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  1. Documentation
  2. Continuous Profiling Cookbooks
  3. Configuring Blackfire Continuous Profiler for Python

Configuring Blackfire Continuous Profiler for Python
Requires Production Plan

The Python continuous profiling is currently made across 5 dimensions:

  • CPU Time: time spent running on the CPU
  • Wall-time: elapsed time per function call
  • Heap Live Size: number of bytes allocated that are not yet garbage collected
  • Allocated memory: number of bytes allocated in memory
  • Allocations: time spent running on the CPU

Get the Blackfire Continuous Profiler Python library:

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pip install blackfire_conprof

The Python profiler API Profiler can be initiated with following options:

  • application_name: the application name.
  • period: specifies the length at which to collect CPU profiles. The default is 45 seconds.
  • upload_timeout: observability data upload timeout. The default is 10 seconds.
  • labels: a dict containing the custom labels specific to the profile payload that is sent.

The Python continuous profiler API has two functions:

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def start():
def stop():

The start function starts the continuous profiler probe. It collects profiling information in the background and periodically uploads it to the Blackfire Agent until the stop function is called.

Stops the continuous profiling probe.

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pip install blackfire_conprof
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from blackfire_conprof.profiler import Profiler

def foo():
    import time
    time.sleep(1.0)

profiler = Profiler(application_name="my-python-app", labels={'my-extra-label': 'data'})
profiler.start()
foo()
profiler.stop()
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python example.py