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Memory Mapped Stats Tools
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Mmstats is a way to expose and read diagnostic values and metrics for applications.

Think of mmstats as /proc for your application and the readers as procps utilities.

This project is a Python implementation, but compatible implementations can be made in any language (see Goals).


  • Separate publishing/writing from consuming/reading tools
  • Platform/language independent (a Java writer can be read by a Python tool)
  • Predictable performance impact for writers via:
    • No locks (1 writer per thread)
    • No syscalls (after instantiation)
    • All in userspace
    • Reading has no impact on writers
  • Optional persistent (writer can sync anytime)
  • 1-way (Publish/consume only; mmstats are not management extensions)



CPython 2.6 or 2.7 (Windows is untested)

PyPy (only tested in 1.7, should be faster in 1.8)


  1. python install
  2. import mmstats
  3. Create a subclass of mmstats.MmStats like:
class WebStats(mmstats.MmStats):
    status2xx = mmstats.CounterField(label='status.2XX')
    status3xx = mmstats.CounterField(label='status.3XX')
    status4xx = mmstats.CounterField(label='status.4XX')
    status5xx = mmstats.CounterField(label='status.5XX')
    last_hit = mmstats.DoubleField(label='timers.last_hit')
  1. Instantiate it once per thread/process:
webstats = WebStats(label_prefix='web.stats.')
  1. Record some data:
if response.status_code == 200:

webstats.last_hit = time.time()
  1. Run slurpstats to read it
  2. Run mmash to create a web interface for stats
  3. Run pollstats -p web.stats.status 2XX,3XX,4XX,5XX /tmp/mmstats-* for a vmstat/dstat like view.
  4. Did a process die unexpectedly and leave around a stale mmstat file? cleanstats /path/to/mmstat/files will check to see which files are stale and remove them.


It's easiest to develop mmstats within a virtualenv:

$ git clone git://
$ cd mmstats
$ virtualenv .
$ source bin/activate
$ python develop
$ ./run_flask_example # This starts up a sample web app
$ curl http://localhost:5001/
$ curl http://localhost:5001/500
$ curl http://localhost:5001/status
$ # If you have ab installed:
$ ab -n 50 -c 10 http://localhost:5001/

Now to view the stats run the following in a new terminal:

$ # To get a raw view of the data:
$ slurpstats mmstats-*
$ # Or start up the web interface:
$ mmash
$ # Run pollstats while ab is running:
$ pollstats -p flask.example. ok,bad,working mmstats-*

To cleanup stray mmstats files: rm mmstats-flask-*

The web interface will automatically reload when you change source files.

Put static files into static/ and template files into templates/

TODO: Factor mmash out into it's own project (with a meaningful name?)


Feel free to use your favorite test runner like nose or pytest or just run:

$ python test

Data Structures

There are two types of data structures so far in mmstats:

  1. buffered
  2. unbuffered

Buffered structures use multiple buffers for handling values which cannot be written atomically.

Unbuffered structures have ff in the write buffer field.


label size label type size type write buffer buffers
ushort char[] ushort char[] byte varies

The buffers field length = sizeof(type) * buffers.

The current write buffer is referenced by: write_buffer * sizeof(type)

TODO: field for total number of buffers?


label size label type size type write buffer value
ushort char[] ushort char[] ff varies

The value field length = sizeof(type).

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