this decision , By the way I have more experience on coding with python . So I usually go with python . Specially in the case of Machine Learning , Your platform /language selection is most important . Here are some tips to choose best machine learning language .

Usually people get some confusing conception in pip and conda package manager . If you want to understand the difference between pip python package manager and conda package manager , Please read this .

End Notes –

Till Now , I have told only advantages . Lets have some discussion on its dis-advantages . Suppose you want to update a single package , You have to update whole repository . This will consume lot of time . This is one the major dis-advantage I personally find . If you want to dig more information about command related to package management in Anaconda you can go through Managing Packages with Anaconda .

I think , this article will help you understand the basics of Python Anaconda Packages .If you find this article helpful and you want to stay in touch with Data Science updates . Please subscribe us . We love to make informative article for you . You can also add your views in comment box .

Data Science Learner Team

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