Traditional methods of threads and synchronous I/O have some drawbacks, especially with Python due to global interpreter lock (GIL). This approach is not suited for large number of concurrent connections, known as C10K problem. In addition, threads in Python have both memory and time overheads, especially on multi-core systems due to context switches; see Inside the Python GIL.
There are now many asynchronous frameworks that address these problems, that usually provide event loop mechanism and callbacks. Programming with such framework requires careful retooling of the application logic, similar to using GOTO statements.
Unlike with those frameworks, using pycos is very similar to the thread based programming so there is almost no learning curve (as far as asynchronous programming is concerned) - existing thread implementations can be converted to pycos almost mechanically (although it cannot be automated). In fact, it is easier to use pycos than threads, as locking is not required with pycos.
For example, a simple client program to send messages using sockets with pycos is:
import sys, socket, pycos def client(host, port, n, task=None): sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) # convert 'sock' to asynchronous socket sock = pycos.AsyncSocket(sock) yield sock.connect((host, port)) data = 'client id: %d' % n yield sock.sendall(data) sock.close() # run 10 client tasks for i in range(10): pycos.Task(client, sys.argv, int(sys.argv), i)
The pgrogram creates 10 tasks; each task process converts socket to asynchronous socket with Asynchronous Socket, connects to server and sends a message. In the tasks, socket I/O operations are called with yield (with connect and sendall here). With these statements, the I/O operation is initiated, the task is suspended and control goes to pycos’s scheduler for scheduling other tasks as well as processing I/O events. When an I/O operation is complete, the scheduler resumes the suspended task with the results of the I/O operation. During the time it takes to complete an I/O operation, the scheduler executes other tasks, so many requests can be concurrently processed. Thus, with pycos yield is similar to system calls in Unix-like kernels.
Note that the above program is similar to regular Python program, except for
using yield and creating processes with Task (instead of
threading.Thread). Unlike with other asynchronous frameworks, the I/O
event loop in pycos is transparent - pycos’s scheduler handles I/O events
automatically. If task method has
task=None default argument, the task
constructor Task will set this
task argument with the Task instance,
which can be used for calling methods in Task class (e.g.,
task.sleep(2) to suspend execution for 2 seconds).
pycos package conists of following modules:
pycosmodule provides API for tasks and asynchronous network programming. It includes following classes:
- Task to create tasks, which are counterpart to threads in regular (synchronous) programs. Programming with tasks is very similar to programming with threads, except for a few differences. Tasks also support message passing for local or remote tasks to exchange information.
Conditionprimitives provide asynchronous API similar to counterparts in threading module. Blokcing operations in these primitives should be used with yield.
- Asynchronous Socket should be used to convert regular (synchronous) socket to asynchronous socket, as done in the example above. Blocking operations, such as connect, send, recv etc. should be used with yield.
- Channel provides broadcasting (one-to-many, subscription based) API for message passing.
netpycosmodule extends Pycos scheduler and Task, Channel etc. so the API works for remote tasks, channels etc. In addition, it provides Location used to refer to resource location and RTI (Remote Task Invocation) to execute (predefined) tasks.
dispycosmodule provides Computation to package computation fragments (code) and data to be scheduled for executing at remote server processes with Pycos. The client program can then schedule (remote) tasks to be executed. These tasks and client can use message passing to exchange data. The remote servers should be started with
asyncfilemodule provides Asynchronous File and Asynchronous Pipe for converting files and pipes to asynchronous API. Blocking operations on these should be used with yield, as with sockets.
pycos has been tested with Python versions 2.7 and 3.2 under Linux, OS X and Windows. Under Windows pycos uses IOCP only if Python for Windows Extensions (pywin32) is installed. pywin32 works with Windows 32-bit and 64-bit.