[Twisted-Python] Twisted Logging?
paul at ref.nmedia.net
Thu Mar 10 17:37:25 EST 2005
> The whole thing becomes a workflow manager that collects information about processed newspaper pages. I'm planning to connect several modules (running on different machines) with PB. The server will handle a database connection and perhaps cache some data that the clients might request. Later the server will provide some status information via http (praise twisted).
> One part is an Acrobat Distiller wrapper (via win32com.client):
> I created a library with makepy and implemented an event handler class that catches Distiller's events, e.g. "OnJobStart".
> That handler class is inherited from a base class by makepy. Each event calls one predefined method.
> The handler class is connected with the distiller class like
> dist = acrobatdistiller.PdfDistiller()
> win32com.client.WithEvents(dist, DistEventHandler)
> There can be only one Distiller instance. I guess I should keep that as long as possible, for several files to distill.
> -> How should I handle these events with twisted? Do I need multiple inheritance to inherit my handler also from some twisted class?
This problem has come up before. Basically, you need to queue up your series
of commands and then send them one at a time. Obviously, blocking is a bad
thing. In this case, your PDF handler can be isolated into a separate
process and/or thread. Twisted supports this. Read the threading stuff
very carefully. The threading support has specific hooks designed to run a
process in just this situation.
So architecturally, you'd have your PDF application running in a thread. Every
time it finishes a job, it sends a signal over to the twisted code signalling
that the job is complete. The twisted code then schedules another one on an
On the twisted side, you can write a server. The server either queues a job
or sends it immediately. Either way, it can return immediately and it won't
be a problem blocking-wise since the time to execute the code is minimal (you
hid all the blocking stuff in the side-thread where your PDF driver runs).
The "return" function essentially is either an outright "pull a command out
of the queue and send it over" function or you could set it up as a
> Before a PostScript file gets distilled [dist.FileToPDF(source, target, joboptions)], I must patch it (write some pdfmarks into it). I guess I should use a thread for those blocking operations (distilling can take several minutes).
> -> One thread for both, just work blocking?
This can be in your threaded code as mentioned earlier since it's all one
> -> Do I need a thread for every copy/move operation (large files via network)?
Nope. That's the beauty of twisted code. I've written this sort of handling
multiple packet trains many times. Write a protocol. There are two ways to
do this. First, you can write one protocol per file transfer. The factory
sets up the protocol to do the file transfer. At the end of the file, the
protocol then saves the file to disk and tears down the connection. Then
on return to the factory, the factory can call the code to write the PDF
file. The protocol code simply shovels the data from the network to a file.
As each packet arrives, it executes for a short period of time before
returning (which releases control back to the reactor). No blocking is
necessary at all. The protocol itself will be little more than a modification
of the Echo example protocol except you may want to add some headers or
something to send a file size and/or CRC to make sure that the file comes
> Another part reads some XML files (using minidom) and writes the mangled content into a database.
> I guess I can't split XML parsing into smaller non-blocking portions -> one thread for every file?
I ran into long processing problems before. There's a simple solution. Pick
something convenient such as simply chunking everything up into processing one
line at a time. Store your state in a "utility class". A utility class is
something like this:
Then you can store anything you want. First, initialize it:
storage = Utility()
Then attach whatever data you need for your state:
storage.data = something
storage.header = something else.
Then, whenever you want to chunk your code into discrete steps, simply pass
it along in a chain of functions, each one ending with:
reactor.calllater(0.0001, nextstep, storage)
The functions will look like:
There are some other ways of handling this. You can get really creative with
your constructs using deferreds. And the Flow module allows you to go even
further than the hard coded version I'm suggesting here. Try reading through
the Flow module documentation. Just don't get hung up about using it. For my
purposes, it was usually better just to have the basic concept in mind than
to actually use Flow.
> For the database stuff I'm using runInteraction, seems to be the best solution.
Yep. Frequently, this is where I'd run a deferred() just after sending the
request to the known-to-be-slow process. Read that section carefully too. Then
your code gets called back immediately when the process completes. You will
need to understand deferred's to fully utilize twisted's threading interface,
and then you'll realize that you probably don't need threads.
> A general issue is logging. I'm used to log4perl/log4net (same as log4j from apache), but dropped log4py in favour of the similar Python 2.3 standard logging. I already asked in my last mail to this list how I can integrate that with twisted.
> -> Is it possible to get correct linenumbers if using deferreds? Or can I trust logging to be non-blocking?
Deferred's work fine. It's just a programming construct that is a work-around
for a lack of a real continuation. On the other hand, deferred's are much
easier to use than continuations. The code seems VERY unnatural to write at
first but once you get used to it, deferred's seem just well...obvious.
As to logging itself...it might be easier to just write your own. Usually I
haven't been overly thrilled with the mechanical-looking output of
off-the-shelf loggers and logging is little more than just printing to a file
anyways, sometimes with some extra (chop it up and reclaim space) features
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