Mercurial > repos > fubar > tool_factory_docker
view toolfactory/README.md @ 0:83f8bb78781e draft
Uploaded
author | fubar |
---|---|
date | Fri, 11 Dec 2020 02:51:15 +0000 |
parents | |
children |
line wrap: on
line source
**Breaking news! Docker container is recommended as at August 2020** A Docker container can be built - see the docker directory. It is highly recommended for isolation. It also has an integrated toolshed to allow installation of new tools back into the Galaxy being used to generate them. Built from quay.io/bgruening/galaxy:20.05 but updates the Galaxy code to the dev branch - it seems to work fine with updated bioblend>=0.14 with planemo and the right version of gxformat2 needed by the ToolFactory (TF). The runclean.sh script run from the docker subdirectory of your local clone of this repository should create a container (eventually) and serve it at localhost:8080 with a toolshed at localhost:9009. Once it's up, please restart Galaxy in the container with ```docker exec [container name] supervisorctl restart galaxy: ``` Jobs just do not seem to run properly otherwise and the next steps won't work! The generated container includes a workflow and 2 sample data sets for the workflow Load the workflow. Adjust the inputs for each as labelled. The perl example counts GC in phiX.fasta. The python scripts use the rgToolFactory.py as their input - any text file will work but I like the recursion. The BWA example has some mitochondrial reads and reference. Run the workflow and watch. This should fill the history with some sample tools you can rerun and play with. Note that each new tool will have been tested using Planemo. In the workflow, in Galaxy. Extremely cool to watch. *WARNING* Install this tool on a throw-away private Galaxy or Docker container ONLY Please NEVER on a public or production instance *Short Story* Galaxy is easily extended to new applications by adding a new tool. Each new scientific computational package added as a tool to Galaxy requires some special instructions to be written. This is sometimes termed "wrapping" the package because the instructions tell Galaxy how to run the package as a new Galaxy tool. Any tool in a Galaxy is readily available to all the users through a consistent and easy to use interface. Most Galaxy tool wrappers have been manually prepared by skilled programmers, many using Planemo because it automates much of the basic boilerplate and makes the process much easier. The ToolFactory (TF) uses Planemo under the hood for many functions, but hides the command line complexities from the TF user. *More Explanation* The TF is an unusual Galaxy tool, designed to allow a skilled user to make new Galaxy tools. It appears in Galaxy just like any other tool but outputs include new Galaxy tools generated using instructions provided by the user and the results of Planemo lint and tool testing using small sample inputs provided by the TF user. The small samples become tests built in to the new tool. It offers a familiar Galaxy form driven way to define how the user of the new tool will choose input data from their history, and what parameters the new tool user will be able to adjust. The TF user must know, or be able to read, enough about the tool to be able to define the details of the new Galaxy interface and the ToolFactory offers little guidance on that other than some examples. Tools always depend on other things. Most tools in Galaxy depend on third party scientific packages, so TF tools usually have one or more dependencies. These can be scientific packages such as BWA or scripting languages such as Python and are usually managed by Conda. If the new tool relies on a system utility such as bash or awk where the importance of version control on reproducibility is low, these can be used without Conda management - but remember the potential risks of unmanaged dependencies on computational reproducibility. The TF user can optionally supply a working script where scripting is required and the chosen dependency is a scripting language such as Python or a system scripting executable such as bash. Whatever the language, the script must correctly parse the command line arguments it receives at tool execution, as they are defined by the TF user. The text of that script is "baked in" to the new tool and will be executed each time the new tool is run. It is highly recommended that scripts and their command lines be developed and tested until proven to work before the TF is invoked. Galaxy as a software development environment is actually possible, but not recommended being somewhat clumsy and inefficient. Tools nearly always take one or more data sets from the user's history as input. TF tools allow the TF user to define what Galaxy datatypes the tool end user will be able to choose and what names or positions will be used to pass them on a command line to the package or script. Tools often have various parameter settings. The TF allows the TF user to define how each parameter will appear on the tool form to the end user, and what names or positions will be used to pass them on the command line to the package. At present, parameters are limited to simple text and number fields. Pull requests for other kinds of parameters that galaxyxml can handle are welcomed. Best practice Galaxy tools have one or more automated tests. These should use small sample data sets and specific parameter settings so when the tool is tested, the outputs can be compared with their expected values. The TF will automatically create a test for the new tool. It will use the sample data sets chosen by the TF user when they built the new tool. The TF works by exposing *unrestricted* and therefore extremely dangerous scripting to all designated administrators of the host Galaxy server, allowing them to run scripts in R, python, sh and perl. For this reason, a Docker container is available to help manage the associated risks. *Scripting uses* To use a scripting language to create a new tool, you must first prepared and properly test a script. Use small sample data sets for testing. When the script is working correctly, upload the small sample datasets into a new history, start configuring a new ToolFactory tool, and paste the script into the script text box on the TF form. *Outputs* Once the script runs sucessfully, a new Galaxy tool that runs your script can be generated. Select the "generate" option and supply some help text and names. The new tool will be generated in the form of a new Galaxy datatype *tgz* - as the name suggests, it's an archive ready to upload to a Galaxy ToolShed as a new tool repository. It is also possible to run a tool to generate test outputs, then test it using planemo. A toolshed is built in to the Docker container and configured so a tool can be tested, sent to that toolshed, then installed in the Galaxy where the TF is running. If the tool requires a command or test XML override, then planemo is needed to generate test outputs to make a complete tool, rerun to test and if required upload to the local toolshed and install in the Galaxy where the TF is running. Once it's in a ToolShed, it can be installed into any local Galaxy server from the server administrative interface. Once the new tool is installed, local users can run it - each time, the package and/or script that was supplied when it was built will be executed with the input chosen from the user's history, together with user supplied parameters. In other words, the tools you generate with the ToolFactory run just like any other Galaxy tool. TF generated tools work as normal workflow components. *Limitations* The TF is flexible enough to generate wrappers for many common scientific packages but the inbuilt automation will not cope with all possible situations. Users can supply overrides for two tool XML segments - tests and command and the BWA example in the supplied samples workflow illustrates their use. *Installation* The Docker container is the best way to use the TF because it is preconfigured to automate new tool testing and has a built in local toolshed where each new tool is uploaded. If you grab the docker container, it should just work. If you build the container, there are some things to watch out for. Let it run for 10 minutes or so once you build it - check with top until conda has finished fussing. Once everything quietens down, find the container with ```docker ps``` and use ```docker exec [containername] supervisorctl restart galaxy:``` That colon is not a typographical mistake. Not restarting after first boot seems to leave the job/worflow system confused and the workflow just will not run properly until Galaxy has restarted. Login as admin@galaxy.org with password "password". Feel free to change it once you are logged in. There should be a companion toolshed at localhost:9090. The history should have some sample data for the workflow. Run the workflow and make sure the right dataset is selected for each of the input files. Most of the examples use text files so should run, but the bwa example needs the right ones to work properly. When the workflow is finished, you will have half a dozen examples to rerun and play with. They have also all been tested and installed so you should find them in your tool menu under "Generated Tools" It is easy to install without Docker, but you will need to make some configuration changes (TODO write a configuration). You can install it most conveniently using the administrative "Search and browse tool sheds" link. Find the Galaxy Main toolshed at https://toolshed.g2.bx.psu.edu/ and search for the toolfactory repository in the Tool Maker section. Open it and review the code and select the option to install it. Otherwise, if not already there pending an accepted PR, please add: <datatype extension="tgz" type="galaxy.datatypes.binary:Binary" mimetype="multipart/x-gzip" subclass="True" /> to your local data_types_conf.xml. *Restricted execution* The tool factory tool itself will then be usable ONLY by admin users - people with IDs in admin_users. **Yes, that's right. ONLY admin_users can run this tool** Think about it for a moment. If allowed to run any arbitrary script on your Galaxy server, the only thing that would impede a miscreant bent on destroying all your Galaxy data would probably be lack of appropriate technical skills. **Generated tool Security** Once you install a generated tool, it's just another tool - assuming the script is safe. They just run normally and their user cannot do anything unusually insecure but please, practice safe toolshed. Read the code before you install any tool. Especially this one - it is really scary. **Send Code** Pull requests and suggestions welcome as git issues please? **Attribution** Creating re-usable tools from scripts: The Galaxy Tool Factory Ross Lazarus; Antony Kaspi; Mark Ziemann; The Galaxy Team Bioinformatics 2012; doi: 10.1093/bioinformatics/bts573 http://bioinformatics.oxfordjournals.org/cgi/reprint/bts573?ijkey=lczQh1sWrMwdYWJ&keytype=ref **Licensing** Copyright Ross Lazarus 2010 ross lazarus at g mail period com All rights reserved. Licensed under the LGPL