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Manage job executions in a cluster

Project description

QMap is a tool aimed to run a collection of similar jobs quickly and easily in parallel. It can run standalone or using different HPC schedulers (Slurm, Sun Grid Engine and LFS).

QMap contains 5 different tools:

  • run: execute commands with extended resources

  • template: create a jobs map file

  • submit: submit jobs from a map file

  • reattach: reattach to a previous QMap execution

  • info: explore the metadata of your jobs

Documentation in:


qmap run

Execute a command with more resources maintaining your working environment

qmap run -m <memory> -c <cores>  "<command>"
qmap template

Create a jobs map file that works with qmap submit.

qmap template "<command with wildcards>" -f <jobs map file>

The file created uses the current loaded Easy Build modules and the current conda environment as jobs pre-commands [1] if not explicitly provided.

The job commands are all the combinations that result of the expansion of:


comma separated list of items


all lines in file

*, ?, [x-y]:

wildcards in Python’s glob module

Wildcards of the format {{...}} are expanded in a first phase and glob wildcards are expanded later on.

As additional feature, any of the above mentioned groups can be named {{?<name>:...}} and replaced anywhere using {{?=<name>}}.

qmap submit

Execute all jobs from a jobs map file

qmap submit -m <memory> -c <cores>  <jobs map file> --logs <logs folder> --max-running <#>

qmap submit has been implemented to submit a set of jobs to a cluster for execution and control them. It acts as a layer between the workload manager and the user preventing she/he from submitting a huge number of jobs at once (potentially blocking future users). The number of jobs that can be submitted to the workload manager is controlled by the –max-running flag.

In addition, in the folder indicated to store the logs with the –logs flag the user can find important information about each job execution as well as the logs from STDOUT and STDERR.

Another feature of this tool is the possibility to group your jobs with the –grouping option. This option uses the value passed as the number of commands that fit in each job. Thus, several commands can be executed as part of the same job, one after another. This option can be interesting for “small” jobs as they use the same allocation. If any of the commands fail, the associated job will fail.

Finally, any job command can include several values that are substituted before execution. Those values represent the job parameters and additionally, a unique identifier for each job.


identifier of the line the job command has in the input file


cores for the execution

qmap reattach

Once a qmap submit execution is closed, you can reconnect from its logs directory

qmap reattach --logs <logs folder>
qmap info

qmap submit generates a file for each job with metadata information. qmap info is designed to explore them and retrieve the requested data. Information is stored in json format and the user can request any fields:

qmap info --logs <logs folder> <field 1> <field 2>.<subfield 1> ...

In addition, the –status option can be used to filter the jobs by their status (completed|failed|other|pending|running|unsubmitted|all).

If you do not pass any field, then the return value is the input commands of the jobs. This feature can be used to generate a new jobs file a subset of the original one.

Jobs map file

This file contains a list of the commands to be executed as well as commands to be executed before and after each job (e.g. loading Easy Build modules or conda environments). The format of the file is:

# command to be executed before any job

# command to be executed after any job

# parameters for all the jobs
cores = 7
memory = 16G

job command
job command


QMap depends on Python >3.5 and some external libraries.

You can install it directly from our github repository:

pip install git+


Apache Software License 2.0.

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