vdk-ipython: add support for %%vdksql magic command#2619
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What happens with the standard run, currently vdk-run only works with standard python so cells which contain this would automatically fail, please change the vdk-notebook to work with those too if we are really going to provide this as functionality |
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If we are not going to add it as a step now, i would say this might cause a lot of errors since probably the users will try to add it as a step and there will be difference between development and full execution of a job |
I've specified in the description we are going to support |
I am not sure that's true. But I do have the change for notebook step ready . But that will be separate Pull Request |
You can see the change in vdk-notebook in #2622 |
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Please add the changes to the README of the plugin and also include a simple example there |
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vdk run now would recognize %%vdksql cell as steps and execute them and SQL steps. This is a continuation of #2619
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To provide a seamless user experience for data professionals using VDK Notebooks for SQL queries. The feature allows them to execute SQL queries (and VDK SQL steps) right within the notebook, visualize the results in an interactive grid, and resuse managed SQL connections through VDK."qgrid", Leveraged the ipyaggrid package to display SQL query results in a user-friendly, interactive grid. Also added auto-initialization for VDK job and managed its connections for SQL execution. Opted for ipyaggrid over other options like qgrid due to its flexibility and feature set. Other evaluated were `itables` (not as rich), `beakerx` (could not get it to work), `qgrid` (could not get it to work) Unit tests. Manual testing was also performed to confirm the user experience and feature functionality. See attached screenshots.
for more information, see https://pre-commit.ci
To provide a seamless user experience for data professionals using VDK Notebooks for SQL queries. The feature allows them to execute SQL queries (and VDK SQL steps) right within the notebook, visualize the results in an interactive grid, and resuse managed SQL connections through VDK."qgrid", Leveraged the ipyaggrid package to display SQL query results in a user-friendly, interactive grid. Also added auto-initialization for VDK job and managed its connections for SQL execution. Opted for ipyaggrid over other options like qgrid due to its flexibility and feature set. Other evaluated were `itables` (not as rich), `beakerx` (could not get it to work), `qgrid` (could not get it to work) Unit tests. Manual testing was also performed to confirm the user experience and feature functionality. See attached screenshots.
To provide a seamless user experience for data professionals using VDK Notebooks for SQL queries. The feature allows them to execute SQL queries (and VDK SQL steps) right within the notebook, visualize the results in an interactive grid, and resuse managed SQL connections through VDK."qgrid", Leveraged the ipyaggrid package to display SQL query results in a user-friendly, interactive grid. Also added auto-initialization for VDK job and managed its connections for SQL execution. Opted for ipyaggrid over other options like qgrid due to its flexibility and feature set. Other evaluated were `itables` (not as rich), `beakerx` (could not get it to work), `qgrid` (could not get it to work) Unit tests. Manual testing was also performed to confirm the user experience and feature functionality. See attached screenshots.
for more information, see https://pre-commit.ci
To provide a seamless user experience for data professionals using VDK Notebooks for SQL queries. The feature allows them to execute SQL queries (and VDK SQL steps) right within the notebook, visualize the results in an interactive grid, and resuse managed SQL connections through VDK."qgrid", Leveraged the ipyaggrid package to display SQL query results in a user-friendly, interactive grid. Also added auto-initialization for VDK job and managed its connections for SQL execution. Opted for ipyaggrid over other options like qgrid due to its flexibility and feature set. Other evaluated were `itables` (not as rich), `beakerx` (could not get it to work), `qgrid` (could not get it to work) Unit tests. Manual testing was also performed to confirm the user experience and feature functionality. See attached screenshots.
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To provide a seamless user experience for data professionals using VDK
Notebooks for SQL queries. The feature allows them to execute SQL
queries (and VDK SQL steps in the future) right within the notebook, visualize the
results in an interactive grid, and resuse managed SQL connections
through VDK.
Leveraged the ipyaggrid package to display SQL query results in a
user-friendly, interactive grid. Also added auto-initialization for VDK
job and managed its connections for SQL execution. Opted for ipyaggrid
over other options like qgrid due to its flexibility and feature set.
Other evaluated were
itables(not as rich),beakers(could not getit to work),
qgrid(could not get it to work)Ipyaggrid is optional because it's not clear if every notebook installation would support (and vdk-ipython should work not just with jupyterlab or even some versions of jupyterlab may not)
Did minor refactoring. Move all Job control related functionality into
vdk.plugin.ipython.jobmodule.The new SQL functionality is in
vdk.plugin.ipython.sqlwhile the registration is kept invdk.plugin.ipythonmodule (though__init__.pyfile)Tested with functional and unit tests. Manual testing was also performed to confirm the user
experience and feature functionality. See attached screenshots and video
ipyaggrid is optional but if it is installed, the grid result would work like this.
vdk-ipython-sql.mp4
Without ipyaggrid i looks like :