Introduction
This is a reference post.
Download Mac OS X 64-bit/32-bit installer; Python 2.7.7rc1 - May 17, 2014. Download Mac OS X 32-bit i386/PPC installer; Download Mac OS X 64-bit/32-bit installer; Python 3.4.1rc1 - May 5, 2014. Download Mac OS X 32-bit i386/PPC installer; Download Mac OS X 64-bit/32-bit installer; Python 3.4.0rc3 - March 10, 2014. Download Mac OS X 32-bit i386. Anaconda Individual Edition is the world’s most popular Python distribution platform with over 20 million users worldwide. You can trust in our long-term commitment to supporting the Anaconda open-source ecosystem, the platform of choice for Python data science.
Installing Anaconda using a graphical installer is probably the easiest way to install Anaconda. 1 ‒ Go to the Anaconda Website and choose a Python 3.x graphical installer (A) or a Python 2.x graphical installer (B). If you aren’t sure which Python version you want to install, choose Python 3. Do not choose both. Techdeidesmo / notebooks / SmartDriverUpdater50187CrackLicenseKeyFreeDownloadWindowMacOSMacOSX. To install Anaconda, we go to anaconda.com, We find the Download link at the top, under Products where we choose the Individual Edition. We scroll down to find our platform, and select the 64-bit Anaconda graphical installer, which is currently at version 3.8. Any later version will also work fine.
I've realized that I'm explaining how to install Anaconda over and over again in most of my posts, often messing up with the instructions!
So to make it easier for me and, most importantly, safer for you, I'm summarizing the instructions in this short post, and I will refer to it from now on.
I'll present you with two installation methods for Anaconda:
- Graphical installation of Anaconda: recommended if you are new to Anaconda.
- Command line installation of Miniconda: recommended if you want a fast and light install, and if you want to work with the command line.
What is Anaconda?
As stated on Anaconda's website:
With over 6 million users, the open source Anaconda Distribution is the fastest and easiest way to do Python and R data science and machine learning on Linux, Windows, and Mac OS X. It's the industry standard for developing, testing, and training on a single machine.
In a nutshell, the anaconda team maintains a repository of more than 1400 data science packages, all compatible, and provides tools to install a version of python and these packages at the push of a button, and under five minutes.
In particular, Anaconda contains:
- scikit-learn : one of leading machine-learning toolkits for python. It will provide an easy access to the handwritten digits dataset, and allow us to define and train our neural network in a few lines of code
- numpy : core package providing powerful tools to manipulate data arrays, such as our digit images
- matplotlib : visualization tools, essential to check what we are doing
- jupyter : the web server that will allow you to follow this tutorial and run the code directly in your web browser.
- and much, much more!
Graphical installation of Anaconda
Download anaconda for your system:
- Choose either the python 3.X or the python 2.X version. Please make sure to chose the version specified in the tutorial you want to run. If you don't know, take the python 3.X version
- If you're using Windows or Linux, make sure to pick the 64 bit installer if you have a 64 bit system.
Then run the installer, and finally start the Anaconda Navigator. On windows, you can find it by clicking the windows start button, and typing anaconda.
In the Anaconda Navigator, you can click on the Environments tab and then select the base (root) environment to see which packages are installed, and to install additional packages. You can also create new environments as shown below.
Finally, to start using it, go to the Home tab and launch the jupyter notebook. This will redirect you to the jupyter notebook main page in your browser.
You can now create and load jupyter notebooks.
You're done!
Command line installation of Miniconda
Download Miniconda for your system:
- Choose either the python 3.X or the python 2.X version. Please make sure to chose the version specified in the tutorial you want to run. If you don't know, take the python 3.X version
- If you're using Windows or Linux, make sure to pick the 64 bit installer if you have a 64 bit system.
On linux, you can download the bash installer from the command line with wget like this (replace with the link you need from the Miniconda page):
On the mac, you can download it with curl:
Anaconda For Mac Os
After this is done, open a bash terminal and type the following (use the name of the installer that you have just downloaded)
Answer all questions, and you're done with the installation.
Log out from your machine, and log in again (or start a login shell)
Then, you can use the command line to:
- create conda environments
- select the version of python you want
- install the packages you need.
I usually do everything in one go like this:
This creates a new environment called testenv based on python 3.7, and with the ipython package.
You can then activate the environment, and test that things are as you expect:
You see that python is indeed version 3.7, and that ipython is there. You can start ipython.
After Miniconda is installed, don't hesitate to create new environments not to mix things up. For example, I have a dozen environments: a python 3.X environment for this blog, a python 2.X one for some tasks at work, another one for activities related to OpenCV... And every time I write an article for this blog, I create a fresh environment to test the installation recipe, before deleting it right away.
Whether you’re a big, small or medium enterprise, Anaconda will support your organization. As a free and open-source distribution of Python and R programming language, it’s aim is to easily scale a single user on one laptop to thousands of machines. If you’re looking for a hassle-free data science platform, this is the one for you.
Extensive packages
Anaconda Prompt Mac
Anaconda is leading the way for innovative data science platforms for enterprises of all sizes.
Anaconda provides you with more than 1,500 packages in its distribution. In it you will find the Anaconda navigator (a graphical alternative to command line interface), Conda package, virtual environment manager, and GUI. What makes Conda different from other PIP package managers is how package dependencies are managed. PIP installs Python package dependencies, even if they’re in conflict with other packages you’ve already installed. So, for example, a program can suddenly stop working when you’re installing a different package with a different version of the NumPy library. Everything will appear to work but, you data will produce different results because you didn’t install PIP in the same order. This is where Conda comes in. It analyzes your current environment and installations. This includes version limitations, dependencies, and incompatibility. As an open source package, it can be individually installed from the Anaconda repository, Anaconda Cloud or even the conda install command.
You can even create and share custom packages using the conda build command. The developers will then compile and build all the packages in the Anaconda repository, providing binaries for Windows, Linux and MacOS. Basically, you won’t worry about installing anything because Conda knows everything that’s been installed in your computer.
Extend your reach with Anaconda Navigator
The built in graphical user interface or GUI allows you to launch applications while managing Conda packages, environments and channels. This means the GUI will complete the process of installing packages without asking for a command-line command. It even includes these applications by default: JupyterLab & Jupyter Notebook / QtConsole / Spyder / Glueviz / Orange / RStudio / Visual Studio Code.
Where can you run this program?
Anaconda 2019.07 has these system requirements:
- Operating system: Windows 7 or newer, 64-bit macOS 10.10+, or Linux, including Ubuntu, RedHat, CentOS 6+.
- System architecture: Windows- 64-bit x86, 32-bit x86; MacOS- 64-bit x86; Linux- 64-bit x86, 64-bit Power8/Power9.
- 5 GB disk space or more.
Anaconda developers recommends you to install Anaconda for the local user so you won’t need administrator permissions. Or, you can opt to install Anaconda system wide, which does require administrator permissions.
Is there a better alternative?
If you’re looking for simple Python-dedicated environment, then you need PyCharm. Targeted specifically for Python programmers, this integrated development environment is filled with programming tools that can impress both new and experienced developers. It provides all the tools in a centralized system so you can increase your efficiency and effectiveness. Features like code analysis, graphical debugger, and unit tester helps you integrate Python programs with version control systems. In fact, every single output you make will be capable of web development from different web frameworks like Django, web2py, and Flask. It offers automated tools like code refactorings, PEP8 checks, and testing assistance to create your code, but what stands out the most is Smart Assistance. It fixes any of your errors or complete portions of your code. With PyCharm, you can expect a neat and maintainable code.
Our take
Anaconda’s host of innovative options makes it the best data science platform for all enterprises. By offering superior collaboration tools, scalability, and security, you never have to worry about gathering big data again.
Should you download it?
If you have experience with other package management and deployment programs, then make the big switch by downloading Anaconda.
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