Downloading the Python Library
Python is a widely used programming language that may be put to use for a variety of purposes, including data analysis, web development, and machine learning. The widespread availability of libraries that may enhance its capability is one of the factors that has contributed to its widespread use. These libraries, which are often referred to as modules, include code that has already been created and is readily importable and used in your applications. The process of downloading and installing Python libraries is going to be covered in this post.
PIP, which stands for Python’s package installer, is the method that is used the most often for downloading and installing Python libraries. Installing, upgrading, and removing Python packages are all possible via the use of the Pip command-line tool. It is a part of the standard library beginning with Python version 2.7.9 and continuing through into later versions. To begin using pip, you must first open a command prompt or terminal and enter the following:
“pip install [library name]”
(without the brackets).
Downloading the NumPy library, which is a library for numerical computation, would need the following steps, for instance:
“pip install numpy”
at the prompt for giving commands. After the execution of this command, pip will download and install the library on your system.
Using Anaconda, a version of Python that comes bundled with a package manager known as conda, is yet another method that may be used in order to obtain and install Python libraries. Conda is a package manager that works across several platforms and has the ability to install, update, and delete packages. Installing a library using conda is as follows:
“conda install [library name]”
at the prompt for entering commands or the terminal. For instance, in order to install the Matplotlib library, which is a library for generating plots and charts, you would follow these steps:
“conda install matplotlib”
at the prompt for giving commands. Conda will then download and install the library on your system after you have executed this command.
It is important to keep in mind that pip and conda are not incompatible with one another. You are free to combine the two uses. Conda has the ability to install Python as well as other packages, while pip is limited to installing just Python packages. Conda also has superior capabilities when it comes to handling dependencies. It enables the creation of sandboxed environments containing certain versions of Python and packages, hence preventing conflicts between different packages from occurring. You may make use of the virtualenv module in Python 3.8 in order to set up a separate environment that you can refer to as “myenv.”
“conda create -n myenv python=3.8”
The environment must then be made active.
“conda activate myenv”
pip or apt-get may then be used to install the necessary packages.
Checking for installed packages
It is highly advised that before installing any library, you first check to see whether it is already present on your system. You are free to utilize the
to examine the list of components that were installed
Because of this, you won’t need to go through the trouble of reinstalling products that you already own. For instance, if you want to determine whether or not numpy has been installed on your computer, you may use the command line to execute “pip freeze” or “conda list,” and if numpy has been installed, it will be shown in the results.
Installing the source code manually is yet another method that may be used to acquire and install Python libraries. If the library you require is not accessible via pip or conda, or if you need a particular version of the library that is not available through those package managers, then this technique may be helpful. To manually install a library, you must first download the source code, then unzip it, and last execute the installation program.
“python setup.py install”
at the prompt for entering commands or the terminal. Using this command will install the library in the directory that contains your Python installation. For instance, if you want to install the library named “mylibrary” that you downloaded, you may go to the folder containing the library and type “python setup.py install” at the command prompt while in the folder containing the library.
Compatibility across different versions of a library is an additional critical component of the installation process. It is of the utmost importance to check that the version of the library that is being installed is compatible with the version of Python that is currently being used. There is a possibility that earlier versions of Python may not support some libraries, and that newer versions of Python will not support other libraries. You can learn which versions of Python are supported by the library by checking out the documentation for the library. Consider the following scenario: you are running Python version 3.6, but you wish to install the “mylibrary” library, which is only compatible with Python versions 3.8 and above. In such situation, you will be required to update your version of Python or search for a library that is compatible.
It’s also important to keep in mind that different libraries might be dependent on one another in various ways. For instance, if you are installing a library on your system that makes use of NumPy, you will need to ensure that NumPy is already installed on your computer. Pip and conda have the ability to handle these dependencies automatically; however, if you are installing a library manually, you are responsible for ensuring that all of the library’s needs are met before installing the library. If you wish to install the library “mylibrary,” which relies on NumPy, for instance, you may examine the documentation to see whether it specifies that NumPy already be installed. If it does, you can install NumPy first using pip or conda, and then install mylibrary thereafter.