The Quantra portal contains all the recommended packages for quant analysis and algo trading. You can use this article to set up your local Python environment which is similar to the Quantra portal. But there can be occasions where some libraries might become incompatible with each other due to an update in one library. These libraries are updated time and again to make sure everything is working smoothly. One of the advantages of Python is that there are a host of libraries that the user can install on their system so that they don't have to code from scratch. (Note: If you do this, you need to replace “ username” in the example with your username and “ u” with the first letter of your username.Python is a versatile programming language that is comparatively easier to learn and program. It provides a lightweight virtual environment and is very straightforward to use.įor example, if we want to use the venv module on Dardel, we can first load the anaconda module, and then create a virtual environment in the home folder as follows. The venv module is a standard Python module that has been available since Python 3.3. This blog post will briefly introduce two ways of creating and managing a Python virtual environment: venv or conda. With the help of a virtual environment, we can have different Python site directories for different projects and have those site directories isolated from each other and from the system site directory. A Python package installed in this way can have only one version, and it is therefore not possible to work with two or more projects that have conflicting requirements regarding the versions of a certain Python package. Or in the so-called Python user base, which is usually in the “ $HOME/.local” folder. $ python -c 'import site print(site.getsitepackages())' Without a virtual environment, Python packages are installed either in the system site directory, which can be located via the following command: A solution to this conflict is to separate the packages for different projects or purposes with the help of a so-called “virtual environment”.Ī Python virtual environment is an isolated run-time environment that makes it possible to install and execute Python packages without interfering with the outside world. For example, project A may require version 1.0 of a certain package, while project B may require version 2.0 of the same package. In the scenario of working on multiple projects, it is not uncommon that different projects have conflicting requirements in terms of packages. We therefore need to install those packages based on the specific requirements of every project. When we use Python in our work or personal projects, it is often necessary to use a number of packages that are not distributed as standard Python libraries.
Note: This post has been updated to reflect the modules on Dardel (December 2021).
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