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Manages Ahrefs API usage in Python using `ahrefs-python` library. Use when working with SEO / marketing related tasks or with data including backlinks, keywords, domain ratings, organic traffic, site audits, rank tracking, and brand monitoring. Covers `ahrefs-python` usage includ
Manages Ahrefs API usage in Python using `ahrefs-python` library. Use when working with SEO / marketing related tasks or with data including backlinks, keywords, domain ratings, organic traffic, site audits, rank tracking, and brand monitoring. Covers `ahrefs-python` usage including AhrefsClient / AsyncAhrefsClient, typed request/response models, error handling, and all API sections.
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The Ahrefs API provides programmatic access to Ahrefs SEO data. The official Python SDK (ahrefs-python) provides typed request and response models for all endpoints, auto-generated from the OpenAPI spec.
Key capabilities:
pip3 install git+https://github.com/ahrefs/ahrefs-python.git
Requires Python 3.11+. Dependencies: httpx, pydantic.
The SDK has 52 methods across 7 API sections. The built-in search tool is the fastest way to find the right method — it returns matching method signatures, parameters, and return types directly, so there's no need to scan through a large reference.
Python (preferred when already in a Python context):
from ahrefs.search import search_api_methods
# Returns formatted text with method signatures, parameters, and return types
print(search_api_methods("domain rating"))
# Filter by API section and limit results
print(search_api_methods("backlinks", section="site-explorer", limit=3))
CLI (preferred when exploring from the terminal):
# Ensure python3 points to the interpreter where ahrefs-python is installed:
# which python3
# python3 -c "import ahrefs"
python3 -m ahrefs.api_search "domain rating"
python3 -m ahrefs.api_search "backlinks" --section site-explorer --limit 3
python3 -m ahrefs.api_search "batch" --json
python3 -m ahrefs.api_search --sections # list all API sections
ahrefs-python SDK. DO NOT make raw httpx/requests calls to the Ahrefs API.YYYY-MM-DD format (e.g. "2025-01-15").select on list endpoints to request only the columns you need. List endpoints return all columns by default, which wastes API units and increases response size.with / async with) for client lifecycle management.AHREFS_API_KEY environment variable or your preferred secrets mechanism.import os
from ahrefs import AhrefsClient
with AhrefsClient(api_key=os.environ["AHREFS_API_KEY"]) as client:
data = client.site_explorer_domain_rating(target="ahrefs.com", date="2025-01-15")
print(data.domain_rating) # 91.0
print(data.ahrefs_rank) # 3
import os
import ahrefs
with ahrefs.AhrefsClient(
api_key=os.environ["AHREFS_API_KEY"], # or any secrets source
base_url="...", # override API base URL (default: https://api.ahrefs.com/v3)
timeout=30.0, # request timeout in seconds (default: 60)
max_retries=3, # retries on transient errors (default: 2)
) as client:
...
Async client:
import os
from ahrefs import AsyncAhrefsClient
async with AsyncAhrefsClient(api_key=os.environ["AHREFS_API_KEY"]) as client:
data = await client.site_explorer_domain_rating(target="ahrefs.com", date="2025-01-15")
For parallel calls, use asyncio.gather:
import asyncio
async with AsyncAhrefsClient(api_key=os.environ["AHREFS_API_KEY"]) as client:
dr_ahrefs, dr_moz = await asyncio.gather(
client.site_explorer_domain_rating(target="ahrefs.com", date="2025-01-15"),
client.site_explorer_domain_rating(target="moz.com", date="2025-01-15"),
)
Two calling styles -- both are equivalent:
# Keyword arguments (recommended)
data = client.site_explorer_domain_rating(target="ahrefs.com", date="2025-01-15")
# Request objects (full type safety)
from ahrefs.types import SiteExplorerDomainRatingRequest
request = SiteExplorerDomainRatingRequest(target="ahrefs.com", date="2025-01-15")
data = client.site_explorer_domain_rating(request)
Method names follow {api_section}_{endpoint}, e.g. site_explorer_organic_keywords, keywords_explorer_overview.
Methods return typed Data objects directly.
Scalar endpoints return a single data object (or None):
data = client.site_explorer_domain_rating(target="ahrefs.com", date="2025-01-15")
print(data.domain_rating)
List endpoints return a list of data objects. There is no pagination — set limit to the number of results you need. Use select to request only the columns you need:
items = client.site_explorer_organic_keywords(
target="ahrefs.com",
date="2025-01-15",
select="keyword,volume,best_position",
order_by="volume:desc",
limit=10,
)
for item in items:
print(item.keyword, item.volume, item.best_position)
import ahrefs
try:
data = client.site_explorer_domain_rating(target="example.com", date="2025-01-15")
except ahrefs.AuthenticationError: # 401
...
except ahrefs.RateLimitError as e: # 429 -- e.retry_after has the delay
...
except ahrefs.NotFoundError: # 404
...
except ahrefs.APIError as e: # other 4xx/5xx -- e.status_code, e.response_body
...
except ahrefs.APIConnectionError: # network / timeout
...
All exceptions inherit from ahrefs.AhrefsError.
Most list endpoints share these parameters:
| Parameter | Type | Description |
|---|---|---|
target | str | Domain, URL, or path to analyze |
date | str | Date in YYYY-MM-DD format |
date_from / date_to | str | Date range for history endpoints |
country | str | Two-letter country code (ISO 3166-1 alpha-2) |
select | str | Comma-separated columns to return |
where | str | Filter expression |
order_by | str | Column and direction, e.g. "volume:desc" |
limit | int | Max results to return |
Parameters typed as enums in the API reference (CountryEnum, VolumeModeEnum, etc.) accept plain strings — pass country="us" not CountryEnum("us").
The where parameter takes a JSON string. Use json.dumps() to build it:
import json
where = json.dumps({"field": "volume", "is": ["gte", 1000]})
items = client.site_explorer_organic_keywords(
target="ahrefs.com", date="2025-01-15",
select="keyword,volume", where=where,
)
For full filter syntax (boolean combinators, operators, nested fields), see references/filter-syntax.md.
Use search_api_methods("query") or python3 -m ahrefs.api_search "query" to find methods by keyword. Search covers all 52 methods across 7 API sections and returns complete signatures, parameters, and response fields.
name: ahrefs-python description: Manages Ahrefs API usage in Python using `ahrefs-python` library. Use when working with SEO / marketing related tasks or with data including backlinks, keywords, domain ratings, organic traffic, site audits, rank tracking, and brand monitoring. Covers `ahrefs-python` usage including AhrefsClient / AsyncAhrefsClient, typed request/response models, error handling, and all API sections.
---
name: ahrefs-python
description: Manages Ahrefs API usage in Python using `ahrefs-python` library. Use when working with SEO / marketing related tasks or with data including backlinks, keywords, domain ratings, organic traffic, site audits, rank tracking, and brand monitoring. Covers `ahrefs-python` usage including AhrefsClient / AsyncAhrefsClient, typed request/response models, error handling, and all API sections.
---
# Ahrefs Python SDK Skill
## Overview
The Ahrefs API provides programmatic access to Ahrefs SEO data. The official Python SDK (`ahrefs-python`) provides typed request and response models for all endpoints, auto-generated from the OpenAPI spec.
Key capabilities:
- **Site Explorer** - Backlinks, organic keywords, domain rating, traffic, referring domains
- **Keywords Explorer** - Keyword research, volumes, difficulty, related terms
- **Rank Tracker** - SERP monitoring, competitor tracking
- **Site Audit** - Technical SEO issues, page content, page explorer
- **Brand Radar** - AI brand mentions, share of voice, impressions
- **SERP Overview** - Search result analysis
- **Batch Analysis** - Bulk domain/URL metrics via POST
## Installation
```sh
pip3 install git+https://github.com/ahrefs/ahrefs-python.git
```
Requires Python 3.11+. Dependencies: `httpx`, `pydantic`.
## API Method Discovery
The SDK has 52 methods across 7 API sections. The built-in search tool is the fastest way to find the right method — it returns matching method signatures, parameters, and return types directly, so there's no need to scan through a large reference.
**Python** (preferred when already in a Python context):
```python
from ahrefs.search import search_api_methods
# Returns formatted text with method signatures, parameters, and return types
print(search_api_methods("domain rating"))
# Filter by API section and limit results
print(search_api_methods("backlinks", section="site-explorer", limit=3))
```
**CLI** (preferred when exploring from the terminal):
```sh
# Ensure python3 points to the interpreter where ahrefs-python is installed:
# which python3
# python3 -c "import ahrefs"
python3 -m ahrefs.api_search "domain rating"
python3 -m ahrefs.api_search "backlinks" --section site-explorer --limit 3
python3 -m ahrefs.api_search "batch" --json
python3 -m ahrefs.api_search --sections # list all API sections
```
## IMPORTANT RULES
- ALWAYS use the `ahrefs-python` SDK. DO NOT make raw `httpx`/`requests` calls to the Ahrefs API.
- ALWAYS pass dates as strings in `YYYY-MM-DD` format (e.g. `"2025-01-15"`).
- ALWAYS use `select` on list endpoints to request only the columns you need. List endpoints return all columns by default, which wastes API units and increases response size.
- USE context managers (`with` / `async with`) for client lifecycle management.
- NEVER hardcode API keys in source code. Use the `AHREFS_API_KEY` environment variable or your preferred secrets mechanism.
- The client handles retries (429, 5xx, connection errors) automatically. DO NOT implement your own retry logic on top of the SDK.
## Quick Start
```python
import os
from ahrefs import AhrefsClient
with AhrefsClient(api_key=os.environ["AHREFS_API_KEY"]) as client:
data = client.site_explorer_domain_rating(target="ahrefs.com", date="2025-01-15")
print(data.domain_rating) # 91.0
print(data.ahrefs_rank) # 3
```
## SDK Patterns
### Client Setup
```python
import os
import ahrefs
with ahrefs.AhrefsClient(
api_key=os.environ["AHREFS_API_KEY"], # or any secrets source
base_url="...", # override API base URL (default: https://api.ahrefs.com/v3)
timeout=30.0, # request timeout in seconds (default: 60)
max_retries=3, # retries on transient errors (default: 2)
) as client:
...
```
Async client:
```python
import os
from ahrefs import AsyncAhrefsClient
async with AsyncAhrefsClient(api_key=os.environ["AHREFS_API_KEY"]) as client:
data = await client.site_explorer_domain_rating(target="ahrefs.com", date="2025-01-15")
```
For parallel calls, use `asyncio.gather`:
```python
import asyncio
async with AsyncAhrefsClient(api_key=os.environ["AHREFS_API_KEY"]) as client:
dr_ahrefs, dr_moz = await asyncio.gather(
client.site_explorer_domain_rating(target="ahrefs.com", date="2025-01-15"),
client.site_explorer_domain_rating(target="moz.com", date="2025-01-15"),
)
```
### Calling Methods
Two calling styles -- both are equivalent:
```python
# Keyword arguments (recommended)
data = client.site_explorer_domain_rating(target="ahrefs.com", date="2025-01-15")
# Request objects (full type safety)
from ahrefs.types import SiteExplorerDomainRatingRequest
request = SiteExplorerDomainRatingRequest(target="ahrefs.com", date="2025-01-15")
data = client.site_explorer_domain_rating(request)
```
Method names follow `{api_section}_{endpoint}`, e.g. `site_explorer_organic_keywords`, `keywords_explorer_overview`.
### Responses
Methods return typed Data objects directly.
**Scalar endpoints** return a single data object (or `None`):
```python
data = client.site_explorer_domain_rating(target="ahrefs.com", date="2025-01-15")
print(data.domain_rating)
```
**List endpoints** return a list of data objects. There is no pagination — set `limit` to the number of results you need. Use `select` to request only the columns you need:
```python
items = client.site_explorer_organic_keywords(
target="ahrefs.com",
date="2025-01-15",
select="keyword,volume,best_position",
order_by="volume:desc",
limit=10,
)
for item in items:
print(item.keyword, item.volume, item.best_position)
```
### Error Handling
```python
import ahrefs
try:
data = client.site_explorer_domain_rating(target="example.com", date="2025-01-15")
except ahrefs.AuthenticationError: # 401
...
except ahrefs.RateLimitError as e: # 429 -- e.retry_after has the delay
...
except ahrefs.NotFoundError: # 404
...
except ahrefs.APIError as e: # other 4xx/5xx -- e.status_code, e.response_body
...
except ahrefs.APIConnectionError: # network / timeout
...
```
All exceptions inherit from `ahrefs.AhrefsError`.
### Common Parameters
Most list endpoints share these parameters:
| Parameter | Type | Description |
|-----------|------|-------------|
| `target` | `str` | Domain, URL, or path to analyze |
| `date` | `str` | Date in YYYY-MM-DD format |
| `date_from` / `date_to` | `str` | Date range for history endpoints |
| `country` | `str` | Two-letter country code (ISO 3166-1 alpha-2) |
| `select` | `str` | Comma-separated columns to return |
| `where` | `str` | Filter expression |
| `order_by` | `str` | Column and direction, e.g. `"volume:desc"` |
| `limit` | `int` | Max results to return |
Parameters typed as enums in the API reference (`CountryEnum`, `VolumeModeEnum`, etc.) accept plain strings — pass `country="us"` not `CountryEnum("us")`.
The `where` parameter takes a JSON string. Use `json.dumps()` to build it:
```python
import json
where = json.dumps({"field": "volume", "is": ["gte", 1000]})
items = client.site_explorer_organic_keywords(
target="ahrefs.com", date="2025-01-15",
select="keyword,volume", where=where,
)
```
For full filter syntax (boolean combinators, operators, nested fields), see `references/filter-syntax.md`.
## API Methods
Use `search_api_methods("query")` or `python3 -m ahrefs.api_search "query"` to find methods by keyword. Search covers all 52 methods across 7 API sections and returns complete signatures, parameters, and response fields.
Skill source recorded
Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.
Review before install: Avoid automatic install
Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.
Check the source for dependencies, API keys and third-party costs. A public repository does not mean every service is free.
Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.
Version reported in registry metadata; check source releases before relying on it.
Quality
75/100
Strong
Trust
68/100
Sandbox only
Audit
81/100
Needs review
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
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"payload_template": {
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"skill_slug": "openclaudia-ahrefs-python",
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"output_quality": 4,
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"notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
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},
"endpoints": {
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"api": "https://www.openagentskill.com/api/agent/skills/openclaudia-ahrefs-python",
"audit": "https://www.openagentskill.com/skills/openclaudia-ahrefs-python/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=openclaudia-ahrefs-python&task=Use%20ahrefs-python%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20ahrefs-python%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20ahrefs-python%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/openclaudia-ahrefs-python/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/openclaudia-ahrefs-python"
}
}Listing source
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