Containerisation practice

Lets build an image to run the following python script on the HPC. You will need to pull the latest python image, you also need to install the pandas and numpy packages to run the following script.

Save it as python_primes_np.py

import pandas as pd
import numpy as np


lower = 2
upper = 5000

df = []

for num in range(lower, upper + 1):
    if num == np.nan:
        print("One of the values you provided is not a number")
        exit()
    # all prime numbers are greater than 1
    if num > 1:
        for i in range(2, num):
            if (num % i) == 0:
                break
        else:
            df.append(num)
pd.DataFrame(df).to_csv('python_primes.csv')

Pull a singularity image to run python_primes_np.py. You will also need a relevant scheduler script.

Solution

I’ve found the following image on the docker repository https://hub.docker.com/r/amancevice/pandas

First pull the image

name@name-VirtualBox:~/Documents/singularity/images$ singularity pull --name python_primes docker//:amancevice/pandas

Run the image locally

name@name-VirtualBox:~$ singularity exec python_primes python python_primes_np.py

If it worked, you should have a csv file called python_primes.csv

Now you will need to create a PBS scheduler script to run your singularity image on ther HPC. Save the following scheduler script as scheduler.sh

#!/bin/bash -l
#PBS -m abe
#PBS -M yourEmail@griffith.edu.au
#PBS -V
#PBS -N TestContainer
#PBS -q workq
#PBS -l select=1:ncpus=1:mem=2gb,walltime=0:05:00
cd  $PBS_O_WORKDIR

module load singularity                 # load singularity
singularity run python_primes.sif     # add the following bash command so that singularity executes the image during runtime

Build a singularity image from a singularity definitions file to run python_primes_np.py

Solution

The following definition script should be saved as python_np_pd.def

Bootstrap: docker
From: ubuntu:18.04

%post
    apt-get update 
    apt-get -y install python3 
    apt-get -y install python3-pip 
    pip3 install pandas:1.2.0
    pip3 install numpy:1.19.4 
    
    rm -rf /var/lib/apt/lists/* 

%labels # these are labels that will appear when someone inspects the singularity image
    Author eResearch Griffith University
    Version v0.0.1

%help
    This image is built using ubuntu 18.04 OS. It installs python3.8, pandas1.2.0 and numpy 1.19.4. 
    A python script is included that calculates all prime number up to 5000 and writes then in a csv output called python_primes.csv
    Use the singularity run command 

%files
    python_primes_np.py

%runscript
    python3 /python_primes_np.py

Now build a singularity image from the definitions file

name@name-VirtualBox:~/Documents$ sudo singularity build python_np_pd.sif python_np_pd.def

Now we have a singularity image called python_np_pd.sif

Use docker to pull an image and then convert it to a singularity image that will run python_primes_np.py

This exercise is only for people who know how to use docker. It does not do anything that singularity cannot alread do. Have a look on the docker repository for a suitable image

Solution

Lets find a docker image with python, pandas and numpy and pull it using docker. I looked on docker and found this image: https://hub.docker.com/r/amancevice/pandas. So I will pull it, -slim means that I will pull a smaller version of python. This image should contain numpy. This is because pandas is reliant on numpy and will install it when pandas is installed.

name@name-VirtualBox:~$ docker pull amancevice/pandas:1.2.0-slim
1.2.0-slim: Pulling from amancevice/pandas
6ec7b7d162b2: Pull complete 
a28a49c1de56: Pull complete
.......

name@name-VirtualBox:~$ docker image ls
REPOSITORY                               TAG                   IMAGE ID       CREATED         SIZE
quay.io/singularity/docker2singularity   latest                e07682c30060   6 days ago      407MB
amancevice/pandas                        1.2.0-slim            5d6c6e32c6ab   3 weeks ago     247MB
continuumio/miniconda3                   latest                52daacd3dd5d   6 weeks ago     437MB

Then run the docker to singularity image.

docker run -v /var/run/docker.sock:/var/run/docker.sock -v ~/Documents/HPC:/output quay.io/singularity/docker2singularity --name pandasprimes amancevice/pandas:1.2.0-slim
Image Format: squashfs
Docker Image: amancevice/pandas:1.2.0-slim
Container Name: pandasprimes

Inspected Size: 247 MB

(1/10) Creating a build sandbox...
.......

You now have a singularity image named pandasprimes.sif

Make a PBS scheduler script to run the your image

Solution

You will need to create a PBS scheduler script to run your singularity image. Save the following scheduler script as scheduler.sh

#!/bin/bash -l
#PBS -m abe
#PBS -M yourEmail@griffith.edu.au
#PBS -V
#PBS -N TestContainer
#PBS -q workq
#PBS -l select=1:ncpus=1:mem=2gb,walltime=0:05:00
cd  $PBS_O_WORKDIR

module load singularity                 # load singularity
singularity run pythonContainer.sif     # add the following bash command so that singularity executes the image during runtime

upload the singularity image and pbs scheduler script to the HPC and run it

Solution

Copy the

s1234567@PC12345 XXXX~$ scp -r directory/on/local/computer/ s1234567@clogin1.rcs.griffith.edu.au:~

Log into the HPC

s1234567@PC12345 XXXX~$ ssh s1234567@clogin1.rcs.griffith.edu.au

[s1234567@clogin1.rcs.griffith.edu.au ~]$

Check that you are in your working directory, then list the files that are there. Make sure that the files from the previous step are there.

[s1234567@clogin1.rcs.griffith.edu.au ~]$ ls
prime_numbers.py   scheduler.sh

Run the job

[s1234567@clogin1.rcs.griffith.edu.au ~]$ qsub scheduler.sh
49243.gc-prd-hpcadm
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