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* Avoid overwriting existing data by adding a random string to the
name of the ProbeSet
* Read ProbeSet names separately from the means for the strains, to
avoid entering the same ProbeSet record over and over with varying
names.
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The "ProbeSetId" value in the file is actually stored in the database
in the `ProbeSet.Name` field, whereas the `ProbeSetXRef` table
actually uses the `ProbeSet.Id` value to define the
relationships. This commit fixes that issue.
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Due to possible schema differences between local small db on
development computer and those on CI/CD and Production, explicitly
specify the columns being operated on by the queries.
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* To avoid confusion, only display the "alert-success" green on
completion of the parsing process. While parsing, if there are no
errors, then display the "No errors found so far" message without
the green colour.
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* guix.scm: Add dependency (gunicorn)
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Use the sys.executable to get the correct python binary to run the
external processes, and setup the environment to point to the correct
PYTHONPATH.
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* guix.scm: reorganise the dependencies
* setup.cfg: change the `install_requires` values
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Check the connections in the wsgi.py file, outside of the `create_app`
application factory to avoid issues with tests failing due to test app
not initialising because of missing connections in the test
environment.
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* Display the status of the job, as it is running
* Display STDERR output if an error occurs
* Display STDOUT output as job is running and on successful completion
of the job
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- Hook up external data insertion script to webserver code
- Provide rudimentary status indication
- Generalise some job creation details
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* Fix bug where stderr was not being updated on redis appropriately
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Ease the selection of a radio button by allowing the user to click on
any of the table cells that are in the same row as the radio button of
concern.
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* quality_control/file_utils.py (new file): extract common file
utilities.
* quality_control/parsing.py (refactor): extract common file
utilities.
* scripts/insert_data.py: Implement data insertion for averages/means
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* qc_app/__init__.py (refactor): Check connection before launching the
application
* qc_app/check_connections.py (new file): Add code to check
connections
* qc_app/db_utils.py (refactor): enable passing the database uri as an
argument to the connection creation function.
* scripts/worker.py (refactor): Use new code to check for redis
connection.
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Use the generic worker script as the interface for launching external
processes.
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Add a generic worker script, whose purpose is:
- to launch the specific worker script
- to capture both stdin and stderr streams and put them on redis
In this way, we can launch redis-aware and redis-unaware workers and
capture their outputs or errors for later processing.
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As preparation for building a new generic worker script, this commit
renames the file validation script from 'worker.py' to
'validate_file.py' so as to ensure the name conforms better to what
the script does.
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Provide user with a confirmation stage where they can verify all the
data before inserting into the database.
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Enable the user to create a new dataset should the need arise.
A few extra fixes were done, such as:
- Provide list of average methods to choose from
- Provide input elements for some expected fields
- Add a new confirmation step before doing the actual data update
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Rather than using the redirect, that led to exposing the study id as a
get parameter, this commit adds an auxilliary step that allows the
user to choose whether to continue with the new study or go back and
select an existing study.
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- Implement UI enabling selection from existing datasets
- Start implementation of UI that enables creation of new dataset
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Enable the creation of the new study, and redirect appropriately with
the new study id.
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- Build code to populate the "Group" and "Tissue" dropdown lists
- Enable redirect with POST data (code 307) in case there is input
error to enable the user fix their errors
- Move hidden fields to macro to reduce repetition
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Implement the select study UI
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