Skip to content
This repository has been archived by the owner on Aug 22, 2023. It is now read-only.

Latest commit

 

History

History
254 lines (173 loc) · 11.7 KB

GETTING_STARTED.md

File metadata and controls

254 lines (173 loc) · 11.7 KB
Raw

Decide On Development Environment

Introduction

The cookie provides the ability to develop and manage the Nautobot server locally (with supporting services being Dockerized) or using only Docker containers to manage Nautobot. The main difference between the two environments is the ability to debug and use pdb when developing locally. Debugging with pdb within the Docker container is more complicated, but can still be accomplished by either exec'ing into the container or attaching your IDE to the container and running the Nautobot service manually within the container.

The upside to having the Nautobot service handled by Docker rather than locally is that you do not have to manage the Nautobot server and the Docker logs provide the majority information you will need to help troubleshoot while getting started quickly and not requiring you to perform several manual steps to get started and remember to have the Nautobot server running or having it run in a separate terminal while you develop. Ultimately, the decision is yours as to how you want to develop, but it was agreed it would be a good idea to provide pros and cons for each development environment.

The local environment still uses Docker containers for the supporting services (Postgres, Redis, and Celery), but the Nautobot server is handled locally by you, the developer.

Follow the directions below for the specific development environment that you choose.

Poetry

Poetry is used in lieu of the "virtualenv" commands and is used for either environment. The virtual environment will provide most of the Python packages required to manage the development environment such as Invoke, but see the Local Development Environment section to see how to install Nautobot if you're going to be developing locally. To get started, run the following commands:

➜ poetry install
➜ poetry shell

The first command creates the virtual environment through Poetry and installs all relevant dependencies, as outlined in the pyproject.toml file.

The second command puts your shell session into the virtual environment, so all commands ran going forward are from within the virtual environment. (This is similar to running the source venv/bin/activate command with virtualenvs).

Full Docker Development Environment

Invoke

The beauty of Invoke is that the Cookiecutter template provides several simple CLI commands to get developing fast. You'll use a few invoke commands to get your environment up and running.### Invoke (Fully Automated) - Local Dev Environment Setup With Mattermost

The baked cookie supports the automated setup of a local Mattermost instance to quickly test your chatops plugin. All settings and credentials will be pre-configured, and a separate Docker container will run Mattermost in the background, accessible at http://localhost:8065

To setup this environment, after creating the creds.env file and running poetry lock run the following invoke commands from the plugin folder, using the optional -m or --mattermost flags:

➜ poetry shell             # Activate poetry environment
➜ invoke build             # Build the containers
➜ invoke setup-mattermost  # Setup the Mattermost container and configure all required settings
➜ invoke start             # Start all Nautobot containers

There is no additional setup needed. After a few seconds, you can test this deployment is working properly as follows:

Mattermost

  • Go to http://localhost:8065/automationteam/messages/@ntcbot
  • Log in using the default admin/Nautobot123!! credentials.
    • These are set in development/development.env, and may have been changed.
  • Send a direct message to @ntcbot. You should be able to run an example command /panorama hello-world test

Nautobot

  • Got to http://localhost:8080
  • Log in using the default admin/admin credentials.
    • These are set in development/creds.env, and may have been changed.

You can see the Mattermost token and command are already configured.### Real-Time Updates? How Cool

Your environment should now be fully setup, all necessary Docker containers are created and running, and you're logged into Nautobot in your web browser. Now what?

Now you can start developing your plugin in the folder generated for you by Cookiecutter.

Adding new chatbot commands

After updating the nautobot_plugin_chatops_panorama/worker.py file and saving it, the backend Django service should auto-reload with your changes. If it doesn't, or a bug in the code caused it to crash, you can quickly relaunch it from your poetry environment with invoke restart.

Docker Magic

The magic here is the root directory is mounted inside your Docker containers when built and ran, so any changes made to the files in here are directly updated to the Nautobot plugin code running in Docker. This means that as you modify the code in your nautobot-plugin folder (or whatever you named your plugin when generating it via Cookiecutter), the changes will be instantly updated in Nautobot.

NOTE: There are a few exceptions to this, as outlined in the section To Rebuild or Not To Rebuild.

The backend Django process is setup to automatically reload itself (it only takes a couple of seconds) every time a file is updated (saved). So for example, if you were to update one of the files like tables.py, then save it, the changes will be visible right away in the web browser!

NOTE: You may get connection refused while Django reloads, but it should be refreshed fairly quickly.

Docker Logs

When trying to debug an issue, one helpful thing you can look at are the logs within the Docker containers.

➜ docker logs <name of container> -f

NOTE: The -f tag will keep the logs open, and output them in realtime as they are generated.

So for example, our plugin is named nautobot-plugin-chatops-panorama, the command would most likely be docker logs nautobot_plugin_chatops_panorama_nautobot_1 -f. You can find the name of all running containers via docker ps.

If you want to view the logs specific to the worker container, simply use the name of that container instead.

To Rebuild or Not to Rebuild

Most of the time, you will not need to rebuild your images. Simply running invoke start and invoke stop is enough to keep your environment going.

However there are a couple of instances when you will want to.

Updating Environment Variables

To add environment variables to your containers, thus allowing Nautobot to use them, you will update/add them in the development/dev.env file. However, doing so is considered updating the underlying container shell, instead of Django (which auto restarts itself on changes).

To get new environment variables to take effect, you will need stop any running images, rebuild the images, then restart them. This can easily be done with 3 commands:

➜ invoke stop
➜ invoke build
➜ invoke start

Once completed, the new/updated environment variables should now be live.

Installing Additional Python Packages

If you want your plugin to leverage another available Nautobot plugin or another Python package, you can easily add them into your Docker environment.

➜ poetry shell
➜ poetry add netutils

Once the dependencies are resolved, stop the existing containers, rebuild the Docker image, and then start all containers again.

➜ invoke stop
➜ invoke build
➜ invoke start

Installing Additional Nautobot Plugins

Let's say for example you want the new plugin you're creating to integrate into Slack. To do this, you will want to integrate into the existing Nautobot ChatOps Plugin.

➜ poetry shell
➜ poetry add nautobot-chatops-plugin

Once you activate the virtual environment via Poetry, you then tell Poetry to install the new plugin.

Before you continue, you'll need to update the file development/nautobot_config.py accordingly with the name of the new plugin under PLUGINS and any relevant settings as necessary for the plugin under PLUGINS_CONFIG. Since you're modifying the underlying OS (not just Django files), you need to rebuild the image. This is a similar process to updating environment variables, which was explained earlier.

➜ invoke stop
➜ invoke build
➜ invoke start

Once the containers are up and running, you should now see the new plugin installed in your Nautobot instance.

You can even launch an ngrok service locally on your laptop, pointing to port 8080 (such as for chatops development), and it will point traffic directly to your Docker images. How cool!

Updating Python Version

To update the Python version, you can update it within tasks.py.

namespace = Collection("nautobot_plugin_chatops_panorama")
namespace.configure(
    {
        "nautobot_plugin_chatops_panorama": {
            ...
            "python_ver": "3.7",
	    ...
        }
    }
)

Or set the INVOKE_NAUTOBOT_PLUGIN_CHATOPS_PANORAMA_PYTHON_VER variable

Updating Nautobot Version

To update the Python version, you can update it within tasks.py.

namespace = Collection("nautobot_plugin_chatops_panorama")
namespace.configure(
    {
        "nautobot_plugin_chatops_panorama": {
            ...
            "nautobot_ver": "1.0.2",
	    ...
        }
    }
)

Or set the INVOKE_NAUTOBOT_PLUGIN_CHATOPS_PANORAMA_NAUTOBOT_VER variable

Local Development Environment

Refer back to the README for developing locally.

Other Miscellaneous Commands To Know

Python Shell

To drop into a Django shell for Nautobot (in the Docker container) run:

➜ invoke nbshell

This is the same as running:

➜ invoke cli
➜ nautobot-server nbshell

Tests

To run tests against your code, you can run all of the tests that in CI runs against any new PR with:

➜ invoke tests

To run an individual test, you can run any or all of the following:

➜ invoke unittest
➜ invoke bandit
➜ invoke black
➜ invoke flake8
➜ invoke pydocstyle
➜ invoke pylint

Home