• Table of contents
• Writing a Script Calling a Third Party Tool
  • • Writing a Dockerfile
    • How to build a docker image from a Dockerfile
    • How to upload a docker image to Arvados
    • How to call an external tool from a crunch script
    • How to write data directly to Keep (Using TaskOutputDir)
    • When TaskOutputDir is not the correct choice
    • Putting it all together

Writing a Script Calling a Third Party Tool¶

Case study: FastQC

Good tips include:

• Keep the Dockerfile in the git repository

Writing a Dockerfile¶

Docker has some wonderful documentation for building Dockerfiles:

• A reference for Dockerfiles: https://docs.docker.com/engine/reference/builder/
• Dockerfile best practices: https://docs.docker.com/engine/userguide/eng-image/dockerfile_best-practices/

From Docker:

"""
Docker can build images automatically by reading the instructions from a Dockerfile. A Dockerfile is a text document that contains all the commands a user could call on the command line to assemble an image. Using docker build users can create an automated build that executes several command-line instructions in succession.

This page describes the commands you can use in a Dockerfile. When you are done reading this page, refer to the Dockerfile Best Practices (https://docs.docker.com/engine/userguide/eng-image/dockerfile_best-practices/) for a tip-oriented guide.
"""

FROM arvados/jobs

USER root

RUN apt-get -q update && apt-get -qy install \
  fontconfig \
  openjdk-6-jre-headless \
  perl \
  unzip \
  wget

USER crunch

RUN mkdir /home/crunch/fastqc
RUN cd /home/crunch/fastqc && \
    wget --quiet http://www.bioinformatics.babraham.ac.uk/projects/fastqc/fastqc_v0.11.4.zip && \
    unzip /home/crunch/fastqc/fastqc_v0.11.4.zip

How to build a docker image from a Dockerfile¶

docker build -t username/imagename path/to/Dockerfile/

How to upload a docker image to Arvados¶

arv keep put username/imagename

How to call an external tool from a crunch script¶

We strongly recommend using the subprocess module for calling external tools. If the output is small and written to standard out, using subprocess.check_output will ensure the tool completed successfully and return the standard output.

import subprocess
foo = subprocess.check_output(['echo','foo'])

If the output is big, subprocess.check_call can redirect it to a file while ensuring the tool completed successfully.

import subprocess
with open('foo', 'w') as outfile:
    subprocess.check_call(['head', '-c', '1234567', '/dev/urandom'], stdout=outfile)

FastQC writes to the current output directory or the output directory specified by the -o flag, so we can use subprocess.check_call

import subprocess
import arvados

#Grab the file path pointing to the file to run fastqc on 
fastq_file = arvados.getjobparam('input_fastq_file')

cmd = ['perl', '/home/crunch/fastqc/FastQC/fastqc', fastq_file]
subprocess.check_call(cmd)

Where to put temporary files

import arvados

task = arvados.current_task()
tmpdir = task.tmpdir

Inside the code:

import subprocess
import arvados

task = arvados.current_task()
tmpdir = task.tmpdir

#Grab the file path pointing to the file to run fastqc on 
fastq_file = arvados.getjobparam('input_fastq_file')

cmd = ['perl', '/home/crunch/fastqc/FastQC/fastqc', fastq_file, '-o', tmpdir]
subprocess.check_call(cmd)

How to write data directly to Keep (Using TaskOutputDir)¶

import arvados
import arvados.crunch
import os
outdir = arvados.crunch.TaskOutputDir()

with open(os.path.join(outdir.path, 'foo'), 'w') as outfile:
    subprocess.check_call(['head', '-c', '1234567', '/dev/urandom'], stdout=outfile)

arvados.task_set_output(outdir.manifest_text())

When TaskOutputDir is not the correct choice¶

• If the tool writes symbolic links or named pipes, which are not supported by fuse
• If the I/O access patterns are not performant with fuse
  • This occurs in Tophat, which opens 20 file handles on multiple files that it writes out

import arvados
import os
task = arvados.current_task()
tmpdir = task.tmpdir

os.mkdir(os.path.join(tmpdir, 'out'))

with open(os.path.join(tmpdir, 'out', 'foo.txt'), 'w') as out:
    subprocess.check_call(['head', '-c', '1234567', '/dev/urandom'], stdout=outfile)

collection_writer = arvados.collection.CollectionWriter()
collection_writer.write_file('random_file.txt')
collection_writer.write_directory_tree(os.path.join(tmpdir, 'out'))
arvados.task_set_output(collection_writer.finish())

Putting it all together¶

import subprocess

cmd = ['perl', '/home/crunch/fastqc/FastQC/fastqc']
fq_files = sorted(glob.glob('*.fq*'))
fastq_files = sorted(glob.glob('*.fastq*'))
cmd.extend(fq_files+fastq_files)
cmd.extend(['-o', outdirpath, '-t', str(num_threads)])
fastqc_pipe = subprocess.Popen(cmd)
fastqc_pipe.wait()

coll_writer = arvados.CollectionWriter()
coll_writer.write_directory_tree(outdirpath)
pdh = coll_writer.finish()

body = {'output':pdh, 'success':fastqc_pipe.returncode==0, 'progress':1.0}
arvados.api('v1').job_tasks().update(uuid=this_task['uuid'], body=body).execute()