Upsun User Documentation

Continuous profiling for Python

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Feature Availability

By default, Upsun offers 15 minutes of continuous profiling per project and for free. To get 30 days of continuous profiling per project and for a fixed fee, upgrade to the Continuous Profiling add-on.

Upsun Continuous Profiler is powered by Blackfire. It is available directly from the Console, under the Profiling tab of your environments.

The PHP continuous profiling is currently made across 4 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

The default sampling frequency is 100 Hz. This means the Python continuous profiler is collecting information 100 times per second.

Prerequisites Anchor to this heading

Upsun Continuous Profiler requires Python >=3.7.0.

Installation Anchor to this heading

The Blackfire Continuous Profiler Python library is included by default in all Python images matching its requirements. There is no installation required.

Python continuous profiler API Anchor to this heading

The Python profiler API (profiler) can be initiated with the 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:

def start():
def stop():
Function Description
def start(): 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.
def stop(): Stops the continuous profiling probe.

Example Anchor to this heading

Here is an example of how you can initiate the Python profiler on a basic app:

  1. Create with the following code:

    def foo():
        import time
    profiler = Profiler(application_name="my-python-app", labels={'my-extra-label': 'data'})
  2. Run the app:


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