Flask-DebugToolbar
A toolbar overlay for debugging Flask applications.
Decision gist · record as of 2026-08-14
Yes. Flask-DebugToolbar is a low-friction, actively maintained development tool with no security vulnerabilities, a permissive license, and a single dependency. It is worth installing for any Flask project in active development where visibility into request handling and template rendering would aid debugging.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Flask debug mode must be enabled for the toolbar to inject into templates; typically run with `flask run --debug`.
- Low install friction with a single runtime dependency on flask.
- The project is actively maintained as part of the Pallets Community Ecosystem, with recent commits and a stable release cadence.
License · maintenance · safety
permissive license (permissive) — Licensed under a permissive BSD license, allowing use in both open-source and proprietary projects without significant restrictions.
last release 2024-09-28 (685 days) · last repo commit 2026-08-03 · 978 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,330,386 downloads/mo, #4,048 on PyPI
Alternatives
Verify before relying
from flask import Flask
from flask_debugtoolbar import DebugToolbarExtension
app = Flask(__name__)
app.config["SECRET_KEY"] = "your-secret-key"
toolbar = DebugToolbarExtension(app)- What specific debugging information panels are available (e.g., SQL queries, cache, headers, profiling).
- Whether the toolbar works with all Flask template engines or only Jinja2.
- Performance impact when the toolbar is active on production-like workloads.
What it is and what it does
Flask-DebugToolbar is a Flask extension that automatically injects a sidebar overlay into HTML pages during development, showing debugging information about the current request and application state. It is designed as a port of Django's debug toolbar and integrates seamlessly with Flask's debug mode, requiring only a few lines of setup code to enable.
The toolbar displays configurable panels of diagnostic data and is injected directly into Jinja templates when debug mode is active. It helps developers inspect requests, view template context, and understand application behavior during development without requiring external tools or manual instrumentation.
Use it for
- Inspect HTTP request and response details, headers, and cookies during development.
- Debug Jinja template rendering and view the context variables passed to templates.
- Monitor database queries and other instrumented operations in real time.
- Profile application performance and identify bottlenecks during development.
- Understand Flask configuration and extension state without adding print statements.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Flask-DebugToolbar is a low-friction, actively maintained development tool with no security vulnerabilities, a permissive license, and a single dependency. It is worth installing for any Flask project in active development where visibility into request handling and template rendering would aid debugging.
Install
flask-debugtoolbar on PyPI
Before you install
Low install friction with a single runtime dependency on flask. The project is actively maintained as part of the Pallets Community Ecosystem, with recent commits and a stable release cadence.
Flask debug mode must be enabled for the toolbar to inject into templates; typically run with `flask run --debug`.
License in practice
Licensed under a permissive BSD license, allowing use in both open-source and proprietary projects without significant restrictions.
Quickstart
from flask import Flask
from flask_debugtoolbar import DebugToolbarExtension
app = Flask(__name__)
app.config["SECRET_KEY"] = "your-secret-key"
toolbar = DebugToolbarExtension(app)Verify before relying
- What specific debugging information panels are available (e.g., SQL queries, cache, headers, profiling).
- Whether the toolbar works with all Flask template engines or only Jinja2.
- Performance impact when the toolbar is active on production-like workloads.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packageflask |
| Maintenance | Actively maintained 685 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 1,330,386 / month, #4,048 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaFramework :: FlaskLicense :: OSI Approved :: BSD LicenseProgramming Language :: PythonTyping :: Typed |
Evidence: flask_debugtoolbar-0.16.0-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 › “flask debug toolbar”
- Flask-DebugToolbarFlask-DebugToolbar injects a debugging sidebar into rendered HTML…
- pyramid-debugtoolbarPyramid_debugtoolbar injects an interactive HTML debug toolbar into…
- django-debug-toolbar-template-timingsA Django Debug Toolbar panel that measures and displays the time…
Give your agent the search over MCP, or paste the wish link into any chat.
More Testing packages
Pluggy provides a plugin system that lets you define hook specifications and register implementations to be called in sequence, enabling extensible Python applications without tight coupling.
Install it if you're building an extensible application or framework.
pytest is a testing framework that lets you write test functions using plain assert statements and automatically discovers and runs them, with detailed failure reporting.
virtualenv creates isolated Python environments where packages can be installed independently without affecting the system Python or other projects.
Coverage.py measures which lines of Python code are executed during test runs, reporting coverage percentages and identifying untested code paths.
Install it if you want to measure test completeness or enforce coverage thresholds in your project.
pytest-asyncio is a pytest plugin that enables writing and running async test functions using the asyncio library, allowing developers to await code directly within test cases.
Install it if you write tests for any asyncio-based code.
A pytest plugin that generates test reports in Common Test Report Format (CTRF) as JSON, compatible with pytest-xdist and pytest-playwright for distributed and browser-based testing.
Install it if you need CTRF-formatted test output for CI/CD integration or cross-tool reporting.
See also aiohttp-debugtoolbar · django-debug-toolbar · debug-mgr · django-debug-toolbar-template-timings · django-graphiql-debug-toolbar · django-debug-toolbar-template-profiler · pyramid-debugtoolbar · Flask-Mail · djdt-flamegraph · Flask-Caching