2/17/2024 0 Comments Python queue to list fast![]() dat files and wanted to create a separate job for each one, you could use the command queue INPUTFN matching files *.dat. Here, you can use wildcards to get HTCondor to automatically construct the list for you. This method of creating a list of input files is particularly convenient because it doesn’t require you to manually list entries, or to define exactly how many files there are, as the previous methods have. For example, you could use:įiles or directories from a filesystem: queue matching Multiple variables defined from a list: queue from | Įxpanding on the previous option, you can define multiple variables using the from syntax. ![]() In this example, $(Step) would run from 0 to 3 for jobs with a $(MagnetPolarity) value of up, and again from 0 to 3 for the down value. You can use another automatically-defined variable, $(Step), to get the index of the jobs for each list element individually. 4 for up, and 4 for down, and the variable $(ProcessId) would run from 0 to 7. If you were to instead run queue 4 MagnetPolarity in (up,down), a total of 8 jobs would be created, i.e. By default, its value is 1, meaning that one job is created for each list entry. It’s worth noting that the optional parameter represents the number of jobs to create per element in the list. For example, you could use queue MagnetPolarity in (up,down) to automatically create two jobs, each with a variable $(MagnetPolarity) defined, which can then be used elsewhere in the submit file to pass either up or down to other options. This defines a variable name and lets you give it a list of values, and HTCondor will create separate jobs for each value in the list. For more information and other examples, you can visit the documentation for the queue command. This part of the lesson showcases some of these options and how to use them. Fortunately, the queue command is extremely flexible and has many alternative choices of syntax. The above syntax for queuing multiple jobs is very simple and convenient for jobs with sequential enumeration starting from zero, but this isn’t always the case. Transfer_input_files = my_script.py, input/$(INPUTFN) Using this, you can modify your submit file to read: These variables are automatically-defined for each job individually. We can do this using the variables $(ClusterId) and $(ProcId) (or, equivalently, $(Cluster) and $(Process) respectively). In order to fix these issues, we need to be able to distinguish each job created by a single submit file. Secondly, once the jobs have all completed, notice that you only have one output.out file - each time one completes, it overwrites any existing output file with its own output because each one has the same name. Firstly, we’re running the exact same job (with the exact same input) multiple times, which is rarely what is needed. There are a couple of issues with the above script. In almost all cases, when you submit multiple jobs using a single queue command, they will share the same cluster ID, and have sequential process IDs starting from 0. In particular, note that all of these jobs have the same cluster ID, but each has a different process ID ranging from 0 to 3. This shows a bit more information about the jobs than the standard condor_q. Getting the required files and certificates.Creating a grid proxy without LbScripts.Alternative Backends - DIRAC (Python bugged).Exploring a TCK: Properties of trigger lines.Add trigger information to your ntuple, continued.Finding Constants Used in an Existing MC Sample (Masses/Lifetimes/etc).Changing particle masses / lifetimes/ widths.Running Gauss and create a generator-only sample.Which option files to use and how to run Gauss.Run a different stripping line on simulated data.Useful high energy physics analysis tools.The analysis flow and analysis preservation.
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