doccano | Open source annotation tool for machine learning | Dataset library

by doccano Python Version: v1.8.3 License: MIT

X-Ray Key Features Code Snippets(4)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | doccano Summary

doccano is a Python library typically used in Artificial Intelligence, Dataset, Deep Learning applications. doccano has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. However doccano build file is not available. You can install using 'pip install doccano' or download it from GitHub, PyPI.

doccano is an open source text annotation tool for humans. It provides annotation features for text classification, sequence labeling and sequence to sequence tasks. So, you can create labeled data for sentiment analysis, named entity recognition, text summarization and so on. Just create a project, upload data and start annotating. You can build a dataset in hours.

Support

Quality

Security

License

Reuse

Support

doccano has a medium active ecosystem.

It has 7871 star(s) with 1562 fork(s). There are 126 watchers for this library.

It had no major release in the last 12 months.

There are 229 open issues and 1157 have been closed. On average issues are closed in 116 days. There are 7 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of doccano is v1.8.3

Quality

doccano has 0 bugs and 0 code smells.

Security

doccano has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

doccano code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

doccano 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

doccano releases are available to install and integrate.

Deployable package is available in PyPI.

doccano has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

It has 9196 lines of code, 676 functions and 553 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Parse a file
Calculate the span of the span
Create a record
Saves all records in the corpus
Create labels for the given examples
Clean the labels
Create examples from a dataframe
Check that the value in the dataframe exists in the dataframe
Checks the existence of the column in the dataframe
Run the web server
Parse CSV file
Gets the label distribution for the given examples
Create a new model
Deletes the item
Create new example
Parse text file
Return True if the given label can be annotated
Saves data for the given user
Save examples to a given user
Render label template
Return True if the user has permission to access the role
Start the task queue
Parse a JSON file
Handle POST request
Create a new example
Return whether the given label can be annotated

Get all kandi verified functions for this library.

doccano Key Features

No Key Features are available at this moment for doccano.

doccano Examples and Code Snippets

Doccano API Client,Usage

Python

Lines of Code : 20

License : Permissive (MIT)

Copy

from doccano_api_client import DoccanoClient

# instantiate a client and log in to a Doccano instance
doccano_client = DoccanoClient(
    'http://doccano.example.com',
    'username',
    'password'
)

# get basic information about the authorized use

doccano-transformer,Examples,Named Entity Recognition

Python

Lines of Code : 6

License : Permissive (MIT)

Copy

from doccano_transformer.datasets import NERDataset
from doccano_transformer.utils import read_jsonl

dataset = read_jsonl(filepath='example.jsonl', dataset=NERDataset, encoding='utf-8')
dataset.to_conll2003(tokenizer=str.split)
dataset.to_spacy(toke

Available and planned services

Shell

Lines of Code : 2

License : Non-SPDX (NOASSERTION)

Copy

ln -s ../../services-available/indra.yaml indra.yaml

traefikhost=labs.coronawhy.org

spaCy CLI debug shows 0 train/dev docs in CLI-formatted JSON converted by spacy.gold.docs_to_json

Python

Lines of Code : 2

License : Strong Copyleft (CC BY-SA 4.0)

Copy

srsly.write_json(filename, [spacy.gold.docs_to_json(docs)])

Community Discussions

Trending Discussions on doccano

How can I solve the 29 unapplied migration(s) for app(s): admin, api, auth, authtoken, contenttypes, sessions, social_django

QUESTION

How can I solve the 29 unapplied migration(s) for app(s): admin, api, auth, authtoken, contenttypes, sessions, social_django

Asked 2020-Dec-27 at 11:33

I was setting up Doccano on my desktop to perform sequence labeling tasks. I followed the instructions from a website on how to setup Doccano. Everything was working fine until I got to the last code below where I experienced migration errors.

...

ANSWER

Answered 2020-Oct-22 at 23:24

This is a Django project, so you are required to manually migrate the required models for the 29 apps that it's referring to.

It seems to me as though you are running this outside the directory that you've cloned

C:\Users\okekec>

should be

C:\Users\okekec\doccano>

There, it should have the manage.py file, i.e. the file should be in the current directory. This should then allow you to perform the migrations.

Source https://stackoverflow.com/questions/64490347

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

Vulnerabilities

No vulnerabilities reported

Install doccano

You can install using 'pip install doccano' or download it from GitHub, PyPI.
You can use doccano 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

As with any software, doccano is under continuous development. If you have requests for features, please file an issue describing your request. Also, if you want to see work towards a specific feature, feel free to contribute by working towards it. The standard procedure is to fork the repository, add a feature, fix a bug, then file a pull request that your changes are to be merged into the main repository and included in the next release. Here are some tips might be helpful. How to Contribute to Doccano Project.

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