Modernize packaging, resource loading, and test/CI setup

Author: DemetersSon83

.github/workflows/ci.yml

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+name: CI
+
+on:
+  push:
+  pull_request:
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install package and test dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -e . pytest build twine
+      - name: Run unit tests
+        run: pytest -q -m "not integration"
+
+  integration:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+      - name: Install package and dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -e . pytest textblob
+      - name: Download corpora
+        run: python -m textblob.download_corpora
+      - name: Run full tests
+        run: pytest -q
+
+  packaging:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+      - name: Build and validate distributions
+        run: |
+          python -m pip install --upgrade pip
+          pip install build twine
+          python -m build
+          twine check dist/*

.gitignore

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+__pycache__/
+*.py[cod]
+*.egg-info/
+.pytest_cache/
+.ruff_cache/
+.venv/
+.idea/
+dist/
+build/

COMPATIBILITY.md

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+# Compatibility Notes (vs NRCLex 4.0 behavior)
+
+## Comparison method
+
+Because external network access is unavailable in this environment, direct installation of `NRCLex==4.0` from PyPI was not possible. Instead, behavior was compared against the repository's 4.0 implementation logic using the same bundled lexicon data.
+
+## Results
+
+### `load_token_list`
+
+For token list `['happy', 'sad', 'unknown', 'happy']`, the updated implementation produced identical values to the 4.0 logic for:
+
+- `raw_emotion_scores`
+- `affect_frequencies`
+- `top_emotions`
+
+### Constructor behavior (`NRCLex()`)
+
+- **4.0 behavior:** default `lexicon_file='nrc_en.json'` required current working directory assumptions and could fail after installation.
+- **Updated behavior:** `NRCLex()` now reliably loads bundled `nrclex/data/nrc_en.json` via `importlib.resources`.
+
+This constructor change is intentional and improves install-time reliability without changing the public API.
+
+## Metadata corrections (intentional)
+
+- Removed stdlib entries (`collections`, `json`) from dependencies.
+- Set `Requires-Python` to `>=3.9` to align with TextBlob support expectations.

README.md

@@ -1,88 +1,71 @@
-# NRCLex
-
-(C) 2019 Mark M. Bailey, PhD
-
-## About
-NRCLex will measure emotional affect from a body of text.  Affect dictionary contains approximately 27,000 words, and is based on the National Research Council Canada (NRC) affect lexicon (see link below) and the NLTK library's WordNet synonym sets.
-
-Lexicon source is (C) 2016 National Research Council Canada (NRC) and this package is **for research purposes only**. Source: http://saifmohammad.com/WebPages/NRC-Emotion-Lexicon.htm As per the terms of use of the NRC Emotion Lexicon, if you use the lexicon or any derivative from it, cite this paper: Crowdsourcing a Word-Emotion Association Lexicon, Saif Mohammad and Peter Turney, Computational Intelligence, 29 (3), 436-465, 2013.
-
-NLTK data is (C) 2019, NLTK Project.  Source: [NLTK] (https://www.nltk.org/).  Reference: Bird, Steven, Edward Loper and Ewan Klein (2009), Natural Language Processing with Python. O’Reilly Media Inc.
-
-## Update
-* Finally got around to cleaning this up a bit.  Updated PyPI package with current version.  Thanks to all the contributors for cleaning up my terrible code!
-* Expanded NRC lexicon from approximately 10,000 words to 27,000 based on WordNet synonyms.
-* Minor bug fixes.
-* Contributor updated NTC library.
-
-## Installation
-`pip install NRCLex`
-
-## Affects
-Emotional affects measured include the following:
-
-* fear
-* anger
-* anticipation
-* trust
-* surprise
-* positive
-* negative
-* sadness
-* disgust
-* joy
-
-## Sample Usage
-
-`from nrclex import NRCLex`<br><br>
-
-
-*#Instantiate NRCLex object, you can pass your own dictionary filename in json format.*<br>
-
-`text_object = NRCLex(lexicon_file='nrc_en.json')`<br><br>
-
-
-*#You can pass your raw text to this method(for best results, 'text' should be unicode).*<br>
-
-`text_object.load_raw_text(text: str)`<br><br>
-
-
-*#You can pass your already tokenized text as a list of tokens, if you want to use an already tokenized input.
-This usage assumes that the text is correctly tokenized and does not make use of TextBlob.*<br>
-
-`text_object.load_token_list(list_of_tokens: list)`<br><br>
-
-
-*#Return words list.*<br>
-
-`text_object.words`<br><br>
-
-
-*#Return sentences list.*<br>
-
-`text_object.sentences`<br><br>
-
-
-*#Return affect list.*<br>
-
-`text_object.affect_list`<br><br>
-
-
-*#Return affect dictionary.*<br>
-
-`text_object.affect_dict`<br><br>
-
-
-*#Return raw emotional counts.*<br>
-
-`text_object.raw_emotion_scores`<br><br>
-
-
-*#Return highest emotions.*<br>
-
-`text_object.top_emotions`<br><br>
-
-
-*#Return affect frequencies.*<br>
-
-`text_object.affect_frequencies`
+# NRCLex
+
+(C) 2019 Mark M. Bailey, PhD
+
+## About
+NRCLex measures emotional affect from text. Affect dictionary contains approximately 27,000 words and is based on the National Research Council Canada (NRC) affect lexicon and NLTK WordNet synonym sets.
+
+Lexicon source is (C) 2016 National Research Council Canada (NRC) and this package is **for research purposes only**. Source: http://saifmohammad.com/WebPages/NRC-Emotion-Lexicon.htm As per the terms of use of the NRC Emotion Lexicon, if you use the lexicon or any derivative from it, cite this paper: Crowdsourcing a Word-Emotion Association Lexicon, Saif Mohammad and Peter Turney, Computational Intelligence, 29 (3), 436-465, 2013.
+
+NLTK data is (C) 2019, NLTK Project. Source: [NLTK](https://www.nltk.org/). Reference: Bird, Steven, Edward Loper and Ewan Klein (2009), Natural Language Processing with Python. O’Reilly Media Inc.
+
+## Installation
+`pip install NRCLex`
+
+## Affects
+Emotional affects measured include:
+
+* fear
+* anger
+* anticipation
+* trust
+* surprise
+* positive
+* negative
+* sadness
+* disgust
+* joy
+
+## Sample Usage
+
+`from nrclex import NRCLex`
+
+Instantiate NRCLex object. By default this loads the bundled lexicon packaged with the library:
+
+`text_object = NRCLex()`
+
+You can pass your raw text to this method (for best results, text should be unicode):
+
+`text_object.load_raw_text(text: str)`
+
+You can pass already tokenized text as a list of tokens. This usage does not require TextBlob tokenization:
+
+`text_object.load_token_list(list_of_tokens: list)`
+
+Return words list:
+
+`text_object.words`
+
+Return sentences list:
+
+`text_object.sentences`
+
+Return affect list:
+
+`text_object.affect_list`
+
+Return affect dictionary:
+
+`text_object.affect_dict`
+
+Return raw emotional counts:
+
+`text_object.raw_emotion_scores`
+
+Return highest emotions:
+
+`text_object.top_emotions`
+
+Return affect frequencies:
+
+`text_object.affect_frequencies`

RELEASING.md

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+# Releasing NRCLex
+
+## 1) Choose version bump
+
+- Patch: bug fixes only, no compatibility changes.
+- Minor: backward-compatible features/packaging improvements.
+- Major: intentional breaking changes.
+
+For this modernization, use at least a **minor** bump if you changed supported Python versions.
+
+## 2) Update version
+
+Update these files together:
+
+1. `pyproject.toml` → `[project].version`
+2. `nrclex/__init__.py` → `__version__`
+
+## 3) Validate locally
+
+```bash
+python -m pip install --upgrade pip
+pip install -e . pytest build twine
+pytest -q -m "not integration"
+python -m build
+twine check dist/*
+```
+
+Optional integration tests (requires corpora):
+
+```bash
+python -m textblob.download_corpora
+pytest -q
+```
+
+## 4) Verify artifacts
+
+Ensure **both** files exist:
+
+- `dist/NRCLex-<version>.tar.gz`
+- `dist/NRCLex-<version>-py3-none-any.whl`
+
+## 5) Publish
+
+```bash
+twine upload dist/*
+```
+
+## 6) Don't forget
+
+- Confirm `from nrclex import NRCLex` works from a clean environment.
+- Confirm `NRCLex()` loads bundled lexicon without manual file path.
+- Confirm dependency metadata does **not** list stdlib modules.
+- Confirm `Requires-Python` matches supported versions (>=3.9).
+- Tag release in git and add release notes.