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name: data-and-downloader description: "Configure NLTK data search paths, download only needed NLTK data packages, locate/load resources with nltk.data, use corpus readers, and recover safely from missing, corrupt, stale, or unsafe data archives." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Data And Downloader

Use this sub-skill when the task is about NLTK data packages rather than NLP algorithm usage: selecting targeted data downloads, setting NLTK_DATA/nltk.data.path, checking nltk.data.find() and nltk.data.load(), using nltk.corpus readers, diagnosing missing or corrupt resources, or recovering from downloader/path security failures.

Route away from this sub-skill when the task is mainly about:

• Tokenization, POS tagging, stemming, lemmatization, or VADER scoring after data is available: use ../tokenize-tag-stem/SKILL.md.
• Grammars, parsers, trees, chunkers, semantics, or inference APIs: use ../grammar-parse-semantics/SKILL.md.
• Classifiers, language models, metrics, probability distributions, or translation/alignment algorithms: use ../ml-metrics-and-translation/SKILL.md.

Fast Paths

• Install only the packages required by the failing API; do not recommend broad all unless the user explicitly wants the full collection. Common targeted packages: punkt_tab, averaged_perceptron_tagger_eng, averaged_perceptron_tagger_rus, wordnet, omw-2.0, vader_lexicon, universal_tagset, brown, treebank, reuters, and comtrans.
• Use python -m nltk.downloader -d /path/to/nltk_data PKG... or import nltk; nltk.download("PKG", download_dir="/path/to/nltk_data") for explicit downloads. Use -q/--quiet, -f/--force, -e/--exit-on-error, and -u/--url only when the task calls for them.
• For portable projects, set NLTK_DATA=/path/to/nltk_data before Python starts, or prepend the directory at runtime with import nltk.data; nltk.data.path.insert(0, "/path/to/nltk_data").
• Probe resources before running an algorithm: nltk.data.find("tokenizers/punkt_tab/english/"), nltk.data.find("taggers/averaged_perceptron_tagger_eng/"), nltk.data.find("corpora/wordnet/"), or nltk.data.find("sentiment/vader_lexicon.zip/vader_lexicon/vader_lexicon.txt").
• Use corpus readers via from nltk.corpus import brown, wordnet, reuters; start with fileids(), words(), sents(), tagged_words(), raw(), readme(), and categories() where the reader supports them.
• Treat LookupError messages as package hints, but distinguish “package missing” from “package present but entry missing/corrupt”; stale/corrupt packages should be force-redownloaded into a controlled directory.
• For recovery from untrusted data inputs, reject traversal-like resource names, do not unzip arbitrary archives into nltk_data, and rely on the downloader’s validated extraction path instead of custom unsafe extraction.

Reference Map

• Targeted package workflows, NLTK_DATA setup, downloader commands, corpus reader recipes, and safe recovery patterns: references/data-workflows.md.
• API signatures and resource/package map for nltk.download, Downloader, nltk.data.find/load, CLI flags, and common corpus reader methods: references/api-reference.md.
• LookupError diagnosis, read-only paths, proxy/network failures, stale/corrupt resources, package renames, and downloader/data security errors: references/troubleshooting.md.
• No-download checker for installed NLTK data paths and optional explicit download mode: scripts/check_nltk_data.py.

Minimum Validation Pattern

1. Print nltk.__version__, Python version, NLTK_DATA, and the effective nltk.data.path before changing the environment.
2. Check exact resources with nltk.data.find() or the bundled no-download script; avoid importing a corpus reader as proof unless you also call a method such as fileids() or words()[:5].
3. If a download is required, name explicit package IDs and use a controlled download_dir; re-run a no-download check afterward.
4. For corpus workflows, assert representative outputs and supported methods: e.g. brown.fileids(), brown.words(fileids="ca01"), brown.tagged_words(tagset="universal"), wordnet.synsets("dog"), reuters.categories(), or comtrans.aligned_sents()[:1] when the package is installed.
5. For security-sensitive recovery, ensure malformed resource strings fail closed (ValueError/LookupError) and archive extraction errors leave no partially trusted content to load.

Run the bundled checker from any current working directory after installing NLTK:

python /path/to/skills/disco/nltk/sub-skills/data-and-downloader/scripts/check_nltk_data.py --help
python /path/to/skills/disco/nltk/sub-skills/data-and-downloader/scripts/check_nltk_data.py --inspect