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ST-1466 Rename files to conform to RFC-1123

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.. _about:
Follow us on social media
=========================
......
.. _about:
SAFe for SKA
************
Coming soon.
.. _about:
The SKA Organisation
********************
Coming soon...
.. _about:
Agile teams and responsibilities
--------------------------------
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.. _contribute:
Contribute to the developer portal
**********************************
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.. _devenv_setup:
.. _devenv-setup:
Configuring your development environment
****************************************
......@@ -9,18 +9,12 @@ Python and Tango development
A completely configured development environment can be set up very easily. This will include
TANGO, PyTANGO, docker and properly configured IDEs.
- :doc:`devenv_setup/tango-devenv-setup`
PyCharm and VSCode are two IDEs that can be configured to support python and
PyTANGO development activities. You will find detailed instructions and how-tos at:
- :doc:`devenv_setup/pycharm/pycharm`
- :doc:`devenv_setup/vscode/vscode`
.. toctree::
:maxdepth: 1
devenv_setup/tango-devenv-setup
devenv_setup/pycharm/pycharm
devenv_setup/vscode/vscode
devenv-setup/tango-devenv-setup
devenv-setup/pycharm/pycharm
devenv-setup/vscode/vscode
......@@ -94,12 +94,12 @@ defined. Set the environment variables to look like this:
.. _`configure Docker Compose as a remote interpreter`: https://www.jetbrains.com/help/pycharm/using-docker-compose-as-a-remote-interpreter.html#docker-compose-remote
.. image:: docker_compose_environment_variables.png
.. image:: docker-compose-environment-variables.png
:align: center
The final Configure Remote Python Interpreter dialog should look like this:
.. image:: docker_compose_remote_interpreter.png
.. image:: docker-compose-remote-interpreter.png
:align: center
Click 'OK' to apply your changes.
......@@ -126,7 +126,7 @@ menu that appears, select Python to add a new Python execution configuration. In
The final Run/Debug dialog should look like this:
.. image:: docker_compose_run_configuration.png
.. image:: docker-compose-run-configuration.png
:align: center
Press OK to apply your changes.
......@@ -135,7 +135,7 @@ From the main menu, choose Run | Run... and select the configuration that you ju
The PowerSupply device will launch alongside the partner containers defined in docker-compose.yml. PyCharm's Run
panel will display output like this, showing the device is executing and ready to accept requests.
.. image:: docker_compose_run_powersupply.png
.. image:: docker-compose-run-powersupply.png
:align: center
......@@ -206,7 +206,7 @@ From the main menu, choose Run | Debug... and select the PowerSupply run configu
will be launched and the PyCharm debugger attached to the session. The Debug panel of PyCharm should look similar to
this:
.. image:: docker_compose_debug_panel.png
.. image:: docker-compose-debug-panel.png
:align: center
Returning to the interactive session, run the unit tests that exercise the live Tango device. For the tango-example
......@@ -259,7 +259,7 @@ Restart the debugging configuration for the code change to take effect and re-ex
session. This time, the breakpoint is respected and execution is frozen, allowing program state to be examined in
PyCharm. The debug panel in PyCharm will look something like this, showing that execution is frozen:
.. image:: docker_compose_working_breakpoint.png
.. image:: docker-compose-working-breakpoint.png
:align: center
......@@ -271,7 +271,7 @@ Troubleshooting
If you see an error message like the one below, then the device is unregistered and needs to be registered manually.
Follow the steps in `Registering the device server`_.
.. image:: device_unregistered.png
.. image:: device-unregistered.png
:align: center
......@@ -280,7 +280,7 @@ Troubleshooting
If you see an error message like the one below, then you forgot to define the environment variables for the
remote interpreter. Edit the variables section in your PyCharm docker-compose configuration and try again.
.. image:: docker_compose_environment_error.png
.. image:: docker-compose-environment-error.png
:align: center
......@@ -43,7 +43,7 @@ you've downloaded.
#. In the Directory field, specify the path where the folder for your local Git repository will be created into which
the remote repository will be cloned. The dialog should now look similar to this:
.. image:: clone_repository.png
.. image:: clone-repository.png
:align: center
4. Click Clone, then click Yes in the subsequent confirmation dialog to create a PyCharm project based on the sources
......@@ -139,12 +139,12 @@ created. The 'Add Python Interpreter' dialog should look similar to this:
.. _`configure Docker as a remote interpreter`: https://www.jetbrains.com/help/pycharm/using-docker-as-a-remote-interpreter.html#config-docker
.. image:: add_python_interpreter.png
.. image:: add-python-interpreter.png
:align: center
As a result, the Python interpreter Preferences dialog should look something like this:
.. image:: preferences_docker_interpreter.png
.. image:: preferences-docker-interpreter.png
:align: center
Click 'OK' to apply your changes.
......@@ -185,7 +185,7 @@ From the main menu, choose Run | Edit Configurations... and click on the '+' but
menu that appears, select Python tests | pytest to add a new pytest test configuration. The menu selection looks like
this:
.. image:: add_new_pytest_configuration.png
.. image:: add-new-pytest-configuration.png
:align: center
#. Change the Target radio button to 'Module Name'. Click '...' to select the target, choosing
......@@ -199,7 +199,7 @@ this:
The configuration dialog should look like similar to this:
.. image:: devicetestcontext_configuration.png
.. image:: devicetestcontext-configuration.png
:align: center
Click 'OK' to accept your changes.
......@@ -207,7 +207,7 @@ Click 'OK' to accept your changes.
From the main menu, choose Run | Run..., then from the Run dialog that opens, select the configuration you just created.
The unit tests will execute, with the results displayed in PyCharm's Run panel. The results will look like this:
.. image:: devicetestcontext_test_results.png
.. image:: devicetestcontext-test-results.png
:align: center
......
.. _pycharm:
PyCharm
*******
......@@ -13,8 +15,8 @@ be downloaded from the `PyCharm download page`_.
:caption: Development tools
:hidden:
docker_configuration
docker_compose_configuration
docker-configuration
docker-compose-configuration
- :doc:`docker_configuration`
- :doc:`docker_compose_configuration`
- :doc:`docker-configuration`
- :doc:`docker-compose-configuration`
.. _devenv-setup
Tango Development Environment set up
------------------------------------
......
[[source]]
url = "https://pypi.python.org/simple"
verify_ssl = true
name = "pypi"
[packages]
[dev-packages]
[requires]
python_version = "3.8"
......@@ -73,7 +73,7 @@ environment which will we will later connect to VSCode.
Start a terminal session inside VSCode:
.. image:: vscode_terminal.png
.. image:: vscode-terminal.png
:align: center
......@@ -81,7 +81,7 @@ On the terminal tab build the image by typing ``make build``. *This step is
optional since the ``make interactive`` command described bellow, takes
care of this task if needed*:
.. image:: vscode_build.png
.. image:: vscode-build.png
:align: center
......@@ -94,14 +94,14 @@ in interactive mode and are ready to debug.
* On the terminal tab start the container interactively with
``make interactive``:
.. image:: vscode_interactive.png
.. image:: vscode-interactive.png
:align: center
* Debug a particular file using the ``vscode-debug.sh`` utility inside
the docker image. For instance
``./vscode-debug.sh powersupply/powersupply.py``:
.. image:: vscode_connect.png
.. image:: vscode-connect.png
:align: center
Notice that the terminal shell now shows a message stating that it is waiting
......@@ -115,13 +115,13 @@ for the debugger attachment:
* You can now set breakpoints inside the VSCode editor (or use previously set
ones):
.. image:: vscode_breakpoints.png
.. image:: vscode-breakpoints.png
:align: center
* Start the debugger from whitin VSCode by pressing ``F5`` or the *debug*
button under the debug tab:
.. image:: vscode_debug.png
.. image:: vscode-debug.png
:align: center
......
.. _vscode:
Visual Studio Code
******************
......@@ -14,8 +16,8 @@ Visual Studio Code is an open source project and available for free from the
:caption: Development tools
:hidden:
docker_configuration
docker-configuration
- :doc:`docker_configuration`
- :doc:`docker-configuration`
.. - :doc:`docker_compose_configuration`
.. - :doc:`docker-compose-configuration`
......@@ -76,7 +76,7 @@ Information about the SKA
* How does the SKA operate? How is it meant to work?
* Read `these slides <https://confluence.skatelescope.org/download/attachments/113803312/SKA_Programmes_Induction_v2020.1.pdf?version=1&modificationDate=1595231309607&api=v2>`_ on the SKA operational programme.
* Read `about the SKA Operational Programme<https://confluence.skatelescope.org/download/attachments/113803312/SKA_Programmes_Induction_v2020.1.pdf?version=1&modificationDate=1595231309607&api=v2>`_.
* What is Radio Astronomy?
......@@ -157,7 +157,7 @@ First Month
This month is about getting you to the stage where you're able to contribute to your team's work.
In each subsection, items are approximately ordered by priority, so things earlier in the list should usually be done before things later in the list.
First of all, you should familiarise yourself with the `SKA Definition of Done <https://developer.skatelescope.org/en/latest/development_practices/definition_of_done.html>`_.
First of all, you should familiarise yourself with the :doc:`SKA Definition of Done </policies/definition-of-done>`
Understanding more about the SKA
--------------------------------
......@@ -171,7 +171,7 @@ Understanding more about the SKA
* And look at the `operational flow <https://confluence.skatelescope.org/display/SE/Observation+Management+and+Controls+Agile+Release+Train?preview=/74743196/74743245/OperationalFlow-v2.pdf>`_. The goal here is to find out where your team fits in the organisation, but with a bit more detail than we had time for in week one.
* Look at the `Module Decomposition <https://confluence.skatelescope.org/display/SWSI/Views%3A+Module>`_ of the SKA, and learn how this maps to the different `GitLab project <https://developer.skatelescope.org/en/latest/projects/list.html>`_.
* Read the `Architectural Decision Process <https://developer.skatelescope.org/en/latest/community/decision_making.html>`_. This process is how we can change and update our architecture, as we find out more about the system we're implementing, or as we need to adopt new technology. All developers are able to reason about the architecture of the system; you'll need to know the process.
* Read the `Architectural Decision Process </policies/decision-making>`. This process is how we can change and update our architecture, as we find out more about the system we're implementing, or as we need to adopt new technology. All developers are able to reason about the architecture of the system; you'll need to know the process.
What are your skills?
---------------------
......@@ -205,7 +205,7 @@ Discuss this with your Scrum Master to see which ones are most appropriate for y
* Join a Community of Practice (CoP). CoPs span the two Agile Release Trains (ARTs), and are a good way of sharing expertise, connecting with the wider community and making a contribution.
* Continue watching the `Radio Interferometry lectures <https://confluence.skatelescope.org/display/SE/Lectures+on+Radio+Interferometry>`_.
* Get involved in a team's feature. This may be as a developer, reviewer, tester, by shadowing a Feature owner, helping with a demo, or something else!
* Learn about (or get!) access to the `EngageSKA Cluster <https://developer.skatelescope.org/en/latest/services/ait_performance_env.html>`_, or `access to HPC facilities <https://confluence.skatelescope.org/display/SE/HPC+access>`_ for testing, prototyping and performance testing. People on the DP ART are more likely to need to access the HPC facilities for performance testing; most developers will need to be aware of how the EngageSKA cluster is used for testing. You may also need to arrange access to the `SKA Data Store <https://confluence.skatelescope.org/display/SE/Working+with+Google+Cloud+Platfom+%28GCP%29+storage>`_.
* Learn about (or get!) access to the `EngageSKA Cluster </tools/test-infrastructure>`, or `access to HPC facilities <https://confluence.skatelescope.org/display/SE/HPC+access>`_ for testing, prototyping and performance testing. People on the DP ART are more likely to need to access the HPC facilities for performance testing; most developers will need to be aware of how the EngageSKA cluster is used for testing. You may also need to arrange access to the `SKA Data Store <https://confluence.skatelescope.org/display/SE/Working+with+Google+Cloud+Platfom+%28GCP%29+storage>`_.
* Create or amend some SKA documentation, whether on the Developer Portal, Confluence, or in a specific GitLab project.
* Attend a system demo. You can find out more about demos in the #system-demos-buzz Slack channel, or in the `Demos <https://confluence.skatelescope.org/pages/viewpage.action?pageId=68715218>`_ pages in Confluence.
* Sign up for some SKA-organised training. We expect that you'll need to attend some SAFe training; now is a good time to sign up!
......@@ -251,7 +251,7 @@ Remember that we have `training pages on Confluence <https://confluence.skateles
* Learn about `ECPs (Engineering Change Proposals) <https://confluence.skatelescope.org/pages/viewpage.action?pageId=5767262>`_. These are often required for major architectural changes, so it's useful to understand the purpose and process of ECPs.
* Continue with your training plan, using the skills matrix!
* Make sure you know where to get help. This was covered in week one, but some revision may be helpful.
* Have a look at the various `Monitoring Dashboards <https://developer.skatelescope.org/en/latest/services/monitoring-dashboards.html>`_ for the EngageSKA Cluster, so you can see what things look like when our prototype is running, and what data we are collecting about it.
* Have a look at the various `Monitoring Dashboards <https://developer.skatelescope.org/en/latest/tools/monitoring-dashboards.html>`_ for the EngageSKA Cluster, so you can see what things look like when our prototype is running, and what data we are collecting about it.
* Learn about the SKA naming conventions for code, repositories, containers, etc. We need to make our code and the artefacts built from it easy to understand, so we have some standards to adhere to, and some recommendations.
This is the end of your formal onboarding!
......
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