TextBlob vs TextLens API

TextBlob handles sentiment analysis and basic NLP in Python. TextLens API covers the same ground plus readability scoring (8 formulas), keyword extraction, and SEO scoring — from a REST endpoint that works in any language.

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Side-by-side comparison

Feature TextBlob TextLens API
Sentiment analysis ✓ ✓
Subjectivity scoring ✓ ✗
Noun phrase extraction ✓ ✗
Part-of-speech tagging ✓ ✗
Readability scoring (8 formulas) ✗ ✓
Consensus readability grade ✗ ✓
TF-IDF keyword extraction ✗ ✓
SEO scoring ✗ ✓
Reading time estimate ✗ ✓
Works in Ruby, Go, PHP ✗ ✓
No Python environment needed ✗ ✓
No NLTK corpus download required ✗ ✓
Free tier Free (open source) 1,000 req/mo
Single endpoint, all content metrics ✗ ✓

The code

TextBlob Python

from textblob import TextBlob
blob = TextBlob("Your text...")
# Sentiment only — two values
print(blob.sentiment.polarity)     # -1.0 to 1.0
print(blob.sentiment.subjectivity) # 0 to 1
# No readability scores
# No keyword extraction
# No SEO scoring

TextBlob excels at sentiment and linguistic analysis. No readability formulas. Requires NLTK corpus download.

TextLens API Python

import requests
result = requests.post(
    "https://api.ckmtools.dev/v1/analyze",
    headers={"X-API-Key": "your_key"},
    json={"text": "Your text..."}
).json()
grade     = result["readability"]["consensus_grade"]
sentiment = result["sentiment"]["label"]
keywords  = result["keywords"]["top_5"]
seo       = result["seo"]["score"]

All content metrics in one HTTP call. Works in Python, Ruby, Go — any language.

Different tools for different jobs

TextBlob

Mature library built on NLTK. Real strength is linguistic analysis — POS tagging, noun phrases, inflection, translation. Requires NLTK corpus downloads (150MB+) but one-time.

No readability scoring. No keyword relevance. Python-only.

TextLens API

Focused on content quality metrics. Readability scoring (8 formulas), keyword relevance, SEO quality. Does not do POS tagging or noun phrase extraction.

Works across languages via HTTP. No dependencies to install.

When to use each

When to use TextBlob

  • POS tagging, noun phrase extraction, word inflection
  • Translation and language detection
  • Subjectivity scoring alongside sentiment
  • Python-only projects where HTTP adds overhead

When to use TextLens API

  • Readability scoring (TextBlob has none)
  • Keyword extraction with relevance scores
  • SEO quality indicators for content
  • Multi-language stack — avoid NLTK dependency

Get Early Access

TextLens API is in development. Join the waitlist to get notified at launch.

From the team behind textlens — 96/week npm downloads.

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