sciencebeam-airflow | Airflow pipeline for ScienceBeam related training | Data Labeling library

by elifesciences Python Version: v0.0.8 License: MIT

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | sciencebeam-airflow Summary

sciencebeam-airflow is a Python library typically used in Artificial Intelligence, Data Labeling, Docker applications. sciencebeam-airflow has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Airflow pipeline for ScienceBeam related training and evaluation. is a platform to programmatically author, schedule, and monitor workflows. ... Airflow is not a data streaming solution. We are using the official Airflow Image.

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sciencebeam-airflow has a low active ecosystem.

It has 4 star(s) with 0 fork(s). There are 8 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 1 have been closed. On average issues are closed in 2 days. There are 4 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of sciencebeam-airflow is v0.0.8

Quality

sciencebeam-airflow has no bugs reported.

Security

sciencebeam-airflow has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

sciencebeam-airflow is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

sciencebeam-airflow releases are available to install and integrate.

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

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Prepare and evaluate convert and evaluation of source_dataset
Returns the path to the output folder
Generate file - list path
Return a list of tasks filtered by the conf
Create a new DAG
Creates a legacy validate config
Add a macro function to a DAG
Create a DockerImageOperator
Retrieve GroBinder tools image
Return the sciencebeam image
Get default arguments
Triggers a simple trigger
Add a model config file
Generate keyword arguments for a Scibeam plugin
Return the grob_trainer image
Parse command line arguments
Returns a list of the names of the names of the child of the given workflow
Triggers all files in the xcom pull task
Return True if conf is valid
Prepare the evaluation conf
Run the command line tool
Trigger next task
Return the command line arguments to be used in the command line
Return the arguments for the helm deploy command
Check if the configuration is valid
Convert evaluation results to jsonl file

Get all kandi verified functions for this library.

sciencebeam-airflow Key Features

No Key Features are available at this moment for sciencebeam-airflow.

sciencebeam-airflow Examples and Code Snippets

No Code Snippets are available at this moment for sciencebeam-airflow.

Community Discussions

Trending Discussions on Data Labeling

How can I do this split process in Python?

Replacing a character with a space and dividing the string into two words in R

Azure ML FileDataset registers, but cannot be accessed for Data Labeling project

QUESTION

How can I do this split process in Python?

Asked 2021-Dec-30 at 14:06

I'm trying to make a data labeling in a table, and I need to do it in such a way that, in each row, the index is repeated, however, that in each column there is another Enum class.

What I've done so far is make this representation with the same enumerator class.

A solution using the column separately as a list would also be possible. But what would be the best way to resolve this?

...

ANSWER

Answered 2021-Dec-30 at 13:57

Instead of using Enum you can use a dict mapping. You can avoid loops if you flatten your dataframe:

Source https://stackoverflow.com/questions/70532286

QUESTION

Replacing a character with a space and dividing the string into two words in R

Asked 2020-Nov-18 at 07:32

I have a dataframe that contains a column that includes strings separeted with semi-colons and it is followed by a space. But unfortunately in some of the strings there is a semi-colon that is not followed by a space.

In this case, This is what i'd like to do: If there is a space after the semi-colon we do not need a change. However if there are letters before and after the semi-colon, we should change semi-colon with space

i have this:

...

ANSWER

Answered 2020-Nov-16 at 07:24

Try something like:

Source https://stackoverflow.com/questions/64853962

QUESTION

Azure ML FileDataset registers, but cannot be accessed for Data Labeling project

Asked 2020-Oct-28 at 20:31

Objective: Generate a down-sampled FileDataset using random sampling from a larger FileDataset to be used in a Data Labeling project.

Details: I have a large FileDataset containing millions of images. Each filename contains details about the 'section' it was taken from. A section may contain thousands of images. I want to randomly select a specific number of sections and all the images associated with those sections. Then register the sample as a new dataset.

Please note that the code below is not a direct copy and paste as there are elements such as filepaths and variables that have been renamed for confidentiality reasons.

...

ANSWER

Answered 2020-Oct-27 at 22:39

Is the data behind virtual network by any chance?

Source https://stackoverflow.com/questions/64546521

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

Vulnerabilities

No vulnerabilities reported

Install sciencebeam-airflow

You can download it from GitHub.
You can use sciencebeam-airflow 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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