![]() Through reference to the library, the development of different fields of business can be realized. The prerequisite for realizing its powerful functions is that Python has a large number of standard libraries and third-party libraries with relatively complete functions. In addition, the power of Python lies in its wide range of applications, covering artificial intelligence, scientific computing, web development, system operation and maintenance, big data and cloud computing, finance, game development, etc. When the code written by it runs on different platforms, it is almost impossible Major changes are required, and users all benefit from its convenience. It can be used in Linux, macOS, and Windows systems. Its use has the characteristics of cross-platform. One that is running Python 2.7 and another which is running Python 3.6.Python is an object-oriented interpreted computer programming language. Having gotten some variety of Conda installed you should make at least two environments. Your instructor can help with getting issues resolved on any of the above platforms but most demonstrations will likely be based in the command line interface and there are several things that can only be done in the command line interface. Documentation for that can be found here. ![]() If you installed Anaconda you can use Anaconda Navigator, the graphical interface to manage Anaconda. If you did not install Conda in your PATH you will want to do these tutorials via the Anaconda command prompt. Be aware that there may be some minor differences between operating systems and how you chose to install Conda. This tutorial walks you through the basics of creating and managing environments. Using Condaīoth Miniconda and Anaconda will install Conda. While it can be very convenient it can be very difficult to debug when things go wrong. It can be found here Unless you are sure you know what you are doing, I would avoid adding it to the PATH. As a side note the link to the download in the Anaconda instructions seems broken. Installing Anaconda or Minicondaįollow the instructions for the regular installation for your operating system when installing Anaconda or Miniconda. ![]() Use this option if you want more control over what packages are installed. It lets you still do all the package and Python version management but it does not come with the long list of preinstalled packages. Miniconda is the smaller alternative to Anaconda. ![]() In general I would probably recommend this route. Anaconda also includes a GUI which can be nice if you are not a big fan of the command line. It takes up a little more space and you might run into a little more hassle if you need specific versions of those included packages. It also includes around 100 of the most common packages used in data science. It lets you set up environments which have specific packages and Python versions installed. Anaconda is a software package that helps deal with these exact issues and while it is not the only option, it has gained a lot of favor in the data science field. These sorts of issues can be exceptionally frustrating to deal with. You may have also had issues with one program requiring a particular version of a library and a different program requiring a different version of that same library. At this point in your experience as a programmer you have probably run into issues on more than one occasion with having the right version of Python installed or in use.
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