If you want to provide your own contrib module, please follow the instructions on the wiki page ProvideContribModules.
List of current optional contribution modules
Makeflow is a workflow manager that allows you to express complex
DAGs (Directed Acyclic Graphs) in a compact Make-like syntax and run them easily on your HTCondor pool. See http://ccl.cse.nd.edu/software/makeflow/
PyDagman is a Python package to simplify the
programmatic creation of DAG files for condor_dagman in Python.
The package is born from frustration writing one-off scripts to create
DAG files for the users I support. We regularly assist users in
creating DAG workflows to their specifications, usually by reading in
parameters from a parameter file and then programmatically building the
DAG file using loops and conditionals. This package takes care of some
of the more annoying aspects, such as string formatting and circular
dependency checking. See https://github.com/brandentimm/pydagman
htcondor_dag.py turns python functions into HTCondor jobs. It writes out a DAG (Directed Acyclic Graph) defining the individual jobs and their dependencies, ready for submission to dagman which schedules their execution across a cluster of compute nodes. See https://github.com/candlerb/htcondor_dag.py
Quill stores job history data persistently in a database and allows HTCondor tools to query the database.
HTCondor DBQ provides a relational database management system interface to HTCondor.
Drop And Compute
DropAndCompute, from the University of Manchester, is an approach to using network (or grid or cloud based) computational resources without having to know the operating system of the resource’s gateway or any command line tools. It provides and DropBox style user interface for job submission and management.
Pigeon allows queuing and forwarding of user log messages via AMQP. It consists of a broker and client tools.
An alternative SOAP API to Birdbath that uses WSO2 and Axis2/C.
An alternative API to the HTCondor scheduler based on a REST interface. CondorAgent is a program that runs beside a HTCondor scheduler. It provides enhanced access to scheduler-based data and scheduler actions via a HTTP-based REST interface. CondorAgent is deployed as either a shell script wrapped Python program (which requires Python 2.4 or greater) or as a Windows binary (which does not require a local Python installation).
A NoSQL operational data store framework that uses mongodb.
HTCondor Log Analyzer
This web site allows you to upload log files generated by the HTCondor system, and get back graphics and an explanation of what happened in the system. This can aid in understanding a workload of hundreds or thousands of jobs.
HTCondor Log Viewer
Real-time visualization of events in the job event log via a Java Swing application.
HTCondor View is used to automatically generate World Wide Web (WWW) pages displaying usage statistics of your HTCondor Pool. Included in the module is a shell script that invokes the condor_stats command to retrieve pool usage statistics from the HTCondor View server and generate HTML pages from the results. See HtcondorViewClient.
DMTCP is a third part user space checkpointing library which, through a
shim script and extra information in one's submit description file, can
checkpoint vanilla universe jobs. See: DmtcpCondor
Stork is a batch scheduler specialized in data placement and data movement, which is based on the concept and ideal of making data placement a first class entity in a distributed computing environment.
Remote HTCondor allows a user to submit and monitor batch jobs through a remote instance of HTCondor from his or her computer without having to install HTCondor locally.
CL-MW: A Master/Slave Distributed Computing Library in Common Lisp
The Hadoop Distributed File System (HDFS) is a user space, distributed file system, maintained by the Apache project. The condor_hdfs daemon is a daemon which manages the running of the java-based hdfs daemon.