textstat vs TextLens API

textstat runs readability scoring locally in Python. TextLens API runs the same analysis as a REST endpoint — from Python, Ruby, Go, or any HTTP client. No dependencies to install.

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Side-by-side comparison

Feature textstat TextLens API
Flesch-Kincaid Grade ✓ ✓
Gunning Fog ✓ ✓
SMOG ✓ ✓
Coleman-Liau ✓ ✓
Automated Readability Index ✓ ✓
Dale-Chall ✓ ✓
Linsear Write ✓ ✓
Consensus grade (all 8 averaged) ✗ ✓
Sentiment analysis (AFINN) ✗ ✓
Keyword extraction (TF-IDF) ✗ ✓
SEO scoring ✗ ✓
Works in Ruby, Go, PHP ✗ ✓
No Python environment needed ✗ ✓
Free tier Free (open source) 1,000 req/mo
Team use / API key management ✗ ✓

The code

textstat Python

# Install: pip install textstat
import textstat

text = "Your text here..."

# Need separate calls for each metric
grade = textstat.flesch_kincaid_grade(text)
fog   = textstat.gunning_fog(text)
smog  = textstat.smog_index(text)
# No consensus grade
# No sentiment
# No keywords

TextLens API Python

# No install — uses stdlib only
import requests

result = requests.post(
    "https://api.ckmtools.dev/v1/analyze",
    headers={"X-API-Key": "your_key"},
    json={"text": "Your text here..."}
).json()

# All metrics in one response
grade     = result["readability"]["consensusGrade"]
sentiment = result["sentiment"]["label"]
keywords  = result["keywords"]["top_5"]

When to use each

When to use textstat

  • You're building a Python-only project
  • You want zero network dependencies
  • You only need readability scores, not sentiment or keywords
  • You process text in bulk locally (thousands of docs/second)

When to use TextLens API

  • Your team uses Python, Ruby, Go, or no-code tools
  • You want readability + sentiment + keywords in one call
  • You don't want to install or maintain NLP dependencies
  • You need consistent results across different environments

Get Early Access

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

From the team behind textlens — the zero-dependency npm package that powers the API.

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