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Add a test for the partial correlations endpoint, with:
- no data in the request
- missing items in the data
Fix the bugs caught by the test
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Create a client fixture to help with the integration tests
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Use pytest's `mark` feature to explicitly categorise the tests and run them
per category
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Add property tests using pytest and hypothesis to test that the expected
properties hold for the
`gn3.computations.partial_correlations.dictify_by_samples`
function.
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These tools have been greatly improved and moved to a new home at
https://git.genenetwork.org/arunisaac/dump-genenetwork-database
* sql/map-database.sh, sql/schema-from-in-db-documentation.org,
sql/schema-original.sql, sql/schema.png, sql/schema.sql, sql/schema.svg: New
files.
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Enable running commands:
- `python3 setup.py unit_check`: run the unit tests
- `python3 setup.py integration_check`: run integration tests
- `python3 setup.py performance_check`: run performance tests
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Quote the shell variables to prevent globbing and word splitting.
Deactivate this check for the specific lines that require intentional word
splitting
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We have our own laminar CI and no longer need GitHub actions.
* .github/workflows: Delete directory.
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Do all the work in a single iteration to avoid unnecessary iterations that
hamper performance.
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Web servers are long-running processes, and python is not very good at
cleaning up after itself especially in forked processes - this leads to memory
errors in the web-server after a while.
This commit removes the use of multiprocessing to avoid such failures.
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This commit refactors the code to make it possible to use multiprocessing to
speed up the computation of the partial correlations.
The major refactor is to move the `__compute_trait_info__` function to the
top-level of the module, and provide to it all the other necessary context via
the new args.
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In Python3 when slicing,
seq[:min(some_val, len(seq))] == seq[:some_val]
because Python3 will just return a copy of the entire sequence if `some_val`
happens to be larger/greater than the length of the sequence.
This commit removes the unnecessary call to `min()`
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If a user replaces an individual value with an "x", delete that date entry
from the respective table. Deletion here is the only option since by default
the Nstrain, PublishData and PublishSE don't accept null values. Note that
deleting all 3 values is equivalent to removing the sample from the CSV file.
* gn3/db/traits.py (update_sample_data): If a value is "x", delete it from the
respective table.
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When editing values from "x" to "0"(or any other value) when editing data, an
"update" statement was being run; thereby no new value was being inserted. To
the end user, modifying an "x" value to something else meant that no value was
being inserted. This commit fixes that by doing an insert whenever a change
from "x" to "0" is performed.
* gn3/db/traits.py (update_sample_data): Add insert statements whenever an
"update" statement returns a 0 row-count.
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The rqtl_wrapper script was throwing an error when only a single
categorical covariate was used. This is apparently because "covars[,name]"
throws an error in such a situation. Using just "covars" in such a
situation prevents the error. So I just added an if statement checking
the number of covariates. There might be some better way to deal with
this in R, but this is the best I could come up with.
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The PublishFreeze table isn't necessary in phenotype queries, since
PublishFreeze.Id = InbredSet.Id (for the purposes of identifying traits,
at least)
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In line 91 of gn3/db/traits.py, there was an if statement "if
record[key] else 'x'" that was treating values of 0 as False, so I
changed it to explicitly check that values aren't None
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The PublishFreeeze table is actually unnecessary for this query, since
the group ID (inbred_set_id) should be passed in and that ID is in the
PublishXRef table (so no neeed to join with PublishFreeze)
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This reverts commit f676c291967f8a81836b73c5a5dcd3c65e02552c.
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We now have separate CI jobs for the pylint and mypy tests.
* README.md: Add pylint and mypy CI badges.
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