Python Error and Performance Monitoring

Actionable insights to resolve Python performance bottlenecks and errors. See the full picture of any Python exception so you can diagnose, fix, and optimize performance in the Python debugging process.

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Grab the Sentry Python SDK:

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pip install --upgrade sentry-sdk

Configure your DSN:

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import sentry_sdk

sentry_sdk.init(
    "https://<key>@sentry.io/<project>",

    # Set traces_sample_rate to 1.0 to capture 100%
    # of transactions for Tracing.
    # We recommend adjusting this value in production.
    enable_tracing=True,
    traces_sample_rate=1.0,
)

Getting Started is Simple

Grab the Sentry Python SDK:

Click to Copy
pip install --upgrade sentry-sdk

Configure your DSN:

Click to Copy
import sentry_sdk

sentry_sdk.init(
    "https://<key>@sentry.io/<project>",

    # Set traces_sample_rate to 1.0 to capture 100%
    # of transactions for Tracing.
    # We recommend adjusting this value in production.
    enable_tracing=True,
    traces_sample_rate=1.0,
)

Check our documentation for the latest instructions.

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How to install the Python SDK

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Python Performance Monitoring

Within minutes after installing Sentry, software teams are able to trace Python performance issues back to a poor performing API call as well as surface all related code errors. Engineering Managers and Developers now have a single tool to optimize the performance of their code and deliver fast customer experiences.

Python Error Monitoring with Complete Stack Traces

See local variables in the stack for prod errors, just like in your dev environment. Introspect more deeply into the runtime and jump into the frame to get additional data for any local variable. Filter and group Python exceptions intuitively to eliminate noise.

Fill In the Blanks About Python Errors

Expose the important events that led to each Python exception: SQL queries, debug logs, network requests, past errors. Improve debugging workflow with a full view of releases so you can mark errors as resolved and prioritize live issues.

Python Profiling

Profiling lets you see what parts of your code are consuming the most resources, like CPU or memory, in your application— so you can optimize them before end user experience is impacted. Test your application performance in any environment, including in production, without writing manual tests or extensive troubleshooting.

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Understand Where Tests Could Prevent Your Python Regressions

Quickly isolate Code Coverage for Python bugs to see where testing could help fix the bug before release with our Codecov integration.

Learn More About Codecov by Sentry

”The time to resolve errors went from days to minutes.”

Vaidik Kapoor
VP of Engineering at Grofers

Debugging Any Python Exception

Aggregate errors by details like HTTP request, hostname, and app version to see what’s new, a priority, or a trend.

Assign custom tags to reproduce the error environment specific to your application, business, and users.

Answer the most important questions: In which app release did the Python bug occur? Was it the kraken?

FAQs

Traditional logging provides you with a trail of events. Some of those events are errors, but many times they’re simply informational. Sentry is fundamentally different because we focus on exceptions, or in other words, we capture application crashes. We discuss in more detail here and on our blog.

Sentry supports every major language, framework, and library. You can browse each of them here.

You can get started for free. Pricing depends on the number of monthly events, transactions, and attachments that you send Sentry. For more details, visit our pricing page.

Sentry doesn’t impact a web site’s performance.

If you look at the configuration options for when you initialize Sentry in your code, you’ll see there’s nothing regarding minimizing its impact on your app’s performance. This is because our team of SDK engineers already developed Sentry with this in mind.

Sentry is a listener/handler for errors that asynchronously sends out the error/event to Sentry.io. This is non-blocking. The error/event only goes out if this is an error.

Global handlers have almost no impact as well, as they are native APIs provided by the browsers.

Supporting Resources

Debugging Python Errors

How Sentry Helps Grofers Meet Unprecedented Delivery Demand

Resolve Python errors with max efficiency, not max effort

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