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Pyroscope:如何在Python客户端中使用py-spy的--native、--idle等配置项

How to Use py-spy Flags Like --native and --idle with Pyroscope Python Client

Great question! I’ve dealt with this exact issue when trying to unlock py-spy’s more advanced features through the Pyroscope Python client. The official configure() method doesn’t expose these low-level py-spy flags directly, but there’s a straightforward workaround using environment variables.

Here’s what you need to do:

1. Use the PYROSCOPE_PYSPY_FLAGS Environment Variable

Pyroscope’s Python client checks this environment variable at startup to pass additional flags directly to the underlying py-spy process. You can set it either before launching your app, or within your code (just make sure you do it before importing pyroscope).

Option A: Set it in your shell before running the app

PYROSCOPE_PYSPY_FLAGS="--native --idle" python your_application.py

Option B: Set it programmatically in your Python code

import os
# Set the flags BEFORE importing pyroscope
os.environ["PYROSCOPE_PYSPY_FLAGS"] = "--native --idle"

import pyroscope
pyroscope.configure(
    application_name="my.python.app",
    server_address="http://your-pyroscope-server:4040"
)

2. Verify the Flags Are Applied

To make sure your flags are being used, you can:

  • Check the running processes (use ps aux | grep py-spy to see the full command line, which should include --native and --idle)
  • Enable debug logging in Pyroscope to see the exact py-spy command being executed:
    pyroscope.configure(
        application_name="my.python.app",
        server_address="http://your-pyroscope-server:4040",
        log_level="debug"
    )
    
    Look for log lines mentioning the py-spy invocation—you’ll see your custom flags included there.

3. Keep Compatibility in Mind

While most py-spy flags work with Pyroscope, be cautious with flags that modify core behavior like sampling rate (--rate) or output format. Pyroscope relies on specific py-spy output conventions, so stick to flags that don’t alter how profiling data is generated or structured (like --native, --idle, --gil, etc.).

内容的提问来源于stack exchange,提问作者Pouria Nikvand

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最近更新时间:2026.04.29 00:17:39