hupper
Integrated process monitor for developing and reloading daemons.
Decision gist · record as of 2026-08-14
Yes. Hupper is a stable, actively maintained tool with no dependencies and broad Python version support. It solves a genuine development friction point—automatic process restart on file changes—and is lightweight enough to add to any development workflow. No known security issues.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Entry point must be an importable string path; the reloader only returns in a monitored subprocess.
- Low friction installation with no runtime dependencies.
- The package is actively maintained with recent commits and supports Python 3.7 through 3.12, including PyPy.
License · maintenance · safety
MIT (permissive) — MIT license permits use in commercial and private projects with minimal restrictions; attribution required.
last release 2024-01-26 (931 days) · last repo commit 2026-08-02 · 223 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 2,877,176 downloads/mo, #2,847 on PyPI
Alternatives
Verify before relying
pip install hupper
import hupper
reloader = hupper.start_reloader('myapp.scripts.serve.main')
reloader.watch_files(['foo.ini'])- Whether watch_files() supports glob patterns or directory recursion beyond explicit file paths.
- Performance characteristics when monitoring large numbers of files or deep directory structures.
What it is and what it does
Hupper is a process monitor designed for development workflows that automatically detects changes to imported Python files and restarts the process. It tracks all modules in sys.modules plus any custom paths you specify, making it useful for iterative development where you want code changes to take effect immediately without manual restarts.
You can use it either from the command line (hupper -m myapp) or programmatically by calling start_reloader() with an importable entry point. The reloader runs as a parent process that monitors file changes and spawns child processes to run your code, allowing you to add extra files to watch via the watch_files() method. It has no runtime dependencies and supports modern Python versions from 3.7 onward.
Use it for
- Developing web applications where you want the server to reload automatically when you edit source files.
- Running long-lived daemons during development and having them pick up code changes without manual restarts.
- Monitoring configuration files alongside Python source and triggering restarts when either changes.
- Building development scripts that need to reload when dependencies or imported modules are modified.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Hupper is a stable, actively maintained tool with no dependencies and broad Python version support. It solves a genuine development friction point—automatic process restart on file changes—and is lightweight enough to add to any development workflow. No known security issues.
Install
hupper on PyPI
Before you install
Low friction installation with no runtime dependencies. The package is actively maintained with recent commits and supports Python 3.7 through 3.12, including PyPy.
Entry point must be an importable string path; the reloader only returns in a monitored subprocess.
License in practice
MIT license permits use in commercial and private projects with minimal restrictions; attribution required.
Quickstart
pip install hupper
import hupper
reloader = hupper.start_reloader('myapp.scripts.serve.main')
reloader.watch_files(['foo.ini'])
Verify before relying
- Whether watch_files() supports glob patterns or directory recursion beyond explicit file paths.
- Performance characteristics when monitoring large numbers of files or deep directory structures.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.7 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 931 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 2,877,176 / month, #2,847 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseNatural Language :: EnglishProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPy |
Evidence: hupper-1.12.1-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “process monitor file watcher”
- hupperHupper monitors Python source files for changes and automatically…
- watchfilesWatches file system changes and triggers callbacks or process…
- kantokuKantoku runs and watches multiple processes and sockets, providing…
Give your agent the search over MCP, or paste the wish link into any chat.
More Monitoring packages
Wraps any iterable to display a real-time progress bar in the terminal or Jupyter notebook, showing iteration count, elapsed time, and estimated time remaining.
Provides generated Python code for OpenTelemetry semantic conventions, enabling standardized attribute naming and constant definitions for instrumentation and telemetry collection.
Install it if you are using OpenTelemetry and want to follow semantic conventions correctly.
Provides the reference implementation of the OpenTelemetry API for collecting and exporting traces, metrics, and logs from Python applications.
Provides the abstract API and interfaces for OpenTelemetry instrumentation in Python, defining how to emit traces, metrics, and logs without tying code to a specific SDK implementation.
Exports OpenTelemetry observability data to an OpenTelemetry Collector using Protobuf-encoded messages over HTTP.
Install it if you are using OpenTelemetry in Python and need to send data to a Collector over HTTP.
Provides automatic instrumentation commands and programmatic APIs to inject distributed tracing into Python applications without code changes, detecting and instrumenting packages used by your program.
Install it if you need distributed tracing without code changes and have compatible instrumented packages in your environment.
See also watchgod · setproctitle · pyinotify · httpwatcher · watchfiles · pywatchman · pytest-watcher · aiousbwatcher · jupyter-server-fileid · uwsgitop