For example, if you open a file explorer, it may use System Python under the hood to list files and folders. This Python installation is called System Python, and it means that this executable is used by our Operating System to do many things.
Python is just an executable binary in our system. If you get a better understanding of virtual environments we have accomplished our goal.Īs you can see, the output of this command says that Python is already installed in our system, specifically in the location /usr/bin/python3. The goal of this post is to end this madness once for all. You would be surprised how many excellent professionals, even with 5+ years of experience still struggle with chaotic, corrupted, and barely usable Python installations because of that.
We also tried other alternatives and always go back to conda because it is the only, let's say, full featured solution on the market.īased on my experience of more than 6 years doing Data Science, conda (and virtual environments in general) is a tool that is often not well understood. We use it for both development and production purposes and we strongly believe that conda stands out from other alternatives like virtualenv, poetry, pyenv or pipenv. This post is about conda, the tool we use to install and manage Python and its libraries in our systems. This is the first post of the WhiteBox toolkit series, where we will tell you more about the tools we use in our everyday job, in high detail. Now if you want to install any particular package, through pip in conda environment, we can do it like −Ībove we have installed opencv package through pip in conda environment.There are two types of Data Scientists, those who took the time to master conda and those who don't (and cry at the corners because of that). We can install pip in our existing conda environment by simply giving the command − conda install pipĪnd your screen will be shown an output something like − Method 3 − If the package is not available in our conda environment or through anaconda navigator, we can find and install the package with another package manager like pip. To install a specific package such as opencv into your existing environment “myenv”(in case you have a virtual environment to install project specific packages). Note − It is recommended to install all required packages at once so that all of the dependencies are installed at once. We can install multiple packages at once, such as OpenCV and tensorflow − conda install opencv tensorflow To install specific a specific version of a opencv package − conda install opencv-3.4.2 Method 2 − Another way of installing packages is by the use of terminal or an Anaconda Prompt − conda install opencvĪbove command will install OpenCV package into your current environment.
Let's suppose tensorflow packages are not installed in your computer, I can simply search the required package(like tensorflow), select it and click on apply to install it. It is very easy to install any package through anaconda navigator, simply search the required package, select package and click on apply to install it. Go to Environments tab just below the Home tab and from there we can check what all packages are installed and what is not.
Once “Ananconda Navigator” is opened, home page will look something like − Method 1 − One common approach is to use the “Anaconda Navigator” to add packages to our anaconda environment. There are multiple ways by which we can add packages to our existing anaconda environment.