Runtime post job actions are post job actions inserted when the workflow is invoked instead of being part of the workflow object in the database. The bug noticed by @kellrott was that these actions were being appended to the original workflow post job actions instead of being transient things just attached to the jobs themselves.
This fixes that problem and adds a test to try to prevent regressions.
- Add example tool demonstrating/testing specifing format via conditional output actions.
- Add API test testing mapping collections over tools without output action formatting.
- Add API test testing more complex actions using the Cut1 tool.
- Add script to hit the API with workflows requests.
- Update testing Dockerfile to allow just booting up with a fixed master API key for this test to leverage.
- WIP: on updating test Dockerfile to work with slurm, multiple handlers, uwsgi, etc...
Going to use bioblend for performance testing instead of galaxy_interactor. This refactoring allows all of those helpers to be reused with bioblend backing the helpers instead of galaxy_interactor.
It would fail when being run with the rest of the suite and not on its own - because it was using the same id for the workflow id and invocation id - which is obviously wrong unless it is a completely fresh database :).
These aren't ideal tests - but it is some indication that things are working that the API will import the workflow and produce a representation. Should follow up at some point and verify the representation is in fact the correct one.
Tools may now use $input.element_identifier during tool evalution for input 'data' parameters with the following semantics:
- If the input was specified as a single dataset by the user - this just fallbacks to providing the $input.name.
- If the input was mapped over a collection (to produce many jobs) or if the input is a 'multiple="true"' input that was provided a collection - the $input.element_identifier will be the element identifier for the corresponding collection item (generally much more useful the dataset name - since if preserved throughout workflows).
'data_collection' parameters already can access this kind of information - but it is something of a best practice to use simple 'data' parameters since they are compatible with more traditional un-collected datasets.
This commit really needs more comments - but Philip Mabon has been patiently waiting for this functionality for a long time.
Normal selects seem to be prevented from execution with invalid parameter values, but not columns. Values are escaped properly so shell exploitation isn't the problem - but as a usability thing Galaxy should prevent execution and provide a warning message.
Models:
Track whether dataset collections have been populated yet.
Dataset collections are still effectively immutable once populated - but dynamic output collections require them to be sort of like `final` fields in Java (analogy courtesy of JJ) - allowing them to be declared before they are initialized or populated. This is tracked by the `populated_state` field.
Tools:
Output collections can now describe `discover_datasets` elements just like datasets - except in this case instead of dynamically populating new datasets in the history - they will comprise the collection. `designation` has been reused to serve as the element_identifier for the collection element corresponding to the dataset.
See Pull Request 356 for more information on the discover_datasets tag https://bitbucket.org/galaxy/galaxy-central/pull-request/356/enhancements-for-runtime-discovered.
Workflows:
Update workflow execution and recovery for dynamic output collections.
Galaxy workflow data flow before collections
* - * - * - * - * - *
Galaxy worfklow data flow after collections (iteration 1)
* - * - * \
* - * - *
* - * - * / \
* - * - *
* - * - * \ /
* - * - *
* - * - * /
Galaxy worfklow data flow after this commit
/ * - * \
* - * * - *
/ \ * - * / \
/ \
/ \
/ / * - * \ \
* - * -- * - * * - * -- * - *
\ \ * - * / /
\ /
\ /
\ / * - * \ /
* - * * - *
\ * - * /
By "static" I mean tools such as a FASTQ de-interlacer that would produce a "paired" collection with two datasets everytime. By "determinable" I mean tools that perform N->N operations within the same job - such as a tool that needs to normalize a bunch of datasets all at once and not in separate jobs. (For N->N collection operations that should or can be done in N separate jobs tool authors should just write tools that operate over a dataset and produce a dataset and let the end-user 'map over' that operation.)
There are still large classes of operations where the structure of the output collection cannot be pre-determined - such as splitting files (e.g. bam files by read group) - that are not implemented in this commit.
Model:
The models have been updated to do a more thorough job of tracking collection outputs. Jobs just producing HistoryDatasetCollectionAssociations works fine for simple jobs producing collections - but you don't want to map a list over a tool that produces a pair and produce a bunch of pairs HDCAs and a list:pair HDCA- you just want a bunch of pieces and the one list:pair at that the top.
Workflow:
Workflows containing such operations can be executed - but the workflow editor has not been updated to handle this complexity (and it will require a significant overhaul) so such tools are not available in the workflow editor.
Tool Testing:
This commit also introduces a new tool XML syntax for describing tests on output collections. See files test/functional/tools/collection_creates_list.xml and test/functional/tools/collection_creates_pair.xml for examples.
Tests:
Includes two tools to test this - one that uses explicit pair output names and one that iterates over the structure of input list to produce an output list.
Includes several new tools API tests that test the tools described above via the API and implicit mapping over such tools. Includes two new workflow API tests - one that verifies a simple workflow with output collections works and one that verifies mapping over workflow steps in collections works.
Feature requested by Kyle. Implemented only in the API at this point - not sure it is a feature valuable to UI consumers.
Pass in PJAs along with step parameters map but keyed on __POST_JOB_ACTIONS__. JSON definition same as when defining PJA in the workflow definition JSON.
Includes test cases for normal use and for use after delayed workflow steps have been evaluated by the new workflow scheduling stuff.
How to use:
1.) Place multiple tools with different IDs in your tool conf.
2.) ... ummm ... no step 2 - just use the tools.
Implementation:
The Tool Shed allows tool lineages by assigning each tool version a GUID and tracking versions in a database. This
implementation works by simply allowing the ToolBox to contain multiple tools with the same ID and orders them by the version specified by the tool author.
To track enable this a second tool lineage has been introduced that just uses tool versions instead of a database (non-toolshed installed tools are not longer placed into the Tool Shed install database). The ToolBox has been updated to allow multiple versions per tool id (defaulting to the 'latest' version for all operations which do not specify a version). Both jobs and workflow steps would track tool versions but did not use that version when fetching tools from the Toolbox - these components have been updated to try to use the tool version.
Unit tests working through most of the ToolBox and tool panel have been added, as well as functional tests exercising the tools API and to ensure workflows now at least attempt to respect tool versions (still kind of silently switches versions in some cases). Manual tests against the new tool form seem to demonstrate the tool switching and tool re-running work with only minor changes to the tools API and the job handler.
Add tests for new date range and history filtering as well as to ensure only admins get to see external_id and command_line and that users cannot see each other's jobs.
Always allow admins to views all jobs on index (instead of only when user_details is specified) and show. Add user_email and external_id to show (for admins) to bring it inline with index and add command_line to index (for admins) to bring it in line with show.
Show still allow more details including job standard error and output as well as job metrics.
Pass in the parameter 'inputs_by' as 'step_uuid' to the workflow run command to use this.
Specifing inputs by UUID has the nice advantage that it survives workflows saves - so if one sets up an API script or something to target a workflow - saving the workflow in the editor doesn't need to break the script as long as inputs were not added or deleted. The UUID (like the order_index) has the advantage of the step id that it is predeterminable - so one can set it up a workflow script against any Galaxy and the script doesn't need to be adapted to raw ids the steps get assigned in that instance.
Give every step a UUID that can be preserved across edit to the workflow. Likewise - allow every step to be given a label (a unique short name for that workflow) - that allows for a human consumable way to reference steps for use in tests and when driving workflows via the API. Workflow editor doesn't yet (and might never) display these attributes but it does preserve them across workflow saves.
Implement automated testing that uploading workflows, updating workflows, and exporting them handle UUID and labels. Manually tested workflow editor preserves labels and UUID across changes.
This means steps that are not connecting an output of one step to the input of another. This could potentially address all sorts of untraditional (in a Galaxy sense) workflows where some sort of data is managed externally. The most important use I think I have heard discussed is that of data managers - this can be used in cases where data managers depend on one another (grab the fasta files in one step, index them in another) or workflows where a downstream analysis depends on index data populated via data managers in earlier steps.
Not really sure how to represent these in the workflow editor - but this is a power user feature anyway so hopefully that is not super pressing. The YAML to workflow DSL supports the operation (see test cases) so these power users (a euphemism for Dan I guess) can just use that for now.
This logic for building up editor representation of the workflow.
Introduce concept of a workflow to dict style - with 'export' and 'editor' as first cracks.
Dannon Baker