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‎.github/ISSUE_TEMPLATE/bug-report.md‎

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---
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name: Bug Report
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about: Report a problem using the Drug Named Entity Recognition Python library
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title: ''
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labels: bug
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assignees: ''
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---
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## Description
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A description of the problem with sufficient detail and context to understand the issue.
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## Environment
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Provide details regarding the operating system, toolchain, and environment.
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## How to Reproduce
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## Expected Behaviour
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A description of the expected behaviour.

‎.github/ISSUE_TEMPLATE/feature-request.md‎

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---
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name: Feature Request
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about: Suggest improvements to the Drug Named Entity Recognition Python library
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title: ''
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labels: enhancement
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assignees: ''
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---
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## Description
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A quick description of the requested feature.
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## Rationale
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A rationale for why the feature should be implemented in the Country Named Entity Recognition Python library

‎.github/PULL_REQUEST_TEMPLATE.md‎

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## Description
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⚠️ **Please check which files you are pushing! If there is any file where you have just changed whitespace, or changed `"` to `'`, etc, please delete it from your pull request. If you can limit the number of files that you modify in your PR to just what is strictly necessary makes it much simpler to track the edits to the project, and also makes things easier to merge your changes if two people work on the project simultaneously and their changes have to be combined.**
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Please include a summary of the change and which issue is fixed. Please also include relevant context. List any dependencies that are required for this change. Ideally we avoid introducing any new third party dependencies in `pyproject.toml` unless absolutely necessary, because this makes the project more susceptible to breaking whenever a third party library is updated. At the moment it's very lightweight with only `requests` as a requirement.
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#### Fixes # (issue)
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## Type of change
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Please delete options that are not relevant.
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- [ ] Bug fix (non-breaking change which fixes an issue)
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- [ ] New feature (non-breaking change which adds functionality)
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- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
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- [ ] Requires a documentation revision
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## Testing
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Please describe the tests that you ran to verify your changes. Provide instructions so we can reproduce. Please also list any relevant details for your test configuration
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- [ ] Test A
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- [ ] Test B
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#### Test Configuration
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* Library version:
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* OS:
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* Toolchain:
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## Checklist
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- [ ] My PR is for one issue, rather than for multiple unrelated fixes.
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- [ ] My code follows the style guidelines of this project. I have applied a Linter (recommended: Pycharm's code formatter) to make my whitespace consistent with the rest of the project.
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- [ ] I have performed a self-review of my own code
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- [ ] I have commented my code, particularly in hard-to-understand areas
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- [ ] I have made corresponding changes to the documentation
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- [ ] My changes generate no new warnings
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- [ ] I have added tests that prove my fix is effective or that my feature works
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- [ ] New and existing unit tests pass locally with my changes
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- [ ] Any dependent changes have been merged and published in downstream modules
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- [ ] I have checked my code and corrected any misspellings
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- [ ] I add third party dependencies only when necessary. If I changed the requirements, it changes in `pyproject.toml`
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- [ ] If I introduced a new feature, I documented it ideally in the README examples so that people will know how to use it.

‎.github/workflows/release.yml‎

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name: Release Pypi package
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on:
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release:
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types: [created]
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workflow_dispatch:
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jobs:
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deploy:
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name: "Build Distribution"
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: "3.x"
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- name: Install pypa/build
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run: >-
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python3 -m
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pip install
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build twine
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- name: Build and publish
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env:
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TWINE_USERNAME: ${{ secrets.TWINE_USERNAME }}
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TWINE_PASSWORD: ${{ secrets.TWINE_PASSWORD }}
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run: |
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python3 -m build
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twine upload --repository pypi dist/*

‎.github/workflows/test.yml‎

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name: Test Pypi package
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on:
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push:
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branches:
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- main
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paths-ignore:
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- README.md
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pull_request:
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branches:
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- main
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paths-ignore:
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- README.md
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jobs:
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build:
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runs-on: ubuntu-latest
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strategy:
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matrix:
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python: [3.10.11]
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steps:
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- uses: actions/checkout@v2
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- name: Setup Python
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uses: actions/setup-python@v2
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with:
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python-version: ${{ matrix.python }}
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- name: Install Tox and any other packages
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run: pip install tox
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- name: Run Tox
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# Run tox using the version of Python in `PATH`
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run: tox -e py

‎CITATION.cff‎

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# This CITATION.cff file was generated with cffinit.
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# Visit https://bit.ly/cffinit to generate yours today!
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cff-version: 1.2.0
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title: Drug named entity recognition
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message: 'If you use this software, please cite it as below.'
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type: software
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authors:
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- family-names: Wood
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given-names: Thomas Andrew
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orcid: 'https://orcid.org/0000-0001-8962-8571'
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repository-code: 'https://github.com/fastdatascience/country_named_entity_recognition/'
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url: 'https://fastdatascience.com/natural-language-processing/country-named-entity-recognition/'
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license: MIT
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version: CITATION.cff
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date-released: '2024-10-04'
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url: 'https://zenodo.org/doi/10.5281/zenodo.10970631'
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doi: 10.5281/zenodo.10970631

‎README.md‎

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We would be grateful for your taking the consideration to cite us. We would suggest something like the following (depending on your style):
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Wood, T.A., Country Named Entity Recognition [Computer software], Version 0.4, accessed at https://fastdatascience.com/country-named-entity-recognition/, Fast Data Science Ltd (2022)
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Wood, T.A., Country Named Entity Recognition [Computer software], Version 1.0.0, accessed at https://fastdatascience.com/natural-language-processing/country-named-entity-recognition/, Fast Data Science Ltd (2022)
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A BibTeX entry for LaTeX users is
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```
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@unpublished{countrynamedentityrecognition,
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AUTHOR = {Wood, T.A.},
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TITLE = {Country Named Entity Recognition (Computer software), Version 0.4},
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TITLE = {Country Named Entity Recognition (Computer software), Version 1.0.0},
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YEAR = {2023},
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Note = {To appear},
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url = {https://fastdatascience.com/country-named-entity-recognition/}
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url = {https://fastdatascience.com/natural-language-processing/country-named-entity-recognition/}
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}
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```
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## Case studies of the Country Named Entity Recognition Library
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Alisa Redding at the University of Helsinki used the tool for her Masters thesis on mass species extinction and biodiversity. Redding, Alisa, [Animals of the Digital Age : Assessing digital media for public interest and engagement in species threatened by wildlife trade.](https://helda.helsinki.fi/items/77960829-145a-4efb-b364-3dbe6ac6bfb4/full), University of Helsinki, Faculty of Science, 2023.
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People and organisations around the world have been using the library and have cited us.
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### The sixth wave of mass species extinction...
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Alisa Redding at the University of Helsinki used the tool for her Masters thesis on mass species extinction and biodiversity.
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* Redding, Alisa. [Animals of the Digital Age: Assessing digital media for public interest and engagement in species threatened by wildlife trade.](https://helda.helsinki.fi/items/77960829-145a-4efb-b364-3dbe6ac6bfb4/full) University of Helsinki, Faculty of Science, 2023.
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### The UN's Sustainable Development Goals (SDGs)
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Christoph Funk and his colleagues at Justus-Liebig-Universität Gießen (Justus Liebig University Giessen) in Germany used country-named-entity-recognition for their meta-analysis of articles related to Sustainable Development Goals in 2023:
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* Funk, Christoph and Tönjes, Elena and Teuber, Ramona and Breuer, Lutz, Reading Between the Lines: The Intersection of Research Attention and Sustainable Development Goals (May 31, 2023). Available at SSRN: [https://ssrn.com/abstract=4465055](https://ssrn.com/abstract=4465055) or [http://dx.doi.org/10.2139/ssrn.4465055](http://dx.doi.org/10.2139/ssrn.4465055)
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### The European Commission: detecting terrorism and extremism
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Francesco Bosso and his team at the European Commission wrote a report investigating NLP for location detection with a focus on the JRC Terrorism and Extremism Database.
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* Bosso, Francesco, et al. [Use of Large Language Models for location detection on the example of the terrorism and extremism event database.](https://publications.jrc.ec.europa.eu/repository/bitstream/JRC134961/JRC134961_01.pdf), JRC Technical Report, European Commission (2023).
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### Labelling radical content online
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Ugochukwu Etudo and Victoria Y. Yoon at Virginia Commonwealth University used the tool in their analysis of radical content online:
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* Ugochukwu Etudo, Victoria Y. Yoon (2023) [Ontology-Based Information Extraction for Labeling Radical Online Content Using Distant Supervision](https://pubsonline.informs.org/doi/abs/10.1287/isre.2023.1223). Information Systems Research 0(0). [https://doi.org/10.1287/isre.2023.1223](https://doi.org/10.1287/isre.2023.1223)
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## Other named entity recognition tools
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* [Medical and clinical named entity recognition Python library](https://fastdatascience.com/ai-in-pharma/medical-named-entity-recognition-python-library/)

‎README.rst‎

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‎pyproject.toml‎

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[project]
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name = "country-named-entity-recognition"
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version = "0.4"
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version = "1.0.0"
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description = "Finds countries in a string"
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readme = "README.md"
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license = "MIT"

country_named_entity_recognition/__init__.py renamed to src/country_named_entity_recognition/__init__.py

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"""
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__version__ = "1.0.0"
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from country_named_entity_recognition.country_finder import find_countries

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