Nimble crawl reference

nimble crawl — reference

Async bulk crawling — starts a crawl job, returns a crawl_id, then you poll for status and retrieve per-page content via individual task_ids.

Tip: For LLM use, prefer nimble map + nimble extract --format markdown (faster, cleaner). Use crawl when you need raw HTML archives of many pages at once.

Table of Contents

• 1. Create crawl (async)
• 2. Get crawl status
• 3. List crawls
• 4. Cancel crawl
• Polling guidelines
• Retrieving page content
• Crawl vs Map

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1. Create crawl (async)

Parameters:

Parameter	CLI flag	Type	Default	Description
url	--url	string	required	Starting URL
limit	--limit	int	5000	Max pages (1–10,000) — always set this
name	--name	string	—	Label for tracking
sitemap	--sitemap	string	include	include | only | skip
include_path	--include-path	string[]	—	URL path regex to include (repeatable)
exclude_path	--exclude-path	string[]	—	URL path regex to exclude (repeatable)
max_discovery_depth	--max-discovery-depth	int	5	Max link depth from start (1–20)
crawl_entire_domain	--crawl-entire-domain	bool	false	Follow sibling/parent paths
allow_subdomains	--allow-subdomains	bool	false	Follow links to subdomains
allow_external_links	--allow-external-links	bool	false	Follow links to external domains
ignore_query_parameters	--ignore-query-parameters	bool	false	Deduplicate query-param variants
callback	--callback	string	—	Webhook URL for real-time page notifications
extract_options	--extract-options	object	—	Extraction config applied to each page

CLI:

nimble crawl run --url "https://docs.example.com" --limit 50 --name "docs-crawl"

Python SDK:

from nimble_python import Nimble
nimble = Nimble(api_key=os.environ["NIMBLE_API_KEY"])

resp = nimble.crawl.run(url="https://docs.example.com", limit=50, name="docs-crawl")
crawl_id = resp.crawl_id

Response fields: crawl_id, status (initial: queued), url, name, crawl_options, created_at

Crawl status values: queued → running → succeeded / failed / canceled

---

2. Get crawl status

Parameters:

Parameter	CLI flag	Type	Description
id	--id	string	crawl_id (required)

CLI:

nimble crawl status --id "abc-123"

Python SDK:

crawl = nimble.crawl.status(id=crawl_id)
print(crawl.status, crawl.completed, crawl.total)

Response adds: total, pending, completed, failed, tasks[]

Field	Description
tasks[].task_id	Use with nimble tasks results to fetch page content
tasks[].status	pending / processing / completed / failed

CRITICAL: Use tasks[].task_id — NOT crawl_id — to fetch page content. Using crawl_id with tasks returns 404.

---

3. List crawls

Parameters:

Parameter	CLI flag	Type	Description
status	--status	string	Filter: queued | running | completed | failed | canceled
limit	--limit	int	Results per page
cursor	--cursor	string	Pagination cursor

CLI:

nimble crawl list --status running

Python SDK:

result = nimble.crawl.list()
# result.data = list of crawl objects
# result.pagination = { has_next, next_cursor, total }

---

4. Cancel crawl

Parameters:

Parameter	CLI flag	Type	Description
id	--id	string	crawl_id (required)

CLI:

nimble crawl terminate --id "abc-123"

Python SDK:

nimble.crawl.terminate(id=crawl_id)
# Returns: {"status": "canceled"}

---

Polling guidelines

CRAWL_ID=$(nimble crawl run --url "https://example.com" --limit 100 --name "my-crawl" \
  | python3 -c "import json,sys; print(json.load(sys.stdin)['crawl_id'])")

while true; do
  STATUS=$(nimble crawl status --id "$CRAWL_ID" \
    | python3 -c "import json,sys; print(json.load(sys.stdin).get('status',''))")
  echo "Status: $STATUS"
  [ "$STATUS" = "succeeded" ] || [ "$STATUS" = "failed" ] || [ "$STATUS" = "canceled" ] && break
  sleep 30
done

Crawl size	Poll interval
< 50 pages	every 15–30s
50–500 pages	every 30–60s
500+ pages	every 60–120s

---

Retrieving page content

After crawl succeeded, fetch each completed task — see nimble-tasks reference:

nimble tasks results --task-id "task-456"

---

Crawl vs Map

	map	crawl
Speed	Seconds (sync)	Minutes (async)
Output	URL list with metadata	Full page content per URL
Best for	Discover URLs, then selectively extract	Archive all pages at once
LLM use	✅ Combine with extract --format markdown	⚠️ Returns raw HTML