yappi

library1.7.6pypypi✓ verified 24d ago

Yappi (Yet Another Python Profiler) is a fast, C-implemented tracing profiler for Python applications, notably supporting multithreaded, asyncio, and gevent code. It overcomes limitations of standard profilers like `cProfile` by offering per-thread CPU time analysis, on-the-fly profiling capabilities, and flexible mechanisms for filtering and sorting profiling results. The library is currently at version 1.7.6 and maintains an active release schedule.

observability

pip install yappi

github ↗package ↗

INSTALL

IMPORT

SIG · YAPPI

yappi

observabilitypythonv1.7.6

Install

1.6s avg

Import

28ms

Disk

16MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v1.7.6 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 0.028s · 18MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 1.6s · import 0.028s · 19MB

16MB installed

● package 16MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

yappi

✓ import yappi

✗ from yappi import _yappi

The `_yappi` module is an internal C implementation detail and should not be imported directly. Attempting to do so or encountering an error related to `_yappi` often indicates an installation issue.

This quickstart demonstrates how to profile a simple Python function using `yappi.start()`, executing the target code, `yappi.stop()`, and then printing function statistics. It also shows how to set the clock type (CPU or Wall time) and clear the collected stats.

import yappi import time def calculate_sum(n): total = 0 for i in range(n): total += i return total def main_task(): time.sleep(0.1) # Simulate some I/O or other work result = calculate_sum(1_000_000) time.sleep(0.05) return result # Start profiling yappi.set_clock_type("cpu") # Can be "wall" for wall time yappi.start() # Run the code to be profiled main_task() # Stop profiling and print statistics yappi.stop() # Get function statistics and print them func_stats = yappi.get_func_stats() print("Function Statistics:") func_stats.print_all( columns={0:('ncall', 5), 1:('tottime', 8), 2:('avgtime', 8), 3:('file', 30)}, sort_type='tottime' ) # Clear collected statistics yappi.clear_stats()

yappi --version

Debug

Known issues

breakingOlder versions of Yappi (pre-1.x) supported Python 2.6.x up to 3.4. Recent versions (from 1.7.0 onwards) officially support Python 3.6 and higher, including Python 3.14. Users on older Python 2 or early Python 3 versions will need to use an older Yappi release or upgrade their Python interpreter.

fix

Upgrade Python to 3.6+ or downgrade Yappi to a compatible older version if strict Python version requirements exist.

affects: <1.7.0

gotchaYappi operates as a per-interpreter resource. Attempting to run multiple Yappi profiler instances within the same Python interpreter concurrently will raise an exception.

fix

Ensure only one `yappi.start()` is active at any given time per interpreter. Use `yappi.stop()` and `yappi.clear_stats()` between profiling sessions if necessary.

affects: All

gotchaWhen interpreting profiling results, distinguish between 'tottime' and 'tsub'. 'tottime' (total time) includes time spent in sub-functions called from the profiled function, while 'tsub' (subtime) represents time spent directly within the function itself, excluding its sub-calls.

fix

Understand the definitions: `tottime` is cumulative, `tsub` is self-time. Choose the appropriate metric based on whether you want to identify bottlenecks within a function's own execution or its entire call graph.

affects: All

gotchaBy default, Yappi profiles using 'CPU time'. For I/O-bound or concurrent applications (e.g., asyncio, gevent), 'Wall time' might be more relevant to capture actual elapsed time, including waits.

fix

Explicitly set the clock type using `yappi.set_clock_type("wall")` before starting the profiler if Wall time is desired. Default is `"cpu"`.

affects: All

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'yappi'

The 'yappi' library is not installed in the current Python environment or the environment where the script is being executed.

fix

Run `pip install yappi` in your terminal to install the library.

fatal error: Python.h: No such file or directory

During installation, the C compiler cannot find the Python development headers required to build the 'yappi' C extension.

fix

On Debian/Ubuntu, install `python3-dev` using `sudo apt-get install python3-dev`. On Fedora, use `sudo dnf install python3-devel`. On macOS with Homebrew, ensure Python is installed with development headers (usually default).

error: Microsoft Visual C++ 14.0 or greater is required.

On Windows, installing 'yappi' requires a C compiler, specifically the Microsoft Visual C++ build tools, which are missing from your system.

fix

Install the Microsoft Visual C++ Build Tools from the official Visual Studio download page (look for 'Build Tools for Visual Studio') and ensure the 'Desktop development with C++' workload is selected.

AttributeError: 'YStat' object has no attribute 'save'

The `save()` method, which exports profiling data, belongs to the `YFuncStats` or `YThreadStats` collection object, not to individual `YStat` objects within that collection.

fix

Call `save()` directly on the `YFuncStats` object returned by `yappi.get_func_stats()` (e.g., `stats = yappi.get_func_stats(); stats.save('profile.txt', type='callgrind')`).

Upgrade

Version history

1.7.6latest on PyPI · released Mar 17, 2026

Audit

Dependencies

pythonrequiredRequired Python version.

Agent activity

38 hits · last 30 days

node

Amazon

OpenAI (training)

Resources

githubhttps://github.com/sumerc/yappi ↗

packagehttps://pypi.org/project/yappi/ ↗