Threadly is a threadpool/scheduler for python. It allows execution of function pointers for easy periodic task scheduleing, keyed execution, or just regular thread pooling.
This project is loosely based off the java Threadly threadpool library threadly.org.
##Documentation:
Documentation can be found here
##Basics:
Threadly is very easy to use. Here are some basic examples.
importthreadlydeftestFoo():
print"Thread %s Executed"%(threading.current_thread())
executor=threadly.Scheduler(10) #starts a thread pool with 10 threads#this will Execute a task in 100 msexecutor.schedule(testFoo, delay=100)
#this will Execute a task every second until removedexecutor.schedule(testFoo, delay=1000, recurring=True)
#these execute the task asapexecutor.execute(testFoo)
executor.execute(testFoo)
executor.execute(testFoo)
#this will run a task, any other tasks using the same key will be executed as though they are single threadedexecutor.schedule(testFoo, key="someObject")
#this removes/stops the first scheduled task for this callable, if it was recurring it will no longer beexecutor.removeScheduled(testFoo)
#this shuts down the threadpoolexecutor.shutdown()##Clock:
Threadly has a Clock class. This is used to make getting time from multipule threads often a little more efficient. It is a singleton and only one can ever exist. It keep 100 millisecond resolution, but can be more accurate if needed.
fromthreadlyimportClockc=Clock()
#this outputs the time in millis. Note this is an int/long not a floatprintc.last_known_time_millis()
#this outputs time like time.time() as a float where everything less then 1 is less then a secondprintc.last_known_time()
#This gets accurate time, just like time.time()printc.accurate_time()NOTE: There is an __stop() function but it should only be used if you know what your doing as it will stop the clock updating thread, and since there is only one instance it stops for everyone.