Python

RankParse in Python.

Official Python SDK. Sync and async clients via httpx. Single runtime dependency. Works with pandas, FastAPI, LangChain, and any Python 3.9+ environment.

Installation

pip install rankparse

Requires Python 3.9+. Single runtime dependency: httpx.

Quick start

Sync client for scripts and notebooks. Async client for FastAPI and asyncio workloads.

from rankparse import RankParseClient

client = RankParseClient(api_key="rp_...")

# Domain authority
result = client.domain_authority("stripe.com")
print(result["data"]["score"])          # 91
print(result["credits_remaining"])      # 9999

# Backlinks
backlinks = client.backlinks("stripe.com", limit=10)
for link in backlinks["data"]:
    print(link["from_url"], "→", link["anchor_text"])

# Pandas enrichment
import pandas as pd
df = pd.read_csv("domains.csv")
df["score"] = df["domain"].apply(
    lambda d: client.domain_authority(d)["data"]["score"]
)
df.sort_values("score", ascending=False).to_csv("enriched.csv")

What's included

FeatureDetails
All 25+ endpointsLink graph, domain intelligence, page & site, batch, dashboard
Sync + asyncRankParseClient and AsyncRankParseClient
Context managerswith / async with for connection reuse
Error classesAuthError, InsufficientCreditsError, RateLimitError, NotFoundError
Pandas-readyApply any method across a DataFrame column
Single dependencyhttpx only — no Pydantic or other heavy deps

Full SDK reference

See the Python SDK docs for the complete method reference, error handling guide, pagination, and async examples. Source on GitHub.

SEO data in Python.

100 free credits. No credit card. First request in 5 minutes.

Get API key — free