TGScheduler
Pure Python Scheduler
Decision gist · record as of 2026-08-14
No. While TGScheduler has no dependencies and a permissive license, it has been abandoned for over 11 years with no maintenance, security updates, or verified compatibility with modern Python versions. For any production or long-term use, choose an actively maintained alternative like APScheduler. Only consider it for legacy TurboGears 1 projects or short-lived prototypes where the lack of maintenance is acceptable.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Package requires 'six' for Python 2/3 compatibility but has not been maintained since 2015; compatibility with modern Python versions is unverified.
- Installation is straightforward with no runtime dependencies.
- However, the package has been abandoned since 2015 and has not received updates for over 11 years, which means no bug fixes, security patches, or compatibility improvements for modern Python versions.
License · maintenance · safety
MIT (permissive) — Licensed under MIT (permissive), so you can use, modify, and distribute the package freely with minimal restrictions.
last release 2015-05-18 (4106 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 108,369 downloads/mo, #12,560 on PyPI
Alternatives
Verify before relying
pip install TGScheduler
from tgscheduler.scheduler import Scheduler
scheduler = Scheduler()
scheduler.add_interval_task(action=my_function, taskname='mytask', minutes=5)- Whether TGScheduler works reliably on Python 3.10+ without modification or workarounds.
- Whether the package's thread and process forking mechanisms are safe for concurrent use in modern applications.
- Whether there are known issues or incompatibilities with current dependency versions.
What it is and what it does
TGScheduler is a lightweight, dependency-free scheduler for Python applications that need to run tasks on a schedule. It originated from TurboGears 1's built-in scheduler and supports three execution modes: in-process threading, forked processes, or synchronous execution. The scheduler is designed to handle both one-time and recurring tasks with a simple API.
The package is pure Python with no external runtime dependencies, making it easy to integrate into existing applications. However, it has been abandoned since 2015 and receives no active maintenance, meaning it lacks updates for modern Python versions, security patches, or bug fixes. The lack of maintenance is a significant concern for production use.
Use it for
- Schedule periodic maintenance tasks or data cleanup jobs to run at fixed intervals within a Python application.
- Run background tasks asynchronously in separate threads without introducing a heavy external scheduler dependency.
- Execute one-time delayed tasks or cron-like jobs in simple applications that do not require a full job queue system.
- Prototype or test scheduling logic in development before migrating to a maintained scheduler like APScheduler or Celery.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
No.
While TGScheduler has no dependencies and a permissive license, it has been abandoned for over 11 years with no maintenance, security updates, or verified compatibility with modern Python versions. For any production or long-term use, choose an actively maintained alternative like APScheduler. Only consider it for legacy TurboGears 1 projects or short-lived prototypes where the lack of maintenance is acceptable.
Install
tgscheduler on PyPI
Before you install
Installation is straightforward with no runtime dependencies. However, the package has been abandoned since 2015 and has not received updates for over 11 years, which means no bug fixes, security patches, or compatibility improvements for modern Python versions.
Package requires 'six' for Python 2/3 compatibility but has not been maintained since 2015; compatibility with modern Python versions is unverified.
License in practice
Licensed under MIT (permissive), so you can use, modify, and distribute the package freely with minimal restrictions.
Quickstart
pip install TGScheduler
from tgscheduler.scheduler import Scheduler
scheduler = Scheduler()
scheduler.add_interval_task(action=my_function, taskname='mytask', minutes=5)Verify before relying
- Whether TGScheduler works reliably on Python 3.10+ without modification or workarounds.
- Whether the package's thread and process forking mechanisms are safe for concurrent use in modern applications.
- Whether there are known issues or incompatibilities with current dependency versions.
Package facts
| License | MIT permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Abandoned 4,106 days since the last release |
| First released | |
| Downloads | 108,369 / month, #12,560 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/StableLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: PythonTopic :: Software Development :: Libraries :: Python Modules |
Evidence: TGScheduler-1.7.0-py2-none-any.whl; TGScheduler-1.7.0-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 › “python task scheduler”
- TGSchedulerTGScheduler is a pure Python task scheduler that runs one-time or…
- celery-redbeatRedBeat is a Celery Beat scheduler that persists scheduled tasks and…
- APSchedulerAPScheduler lets you schedule Python code to run later—once,…
Give your agent the search over MCP, or paste the wish link into any chat.
More Python Modules packages
Converts domain names between Unicode and ASCII-compatible encoding (Punycode) according to IDNA 2008 and Unicode Technical Standard 46, with security validation and broader script coverage than the standard library.
Install it if you work with internationalized domain names, need to validate domains, or use HTTP clients that depend on it transitively.
Setuptools is a Python build backend and package management tool that handles building, distributing, and installing Python packages, including support for C/C++ extension modules.
PyYAML parses and emits YAML 1.1 data format, enabling serialization and deserialization of configuration files and Python objects to and from human-readable YAML text.
Pydantic validates Python data structures against type hints, coercing and checking input at runtime to ensure it matches a declared schema.
Provides reusable metadata objects for use with PEP-593 `typing.Annotated` to express common constraints like bounds, collection sizes, and predicates on types.
Install it if you use or build libraries that need to express type constraints in a standardized, inspectable way—or if you want to annotate your own types with…
Provides runtime tools to inspect and introspect Python type annotations, enabling programmatic examination of type hints at execution time.
See also scheduler · APScheduler · schedule · google-cloud-scheduler · distributed · arq · celery-redbeat · rq-scheduler · django-apscheduler · cron-schedule-triggers