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

 by   doccano Python Version: v1.8.3 License: MIT

kandi X-RAY | doccano Summary

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.

            kandi-support Support

              doccano has a medium active ecosystem.
              It has 7871 star(s) with 1562 fork(s). There are 126 watchers for this library.
              There were 1 major release(s) 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

            kandi-Quality Quality

              doccano has 0 bugs and 0 code smells.

            kandi-Security 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.

            kandi-License 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.

            kandi-Reuse 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
            Pythondot img1Lines of Code : 20dot img1License : Permissive (MIT)
            copy iconCopy
            from doccano_api_client import DoccanoClient
            # instantiate a client and log in to a Doccano instance
            doccano_client = DoccanoClient(
            # get basic information about the authorized use  
            doccano-transformer,Examples,Named Entity Recognition
            Pythondot img2Lines of Code : 6dot img2License : Permissive (MIT)
            copy iconCopy
            from doccano_transformer.datasets import NERDataset
            from doccano_transformer.utils import read_jsonl
            dataset = read_jsonl(filepath='example.jsonl', dataset=NERDataset, encoding='utf-8')
            Available and planned services
            Shelldot img3Lines of Code : 2dot img3License : Non-SPDX (NOASSERTION)
            copy iconCopy
            ln -s ../../services-available/indra.yaml indra.yaml
            copy iconCopy
            srsly.write_json(filename, [])

            Community Discussions


            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.



            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


            should be


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


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


            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.


            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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            gh repo clone doccano/doccano

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