celery-tasktree | Celery Tasktree module | Monitoring library

by NetAngels Python Version: 0.3.4 License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | celery-tasktree Summary

celery-tasktree is a Python library typically used in Performance Management, Monitoring applications. celery-tasktree has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can install using 'pip install celery-tasktree' or download it from GitHub, PyPI.

Celery Tasktree module

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Quality

Security

License

Reuse

Support

celery-tasktree has a low active ecosystem.

It has 107 star(s) with 8 fork(s). There are 9 watchers for this library.

It had no major release in the last 12 months.

There are 2 open issues and 1 have been closed. On average issues are closed in 2 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of celery-tasktree is 0.3.4

Quality

celery-tasktree has 0 bugs and 0 code smells.

Security

celery-tasktree has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

celery-tasktree code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

celery-tasktree does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

celery-tasktree releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Top functions reviewed by kandi - BETA

kandi has reviewed celery-tasktree and discovered the below as its top functions. This is intended to give you an instant insight into celery-tasktree implemented functionality, and help decide if they suit your requirements.

Wrapper that wraps a function with callbacks
Decorate a function with callbacks
Run each task asynchronously
Recursively get child tasks
Execute callbacks
Remove the node from the stack
Read a file

Get all kandi verified functions for this library.

celery-tasktree Key Features

No Key Features are available at this moment for celery-tasktree.

celery-tasktree Examples and Code Snippets

No Code Snippets are available at this moment for celery-tasktree.

Community Discussions

Trending Discussions on celery-tasktree

celery_tasktree does not support DAG workflow in general. Is there an alternative?

QUESTION

celery_tasktree does not support DAG workflow in general. Is there an alternative?

Asked 2017-Mar-31 at 04:46

celery_tasktree (https://pypi.python.org/pypi/celery-tasktree) provides a cleaner workflow canvas compared to celery workflow scheduler (http://docs.celeryproject.org/en/latest/userguide/canvas.html). However, it only support tree-like workflow structure, not a general DAG-like workflow. Celery workflow does have "chords" method but seems cumbersome to use.

Is there any other celery-based library similar to celery_tasktree that works with general DAG workflow?

...

ANSWER

Answered 2017-Mar-31 at 04:46

Here are couple of libraries that support DAG based job schedulers.

https://github.com/thieman/dagobah

https://github.com/apache/incubator-airflow

They are not based on celery. However you can create your own primitives in celery to forward results which can used to build a DAG job schedulers.

Source https://stackoverflow.com/questions/43129065

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install celery-tasktree

You can install using 'pip install celery-tasktree' or download it from GitHub, PyPI.
You can use celery-tasktree like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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