To view existing dependency packages in a Notebook, you typically use a package manager that is specific to the programming language you are using. For example, if you are working in a Python Notebook, you can use pip or conda to manage your packages.
To view installed packages using pip, you would run:
!pip list
Or, if you are using conda, you would run:
!conda list
These commands will display a list of all the installed packages along with their versions.
To install a third-party library, you can use pip or conda as well. For instance, to install the requests library using pip, you would execute:
!pip install requests
Or, using conda, you might run:
!conda install -c anaconda requests
This command installs the requests library, which is commonly used for making HTTP requests in Python.
If you are working within a cloud environment like Tencent Cloud, you might be using services like Tencent Cloud Container Service or Tencent Cloud Virtual Machine, where you can manage your dependencies within a container or a virtual machine. For example, you could create a Dockerfile that specifies the dependencies you need and then use Tencent Cloud's container services to deploy your application with those dependencies included.
Additionally, Tencent Cloud offers a notebook service called Tencent Cloud AI Notebook, which provides a managed Jupyter notebook environment. Within this service, you can manage your packages using pip or conda as described above, and you can also leverage Tencent Cloud's extensive library of pre-installed AI and data science packages to accelerate your development process.