Textalyzer
Textalyzer is a lightweight python module or library to help ease analyzing of text or words in a particular sentence and manipulating it. Textalyzer analyzes repeating words and contracted words or contractions.
Class Functions Involved in this module
[-] ContractionReplacers
[-] RepeatingReplacers
Usage
-Place the file in a folder where you have either read or write and read permisson. Eg. /opinionmining/lib/Textalyzer.py
-Import the module into your application.
from opinionmining.lib.Textalyzer import "Function To Use"
sample = "I can't wait for the football match"
object = ContractionReplacers()
data = object.text_replacers(sample)
Sample
Repeating words
- Repeating words like helloooooooooooo - textalyzer help format this word by removing the o's to its normal word "hello"
- Contractions like I'm - Textalyzer help format this word by converting it to it's normal word "I am"
Dependencies
- nltk
- Download the WordNet corpus before using
RepeatingReplacers:python -m nltk.downloader wordnet
PyPI
-
Textalyzer is available at python package index.
Installation Guide
- Download textalyzer using pip
- pip install textalyzer
- Import textalyzer into your project by using
from textalyzer import Textalyzerdepending on the function you want to use. - Then use
replacer = Textalyzer.ContractionReplacers()andrepeat = Textalyzer.RepeatingReplacers()
- ## Or - Simple do
import textalyzer - Then Use
data = textalyzer.Textalyzer replacer = data.ContractionReplacers()
Alternatively
- You can download the tarball file from
pypi.python.org/pypi/textalyzer - Extract the tarball file
- Navigate into the extracted folder and install using
python setup.py install
To Check Whether it's installed
- type
pip freezeto display the list of installed packages
- Download textalyzer using pip
Why This
- Textalyzer is mostly used by python programmers who are more involved with Natural Language Processing , Machine Learning, Text Extraction and others.
Metadata
Release files for textalyzer 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| textalyzer-0.2.0.tar.gz | 4.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| textalyzer-0.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 9.1 kB
Release files / textalyzer-0.2.0.tar.gz
| Download URL | textalyzer-0.2.0.tar.gz |
|---|---|
| Size | 4.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / textalyzer-0.2.0-py3-none-any.whl
| Download URL | textalyzer-0.2.0-py3-none-any.whl |
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| Size | 4.5 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
3ba892cda4880e0da3cd3e5766570587fc29917a0223ce6babac27d44f7a4eb4
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.13
|
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.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jun 8, 2026.
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