Official Python SDK for the RankParse API. Sync and async clients, single dependency (httpx).

Installation

pip install rankparse

Requires Python 3.9+. Single runtime dependency: httpx.

Quick start

from rankparse import RankParseClient

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

result = client.domain_authority("github.com")
print(result["data"]["score"])          # 94
print(result["credits_remaining"])      # 9995

Async client

import asyncio
from rankparse import AsyncRankParseClient

async def main():
    async with AsyncRankParseClient(api_key="rp_...") as client:
        result = await client.domain_authority("github.com")
        print(result["data"]["score"])

asyncio.run(main())

Configuration

from rankparse import RankParseClient

client = RankParseClient(
    api_key="rp_...",
    base_url="https://api.rankparse.com/v1",  # optional override
    timeout=30.0,                              # seconds, default 30
)

Context managers

# Sync
with RankParseClient(api_key="rp_...") as client:
    result = client.backlinks("example.com")

# Async
async with AsyncRankParseClient(api_key="rp_...") as client:
    result = await client.backlinks("example.com")

Error handling

from rankparse.errors import AuthError, InsufficientCreditsError, RateLimitError

try:
    result = client.backlinks("example.com")
except AuthError:
    print("Invalid API key")
except InsufficientCreditsError:
    print("Top up at rankparse.com/dashboard")
except RateLimitError:
    print("Back off and retry")

All methods

Link graph

Method	Endpoint	Credits
`backlinks(domain, *, limit, offset, sort, from_domain, link_type)`	`GET /backlinks`	2
`referring_domains(domain, *, limit, offset)`	`GET /referring-domains`	2
`outbound_links(domain, *, limit)`	`GET /outbound-links`	2
`anchor_text(domain, *, limit)`	`GET /anchor-text`	2
`link_intersect(domain_a, domain_b, *, limit)`	`GET /link-intersect`	5
`link_velocity(domain)`	`GET /link-velocity`	0 (v2)
`new_links(domain)`	`GET /new-links`	0 (v2)
`lost_links(domain)`	`GET /lost-links`	0 (v2)

Domain intelligence

Method	Endpoint	Credits
`domain_authority(domain)`	`GET /domain-authority`	1
`domain_rank(domain)`	`GET /domain-rank`	2
`domain_overlap(domains, *, limit)`	`GET /domain-overlap`	5
`similar_domains(domain, *, limit)`	`GET /similar-domains`	5
`competitor_gap(domain, vs, *, limit)`	`GET /competitor-gap`	5
`link_audit(domain)`	`GET /link-audit`	8
`site_explorer(domain, *, limit)`	`GET /site-explorer`	10

Page & site

Method	Endpoint	Credits
`page_seo(url)`	`GET /page-seo`	3
`page_performance(url, *, strategy)`	`GET /page-performance`	3
`tech_stack(url)`	`GET /tech-stack`	2
`site_health(domain)`	`GET /site-health`	2
`sitemap(domain)`	`GET /sitemap`	2
`crawl_history(domain, *, limit, offset)`	`GET /crawl-history`	2
`top_pages(domain, *, limit)`	`GET /top-pages`	2
`schema_markup(url)`	`GET /schema-markup`	0 (v2)
`internal_links(url, *, limit, offset)`	`GET /internal-links`	0 (v2)

Batch & dashboard

Method	Description
`batch(requests)`	Run up to 50 requests in one call
`me()`	Current user profile + credit balance
`credits()`	Credit balance
`keys()`	List API keys
`create_key(name)`	Create a new API key
`revoke_key(key_id)`	Revoke an API key
`usage(*, limit, offset)`	Paginated usage logs

Pagination

page1 = client.backlinks("example.com", limit=100, offset=0)
page2 = client.backlinks("example.com", limit=100, offset=100)

Batch requests

results = client.batch([
    {"endpoint": "domain-authority", "domain": "stripe.com"},
    {"endpoint": "domain-authority", "domain": "github.com"},
    {"endpoint": "backlinks", "domain": "vercel.com", "limit": 10},
])

Pandas enrichment

import pandas as pd
from rankparse import RankParseClient

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

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")

Source & issues

GitHub: abhibavishi/rankparse-python

Python SDK

On this page