HTTPS SSH
# WARNING before you start
# Carefully inspect tool usage. If bugs are found within the tool, users may be able to break
# out of the container and mount files on the host system.

This is a fork of toolfactory that makes use of Docker to sandbox the generated script.
As such you need to have the system user under which galaxy tools are executed be able to run Docker. 
On Ubuntu you can do this by adding your galaxy user to the docker group (http://askubuntu.com/questions/477551/how-can-i-use-docker-without-sudo).
Assuming galaxy runs as the user galaxy, this is the short form for installing Docker from the official docker Ubuntu Trusty repository:

sudo apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv-keys 36A1D7869245C8950F966E92D8576A8BA88D21E9
sudo sh -c "echo deb https://get.docker.io/ubuntu docker main > /etc/apt/sources.list.d/docker.list"
sudo apt-get update
sudo apt-get install lxc-docker
sudo gpasswd -a galaxy docker
sudo service docker restart

Eventually the galaxy process might need to be restarted.

On OSX, you need to boot2docker installed and available to the galaxy user.

Note that this could bring severe security problems in case untrusted users can become this user.
If you want to use this tool, read and understand the following article:
https://docs.docker.com/articles/security/#docker-daemon-attack-surface

Work is ongoing, some important features are missing, like being able to manage containers.
Currently, only a single container with pre-installed tools is available.

This is an beta-stage, potentially dangerous tool.

Please cite:
  - http://bioinformatics.oxfordjournals.org/cgi/reprint/bts573?ijkey=lczQh1sWrMwdYWJ&keytype=ref 
  - van den Beek M., Antoniewski C., in preparation 
if you use this tool in your published work.

*Short Story*

This is an unusual Galaxy tool that exposes unrestricted scripting to users of a Galaxy server, 
allowing them to run scripts in R, python, sh and perl over input datasets, 
writing a single new data set as output.

In addition, this tool optionally generates very simple new Galaxy tools, that effectively
freeze the supplied script into a new, ordinary Galaxy tool that runs it over one or more input files, 
working just like any other Galaxy tool for your users.

To use the ToolFactory, you should have prepared a script to paste into a text box,
and a small test input example ready to select from your history to test your new script.
There is an example in each scripting language on the Tool Factory form. You can just
cut and paste these to try it out - remember to select the right interpreter please. You'll
also need to create a small test data set using the Galaxy history add new data tool.

If the script fails somehow, use the "redo" button on the tool output in your history to
recreate the form complete with broken script. Fix the bug and execute again. Rinse, wash, repeat.

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 - toolshed.gz - as the name suggests,
it's an archive ready to upload to a Galaxy ToolShed as a new tool repository.

Once it's in a ToolShed, it can be installed into any local Galaxy server from
the Galaxy administrative interface.

Once the new tool is installed, local users can run it - each time, the script that was supplied
when it was built will be executed with the input chosen from the user's history. In other words,
the tools you generate with the ToolFactory run just like any other Galaxy tool,
but run your script every time. 

Tool factory tools are perfect for workflow components. One input, one output, no variables.

*Reasons to read further*

If you use Galaxy to support your research;

You and fellow users are sometimes forced to take data out of Galaxy, process it with ugly
little perl/awk/sed/R... scripts and put it back;

You do this when you can't do some transformation in Galaxy (the 90/10 rule);

You don't have enough developer resources for wrapping dozens of even relatively simple tools;

Your research and your institution would be far better off if those feral scripts were all tucked 
safely in your local toolshed and Galaxy histories.

*The good news* If it can be trivially scripted, it can be running safely in your
local Galaxy via your own local toolshed in a few minutes - with functional tests.


*Value proposition* The ToolFactory allows Galaxy to efficiently take over most of your lab's 
dark script matter, making it reproducible in Galaxy and shareable through the ToolShed.

That's what this tool does. You paste a simple script and the tool returns 
a new, real Galaxy tool, ready to be installed from the local toolshed to local servers.
Scripts can be wrapped and online literally within minutes.

*To fully and safely exploit the awesome power* of this tool, Galaxy and the ToolShed,
you should be a developer installing this tool on a private/personal/scratch local instance where you 
are an admin_user. Then, if you break it, you get to keep all the pieces
see https://bitbucket.org/fubar/galaxytoolfactory/wiki/Home

** Installation **
This is a Galaxy tool. You can install it most conveniently using the administrative "Search and browse tool sheds" link.
Find the Galaxy Test toolshed (not main) and search for the toolfactory repository.
Open it and review the code and select the option to install it.

If you can't get the tool that way, the xml and py files here need to be copied into a new tools 
subdirectory such as tools/toolfactory Your tool_conf.xml needs a new entry pointing to the xml 
file - something like::

  <section name="Tool building tools" id="toolbuilders">
    <tool file="DockerToolFactory.xml"/>
  </section>

If not already there (I just added it to datatypes_conf.xml.sample), please add:
<datatype extension="toolshed.gz" type="galaxy.datatypes.binary:Binary" mimetype="multipart/x-gzip" subclass="True" />
to your local data_types_conf.xml. 

Ensure that html sanitization is set to False and uncommented in universe_wsgi.ini

You'll have to restart the server for the new tool to be available.

R, python, perl are preloaded in the supplied Dockerfile.
Upon first execution the Dockerfile will be used to build an image
with varius pre-installed tools.
Adding new ones should be easy enough, and follows standard conventions
for Docker tools.
Please make suggestions as bitbucket issues and code.
The HTML file code automatically shrinks R's bloated pdfs, and depends on ghostscript. The thumbnails require imagemagick .

*What it does* This is a tool factory for simple scripts in python, R and perl currently. 
Functional tests are automatically generated.
On a technical level, a Docker container is started, and input and output files
are made available to the container.
After running, the docker container will be terminated.

LIMITED to simple scripts that read inputs from the history.
Optionally can write one new history dataset, and optionally collect any number of outputs into links on an autogenerated HTML
index page for the user to navigate - useful if the script writes images and output files - pdf outputs
are shown as thumbnails and R's bloated pdf's are shrunk with ghostscript so that and imagemagik need to
be avaailable.

Generated tools can be edited and enhanced like any Galaxy tool, so start small and build up since
a generated script gets you a serious leg up to a more complex one.

*What you do* You paste and run your script
you fix the syntax errors and eventually it runs
You can use the redo button and edit the script before
trying to rerun it as you debug - it works pretty well.

Once the script works on some test data, you can
generate a toolshed compatible gzip file
containing your script ready to run as an ordinary Galaxy tool in a
repository on your local toolshed. That means safe and largely automated installation in any
production Galaxy configured to use your toolshed.

*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 fucking code before you install any tool. 
Especially this one - it is really scary.

If you opt for an HTML output, you get all the script outputs arranged
as a single Html history item - all output files are linked, thumbnails for all the pdfs.
Ugly but really inexpensive.

Patches and suggestions welcome as bitbucket issues please? 


copyright ross lazarus (ross stop lazarus at gmail stop com) May 2012

all rights reserved
Licensed under the LGPL if you want to improve it, feel free https://bitbucket.org/fubar/galaxytoolfactory/wiki/Home

Material for our more enthusiastic and voracious readers continues below - we salute you.

**Motivation** Simple transformation, filtering or reporting scripts get written, run and lost every day in most busy labs 
- even ours where Galaxy is in use. This 'dark script matter' is pervasive and generally not reproducible.

**Benefits** For our group, this allows Galaxy to fill that important dark script gap - all those "small" bioinformatics 
tasks. Once a user has a working R (or python or perl) script that does something Galaxy cannot currently do (eg transpose a 
tabular file) and takes parameters the way Galaxy supplies them (see example below), they:

1. Install the tool factory on a personal private instance

2. Upload a small test data set

3. Paste the script into the 'script' text box and iteratively run the insecure tool on test data until it works right - 
there is absolutely no reason to do this anywhere other than on a personal private instance. 

4. Once it works right, set the 'Generate toolshed gzip' option and run it again. 

5. A toolshed style gzip appears ready to upload and install like any other Toolshed entry. 

6. Upload the new tool to the toolshed

7. Ask the local admin to check the new tool to confirm it's not evil and install it in the local production galaxy

**Simple examples on the tool form**

A simple Rscript "filter" showing how the command line parameters can be handled, takes an input file, 
does something (transpose in this case) and writes the results to a new tabular file::

 # transpose a tabular input file and write as a tabular output file
 ourargs = commandArgs(TRUE)
 inf = ourargs[1]
 outf = ourargs[2]
 inp = read.table(inf,head=F,row.names=NULL,sep='\t')
 outp = t(inp)
 write.table(outp,outf, quote=FALSE, sep="\t",row.names=F,col.names=F)

Calculate a multiple test adjusted p value from a column of p values - for this script to be useful,
it needs the right column for the input to be specified in the code for the
given input file type(s) specified when the tool is generated ::

 # use p.adjust - assumes a HEADER row and column 1 - please fix for any real use
 column = 1 # adjust if necessary for some other kind of input
 fdrmeth = 'BH'
 ourargs = commandArgs(TRUE)
 inf = ourargs[1]
 outf = ourargs[2]
 inp = read.table(inf,head=T,row.names=NULL,sep='\t')
 p = inp[,column]
 q = p.adjust(p,method=fdrmeth)
 newval = paste(fdrmeth,'p-value',sep='_')
 q = data.frame(q)
 names(q) = newval
 outp = cbind(inp,newval=q)
 write.table(outp,outf, quote=FALSE, sep="\t",row.names=F,col.names=T) 



Another Rscript example without any input file - generates a random heatmap pdf - you must make sure the option to create an HTML output file is
turned on for this to work. The heatmap will be presented as a thumbnail linked to the pdf in the resulting HTML page::

 # note this script takes NO input or output because it generates random data
 foo = data.frame(a=runif(100),b=runif(100),c=runif(100),d=runif(100),e=runif(100),f=runif(100))
 bar = as.matrix(foo)
 pdf( "heattest.pdf" )
 heatmap(bar,main='Random Heatmap')
 dev.off()

A Python example that reverses each row of a tabular file. You'll need to remove the leading spaces for this to work if cut
and pasted into the script box. Note that you can already do this in Galaxy by setting up the cut columns tool with the
correct number of columns in reverse order,but this script will work for any number of columns so is completely generic::

# reverse order of columns in a tabular file
import sys
inp = sys.argv[1]
outp = sys.argv[2]
i = open(inp,'r')
o = open(outp,'w')
for row in i:
    rs = row.rstrip().split('\t')
    rs.reverse()
    o.write('\t'.join(rs))
    o.write('\n')
i.close()
o.close()


Galaxy as an IDE for developing API scripts
If you need to develop Galaxy API scripts and you like to live dangerously, please read on.

Galaxy as an IDE?
Amazingly enough, blend-lib API scripts run perfectly well *inside* Galaxy when pasted into a Tool Factory form. No need to generate a new tool. Galaxy+Tool_Factory = IDE I think we need a new t-shirt. Seriously, it is actually quite useable.

Why bother - what's wrong with Eclipse
Nothing. But, compared with developing API scripts in the usual way outside Galaxy, you get persistence and other framework benefits plus at absolutely no extra charge, a ginormous security problem if you share the history or any outputs because they contain the api script with key so development servers only please!

Workflow
Fire up the Tool Factory in Galaxy.

Leave the input box empty, set the interpreter to python, paste and run an api script - eg working example (substitute the url and key) below.

It took me a few iterations to develop the example below because I know almost nothing about the API. I started with very simple code from one of the samples and after each run, the (edited..) api script is conveniently recreated using the redo button on the history output item. So each successive version of the developing api script you run is persisted - ready to be edited and rerun easily. It is ''very'' handy to be able to add a line of code to the script and run it, then view the output to (eg) inspect dicts returned by API calls to help move progressively deeper iteratively.

Give the below a whirl on a private clone (install the tool factory from the main toolshed) and try adding complexity with few rerun/edit/rerun cycles.

Eg tool factory api script
import sys
from blend.galaxy import GalaxyInstance
ourGal = 'http://x.x.x.x:xxxx'
ourKey = 'xxx'
gi = GalaxyInstance(ourGal, key=ourKey)
libs = gi.libraries.get_libraries()
res = []
# libs looks like
# u'url': u'/galaxy/api/libraries/441d8112651dc2f3', u'id': u'441d8112651dc2f3', u'name':.... u'Demonstration sample RNA data',
for lib in libs:  
    res.append('%s:\n' % lib['name'])
    res.append(str(gi.libraries.show_library(lib['id'],contents=True)))
outf=open(sys.argv[2],'w')
outf.write('\n'.join(res))
outf.close()

**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

**Obligatory screenshot**

http://bitbucket.org/fubar/galaxytoolmaker/src/fda8032fe989/images/dynamicScriptTool.png