textacy: NLP, before and after spaCy
textacy is a Python library for performing a variety of natural language processing (NLP) tasks, built on the high-performance spacy library. With the fundamentals — tokenization, part-of-speech tagging, dependency parsing, etc. — delegated to another library, textacy focuses on the tasks that come before and follow after.
Features
Provide a convenient entry point and interface to one or many documents, with the core processing delegated to spaCy
Stream text, json, csv, spaCy binary, and other data to and from disk
Download and explore a variety of included datasets with both text content and metadata, from Congressional speeches to historical literature to Reddit comments
Clean and normalize raw text, before analyzing it
Access and filter basic linguistic elements, such as words, ngrams, and noun chunks; extract named entities, acronyms and their definitions, and key terms
Flexibly tokenize and vectorize documents and corpora, then train, interpret, and visualize topic models using LSA, LDA, or NMF methods
Compare strings, sets, and documents by a variety of similarity metrics
Calculate common text statistics, including Flesch-Kincaid Grade Level, SMOG Index, and multilingual Flesch Reading Ease
… and more!
Links
Note: ReadTheDocs builds have been failing for months, so those docs are currently out-of-date. Very sorry. As a (temporary?) workaround, docs for the latest version (v0.6.0) have been published via GitHub Pages:
Maintainer
Howdy, y’all. 👋
Burton DeWilde (<burton@chartbeat.com>)
1 maintainer
Metadata
1 maintainer
Release files for textacy 0.6.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| textacy-0.6.1.tar.gz | 170.3 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| textacy-0.6.1-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 308.3 kB
Release files / textacy-0.6.1.tar.gz
| Download URL | textacy-0.6.1.tar.gz |
|---|---|
| Size | 170.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
32ffb796f2abf0577af480d482608cca2baf85d366a4e2981ffd3e632ebeb76c
|
|
BLAKE2b-256 checksum How to use checksums |
2c0c8a6731c84ad3063a105c2be01ec0e8aada5a51ec48a20b2f16de23c669b7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Release files / textacy-0.6.1-py2.py3-none-any.whl
| Download URL | textacy-0.6.1-py2.py3-none-any.whl |
|---|---|
| Size | 137.9 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
339b8786c3f69fb389575d27df7bb38f8eb4ba3fea82e4cc8d61ccab020293bf
|
|
BLAKE2b-256 checksum How to use checksums |
419f22b9dec63bff5e6ef7fb47b2cd37025087c3995b6ca5467d78160f5b0eb3
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Security for textacy 0.6.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
