The project we are working on is likely to have many dependencies that need to be installed . These dependencies facilitate many tasks in the project . However, especially when dealing with multiple projects , We need to be very careful .
Like any other technology , Software packages or programming languages are also improving . Therefore, a new version is being launched .
Different projects may require different versions of packages or software . for example , We may have a project that needs Python2.7, Another project requires Python3.6. As the number of projects and dependencies increases , It is difficult to track and deal with these differences .
One way to overcome this problem is to use virtual environments . They can be regarded as the bounding box of the software package . We can develop a project in a virtual environment , And install all dependencies specific to the project . What we have in the virtual environment is not affected by the global changes of the machine .
Python There are many virtual environment tools , Such as pipenv、virtualenv、venv etc. . In this paper , We will discuss some uses virtualenv and pipenv An example of , To be familiar with the concept of virtual environment and its working mode .
Let's start with virtualenv Start . use first python Package installer （pip） Install it from the terminal .
$ pip install virtualenv
Create a sample project file as the working directory .
$ mkdir demoproject
$ cd demoproject
Now in demoproject Directory . We will use the following command to create a virtual environment .
$ virtualenv venv_demo
It was created . We can run ls Command to view the files in the current working directory .
$ ls
venv_demo
The next step is to activate the virtual environment .
$ source venv_demo/bin/activate
Once the virtual environment is activated , Its name will be displayed in the terminal , As shown below ：
Now you can install the package .
$ python -m pip install pandas
We have now installed pandas.freeze The command displays a list of installed packages .
$ python -m pip freeze
numpy==1.19.4
pandas==1.1.5
python-dateutil==2.8.1
pytz==2020.5
six==1.15.0
NumPy Also installed , Because it is pandas Dependence .pandas The installed version of is 1.1.5. We can specify the required version when installing the software package .
$ python -m pip install pandas==1.0.5
If you only want to check the installed version of a specific package , Please put freeze Command and grep Use it together ：
$ pip freeze | grep pandas
pandas==1.0.5
We can also install several software packages saved in text files . This is better than installing dependencies one by one , Especially when there are multiple dependencies .
$ python -m pip install -r requirements.txt
In order to exit the virtual environment , We use deactivate command .
$ deactivate
The next tool we will find is pipenv, It can be used pip install ：
$ pip install pipenv
Use pipenv Create a new virtual environment .
$ pipenv install --python=/usr/bin/python3.6
Pipenv Allow dependencies to be installed when creating virtual environments . for example , I can add pandas, Then you can create the installation pandas Virtual environment for .
function shell Command to activate the virtual environment .
$ pipenv shell
We are now in a virtual environment . Also install this pandas Well .
$ pipenv install pandas
graph The command displays a detailed overview of the installed packages .
$ pipenv graph
pandas==1.1.5
- numpy [required: >=1.15.4, installed: 1.19.4]
- python-dateutil [required: >=2.7.3, installed: 2.8.1]
- six [required: >=1.5, installed: 1.15.0]
- pytz [required: >=2017.2, installed: 2020.5]
We can use uninstall Command to uninstall a specific package or all packages in the virtual environment .
$ pipenv uninstall pandas
The following command will uninstall all packages .
$ pipenv uninstall -all
type “exit” Command to exit the virtual environment .
Virtual environment is a good tool for managing multiple projects at the same time . There are many software packages and libraries that can be updated quickly . therefore , Trying to update manually is inefficient .
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