Crawl4AI
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Pay per usage
Wraps the Crawl4AI open-source library for retrieving text content from websites.
Pricing
Pay per usage
Rating
3.3
(2)
Developer
Jan Buchar
Maintained by CommunityActor stats
16
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795
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8
Monthly active users
21 days
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3 days ago
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# The rest is copied from https://github.com/github/gitignore/blob/main/Python.gitignore
# Byte-compiled / optimized / DLL files__pycache__/*.py[cod]*$py.class
# C extensions*.so
# Distribution / packaging.Pythonbuild/develop-eggs/dist/downloads/eggs/.eggs/lib/lib64/parts/sdist/var/wheels/share/python-wheels/*.egg-info/.installed.cfg*.eggMANIFEST
# PyInstaller# Usually these files are written by a python script from a template# before PyInstaller builds the exe, so as to inject date/other infos into it.*.manifest*.spec
# Installer logspip-log.txtpip-delete-this-directory.txt
# Unit test / coverage reportshtmlcov/.tox/.nox/.coverage.coverage.*.cachenosetests.xmlcoverage.xml*.cover*.py,cover.hypothesis/.pytest_cache/cover/
# Translations*.mo*.pot
# Django stuff:*.loglocal_settings.pydb.sqlite3db.sqlite3-journal
# Flask stuff:instance/.webassets-cache
# Scrapy stuff:.scrapy
# Sphinx documentationdocs/_build/
# PyBuilder.pybuilder/target/
# Jupyter Notebook.ipynb_checkpoints
# IPythonprofile_default/ipython_config.py
# pyenv# For a library or package, you might want to ignore these files since the code is# intended to run in multiple environments; otherwise, check them in:.python-version
# pdm# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.#pdm.lock# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it# in version control.# https://pdm.fming.dev/latest/usage/project/#working-with-version-control.pdm.toml.pdm-python.pdm-build/
# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm__pypackages__/
# Celery stuffcelerybeat-schedulecelerybeat.pid
# SageMath parsed files*.sage.py
# Environments.env.venvenv/venv/ENV/env.bak/venv.bak/
# Spyder project settings.spyderproject.spyproject
# Rope project settings.ropeproject
# mkdocs documentation/site
# mypy.mypy_cache/.dmypy.jsondmypy.json
# Pyre type checker.pyre/
# pytype static type analyzer.pytype/
# Cython debug symbolscython_debug/
# PyCharm# JetBrains specific template is maintained in a separate JetBrains.gitignore that can# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore# and can be added to the global gitignore or merged into this file. For a more nuclear# option (not recommended) you can uncomment the following to ignore the entire idea folder..idea/
# Visual Studio Code# Ignores the folder created by VS Code when changing workspace settings, doing debugger# configuration, etc. Can be commented out to share Workspace Settings within a team.vscode
# Zed editor# Ignores the folder created when setting Project Settings in the Zed editor. Can be commented out# to share Project Settings within a team.zed# Keep the Playwright version in pyproject.toml in sync with the tag below.FROM apify/actor-python-playwright:3.13-1.62.0
COPY /uv /usr/local/bin/uv
USER myuser
# Putting the project environment on PATH lets the base image's launcher keep running plain `python`.ENV UV_PROJECT_ENVIRONMENT=/usr/src/app/.venv \ UV_PYTHON=/usr/local/bin/python \ UV_PYTHON_DOWNLOADS=never \ UV_COMPILE_BYTECODE=1 \ PATH=/usr/src/app/.venv/bin:$PATH
# Copy just the dependency manifests first, so that the install layer is cached across source changes.COPY pyproject.toml uv.lock ./
# `--frozen` fails the build if uv.lock has drifted from pyproject.toml, and prints every resolved version.RUN uv sync --frozen --no-dev
# `crawl4ai-setup` is deliberately not run - the only thing it does that matters here is installing# Playwright's browsers, which the base image already ships, and it needs root to even try.
COPY . ./
# Use compileall to ensure the runnability of the Actor Python code.RUN python -m compileall -q src/
CMD ["python", "-m", "src"]1[project]2name = "actor-crawl4ai"3version = "0.1.0"4description = "Apify Actor wrapping the crawl4ai web crawler"5requires-python = ">=3.13,<3.14"6dependencies = [7 "apify>=4.0.0,<5.0.0",8 "crawl4ai>=0.9.2,<0.10.0",9 # Must match the Playwright version bundled in the base image, otherwise the pre-installed10 # browsers will not be found. Keep in sync with the tag in Dockerfile.11 "playwright==1.62.0",12]13
14[dependency-groups]15dev = ["ruff~=0.14.0"]16
17[tool.uv]18# This is an application, not a library - there is nothing to build and install.19package = false20
21[tool.ruff]22line-length = 12023
24[tool.ruff.lint]25select = ["ALL"]26ignore = [27 "ANN401", # `Any` - unavoidable when forwarding kwargs to crawl4ai and when returning parsed JSON28 "COM812", # conflicts with the formatter29 "D100", # undocumented public module30 "D104", # undocumented public package31 "D107", # undocumented __init__32 "ISC001", # conflicts with the formatter33 "TRY003", # long messages outside exception class - the messages are user-facing34 "EM101", # string literal in exception - see above35 "EM102", # f-string in exception - see above36]37
38[tool.ruff.lint.flake8-quotes]39inline-quotes = "single"40
41[tool.ruff.format]42quote-style = "single"1# CLAUDE.md2
3An Apify Actor wrapping the [crawl4ai](https://crawl4ai.com/) crawler. Published as4[janbuchar/crawl4ai](https://apify.com/janbuchar/crawl4ai).5
6When working in this repository, use the `actor-best-practices` skill. Note that it is written for TypeScript7Actors — this one is Python, so the Crawlee-specific rules (request queues, routers, `userData` typing) do not8apply. There is deliberately no Crawlee crawler here; crawl4ai owns the traversal.9
10Read `DEV_README.md` before changing anything. It documents the non-obvious parts: how multiple start URLs are11fed to a single-start-URL API, the migration-resume wiring, the `maxPages` off-by-one workaround, why the proxy12lives on `BrowserConfig`, and why there is no type checker.13
14The input schema must stay backwards compatible with the older version of this Actor — field names in15`.actor/input_schema.json` are part of the contract. Adding fields is fine; renaming or removing them is not.1[settings]2idiomatic_version_file_enable_tools = []3
4[tools."github:apify/apify-cli"]5version = "latest"6bin = "apify"7
8[tools."github:apify/apify-cli".platforms]9linux-x64 = { asset_pattern = "apify-*-linux-x64" }10linux-arm64 = { asset_pattern = "apify-*-linux-arm64" }11macos-x64 = { asset_pattern = "apify-*-darwin-x64" }12macos-arm64 = { asset_pattern = "apify-*-darwin-arm64" }13windows-x64 = { asset_pattern = "apify-*-windows-x64.exe" }14windows-arm64 = { asset_pattern = "apify-*-windows-arm64.exe" }1# Development2
3## Running locally4
5Dependencies are managed with uv; `uv.lock` is committed and is the source of truth.6
7```bash8uv sync9uv run playwright install chromium10
11# edit storage/key_value_stores/default/INPUT.json first12apify run13```14
15`apify run` picks up the `.venv` uv creates, so there is nothing to activate.16
17`apify run` purges local storage on every run, which wipes the request queue. To exercise the resume path18locally, run the module directly with purging off:19
20```bash21APIFY_PURGE_ON_START=0 .venv/bin/python -m src22```23
24Lint and format (no type checker — see below):25
26```bash27uv run ruff format src/ && uv run ruff check src/28```29
30## Architecture31
32There is no Crawlee crawler here, and no crawl4ai deep crawl strategy either. This Actor owns the traversal33loop; crawl4ai fetches and processes individual pages, and the Apify SDK supplies the frontier, storages,34proxy, concurrency signals and lifecycle events.35
36- `src/input_model.py` — pydantic mirror of `.actor/input_schema.json`, camelCase aliases via `to_camel`.37- `src/crawl_config.py` — translates the input into crawl4ai's `BrowserConfig` / `CrawlerRunConfig` /38 deep crawl strategy / extraction strategy.39- `src/dispatcher.py` — concurrency control wired to the platform's memory accounting.40- `src/frontier.py` — the crawl frontier, backed by an Apify request queue.41- `src/main.py` — drives the crawl, mirrors results into the dataset and key-value store, persists state.42
43### The frontier lives in the request queue44
45crawl4ai's own deep crawl strategies are **not** used. They keep the frontier in memory (`visited`, `depths`,46a pending list) and expect the whole thing to be snapshotted to survive a migration. That snapshot grew about47105 bytes per *discovered* URL, and discovery outruns crawling badly - a depth-2 run crawling 12 pages had48already discovered 281. At 100k discovered URLs that is a ~10 MB blob held in memory and rewritten on every49persist cycle.50
51Instead `Frontier` (`src/frontier.py`) puts the frontier in an Apify request queue, and `Crawler.run` drives52the loop directly: take a batch, hand it to `arun_many`, enqueue what the results link to. crawl4ai is used53only to fetch and process a single page. Consequences:54
55- Deduplication is the queue's `unique_key`, so there is no `visited` set to grow. The only thing persisted56 is three integers (`pushed`, `failed`, `deferred`) needed to keep counting across a migration.57- Interrupted work is left unhandled rather than snapshotted, so the next run picks it up. There is no resume58 branch anywhere - start URLs are re-added on every run and the queue ignores the ones it has seen.59- The queue's handled/total counters show up in the console and in the status message.60- `dispatcher=` can be passed to `arun_many` directly, so no crawler subclass is needed to inject it.61
62Strategy mapping, since the queue has a front and a back but no priority ordering:63
64| `crawlStrategy` | mechanism | faithful? |65|---|---|---|66| `bfs` | plain FIFO | yes |67| `dfs` | every child enqueued with `forefront=True`, batch size 1 | yes |68| `bestFirst` | children scoring above zero enqueued with `forefront=True` | approximate |6970`bestFirst` is documented as approximate on purpose. Three reasons, all inherent:71
72- there is no global ordering by score, only "in front of" or "behind" what is already queued;73- a URL already in the queue is not re-prioritised when a later page rediscovers it with a better score;74- a batch is dispatched concurrently, so within one batch pages finish in whatever order they finish. The75 prioritisation is only observable *across* batches, which means it fades as `maxConcurrency` grows.76 Demonstrate it with `maxConcurrency: 1`, where the queue order is the crawl order exactly.77
78Verify ordering against a strict tree, not a real site - on a cross-linked site the first page enqueues79almost everything and DFS legitimately looks flat, because rediscovered children are already queued and80dedup keeps them where they are. `docs/` has no fixture for this; generate a tree of static pages, serve it81on `127.0.0.1` (crawl4ai rejects dotless hosts, so not `localhost`) and give each page a few hundred words -82crawl4ai's anti-bot heuristic fails pages with little visible text. Expected output:83
84```85bfs: index@0 a@1 b@1 a1@2 a2@2 b1@2 b2@2 a11@3 a12@3 ...86dfs: index@0 b@1 b2@2 b22@3 b21@3 b1@2 b12@3 b11@3 a@1 ...87```88
89### Memory-adaptive concurrency90
91`maxConcurrency` is a ceiling, not a target. crawl4ai's `MemoryAdaptiveDispatcher` stops admitting new pages92above 90% memory use, resumes below 85%, and requeues in-flight pages above 95%.93
94Out of the box it measures pressure with `psutil.virtual_memory()`, which inside a container reports the95**host** — the Actor's own allocation is invisible, so it would keep opening browser tabs right up to an OOM96kill, or throttle because an unrelated tenant is busy. `ApifyMemoryAdaptiveDispatcher` replaces that reading97with `Event.SYSTEM_INFO`'s `memory_info.current_size` (this process plus its children, so browser98subprocesses count) over the allocation from `Actor.configuration.memory_mbytes`, falling back to99`available_memory_ratio` of the machine when running off-platform.100
101The injection points are unobvious, and both are deliberate:102
103- **The number**: `current_memory_percent` is overridden as a property whose setter *discards* what104 crawl4ai's monitor loop writes. That leaves all of crawl4ai's pressure/recovery/critical logic intact and105 swaps only the input, instead of reimplementing the monitor loop and having it drift.106- **The dispatcher**: it is passed to `arun_many` directly, which is only possible because this Actor drives107 the crawl loop itself. crawl4ai's deep crawl strategies call `arun_many` without one and offer no way to108 override it.109
110Two behaviours to know about, both reproducible with `ACTOR_MEMORY_MBYTES=256 apify run`:111
112- Above the critical threshold crawl4ai emits a **placeholder `CrawlResult`** with `success=False`,113 `error_message='Requeued due to critical memory pressure'` and `metadata['status'] == 'requeued'`. It is an114 internal control signal, not a page outcome. `_process_result` returns `False` for it, so the page is115 neither pushed to the dataset nor marked handled — it is reclaimed into the queue and retried later. Any116 request in a batch that never produces a result at all is reclaimed the same way.117- When the allocation is too small to crawl even one page, the dispatcher pauses and nothing ever drains.118 `memory_wait_timeout` is lowered from crawl4ai's 600s to **180s** so the run fails rather than idling on the119 clock, and the `MemoryError` is re-raised with a message that names the fix. The pause itself is logged with120 the percentage, which is usually enough to spot a wildly undersized allocation.121
122## Proxy123
124The proxy is set on `BrowserConfig`, not on `CrawlerRunConfig`. crawl4ai keys its browser context cache on the125run config's proxy settings, so a rotating per-request proxy would spawn a browser context per request. Its126`proxy_rotation_strategy` is also unusable under concurrency — it mutates the shared `CrawlerRunConfig` in127place, so concurrent crawls race over `proxy_config`. Apify Proxy rotates exit IPs on its own, so one static128upstream URL is the right answer here.129
130## No type checker131
132crawl4ai annotates optional parameters as `str = None` rather than `str | None = None` throughout. Running133basedpyright in `standard` mode produces 22 diagnostics, all of them false positives from those annotations.134Ruff is the only static check.135
136## Docker137
138The base image tag pins the Playwright version (`apify/actor-python-playwright:3.13-1.62.0`); `pyproject.toml`139pins the same version so that uv does not install a Playwright whose browsers are missing from the image. Keep140the two in sync. The browsers themselves live in `/pw-browsers`, outside any virtualenv, so building a fresh141project environment does not lose them.142
143`uv sync --frozen` installs into `/usr/src/app/.venv`, which the `PATH` in the Dockerfile puts ahead of the144system interpreter — the base image's launcher runs a plain `python -m src` and picks it up. `--frozen` also145makes the build fail if `uv.lock` has drifted from `pyproject.toml`.146
147The uv binary is copied from `astral/uv` on Docker Hub rather than `ghcr.io/astral-sh/uv`; ghcr refuses148anonymous pulls from at least some networks, and the base image comes from Docker Hub anyway.149
150`crawl4ai-setup` is not run during the build. It needs root to install browsers the base image already has, and151everything else it does happens lazily at runtime anyway.152
153Verify a build end to end with:154
155```bash156docker build -t actor-crawl4ai:test .157docker run --rm -v "$PWD/storage:/usr/src/app/storage" actor-crawl4ai:test158```version = 1revision = 3requires-python = "==3.13.*"
[[package]]name = "actor-crawl4ai"version = "0.1.0"source = { virtual = "." }dependencies = [ { name = "apify" }, { name = "crawl4ai" }, { name = "playwright" },]
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# Added by Apify CLInode_modules1"""Apify Actor wrapping the crawl4ai library."""2
3from __future__ import annotations4
5import json6from base64 import b64decode7from hashlib import sha2568from typing import TYPE_CHECKING, Any9
10from apify import Actor, Event11from apify.request_loaders import ApifyRequestList12from crawl4ai import AsyncWebCrawler13
14from .crawl_config import build_browser_config, build_filter_chain, build_run_config, build_url_scorer15from .dispatcher import build_dispatcher16from .frontier import build_frontier17from .input_model import ActorInput18
19if TYPE_CHECKING:20 from apify import ProxyInfo21 from apify.storages import KeyValueStore22 from crawl4ai import CrawlResult23 from crawlee import Request24
25 from .frontier import Frontier26
27STATE_KEY = 'CRAWL_STATE'28
29
30async def main() -> None:31 """Run the Actor."""32 async with Actor:33 actor_input = ActorInput.model_validate(await Actor.get_input())34
35 if actor_input.debug_log:36 Actor.log.setLevel('DEBUG')37
38 store = await Actor.open_key_value_store()39 frontier = await build_frontier(actor_input, build_filter_chain(actor_input), build_url_scorer(actor_input))40
41 # Re-adding the start URLs after a migration is a no-op, so this needs no resume branch.42 await frontier.add_start_urls(await _resolve_start_urls(actor_input))43
44 crawler = Crawler(actor_input, await store.get_value(STATE_KEY) or {}, store, frontier)45
46 Actor.on(Event.PERSIST_STATE, crawler.persist_state)47 Actor.on(Event.MIGRATING, crawler.stop)48 Actor.on(Event.ABORTING, crawler.stop)49
50 try:51 await crawler.run()52 except MemoryError as exc:53 # crawl4ai's own message names a threshold and a duration, neither of which tells anyone what54 # to change. Whatever is left in the queue is still there for a resurrected run to pick up.55 raise MemoryError(56 f'Ran out of memory with up to {actor_input.max_concurrency} pages in flight. Give the Actor '57 'a larger memory allocation, or lower Maximum concurrency.'58 ) from exc59 finally:60 await crawler.persist_state()61
62 await Actor.set_status_message(await crawler.status_message())63
64
65class Crawler:66 """Crawls whatever the frontier hands out and mirrors the results into Apify storages."""67
68 def __init__(69 self,70 actor_input: ActorInput,71 counts: dict[str, int],72 store: KeyValueStore,73 frontier: Frontier,74 ) -> None:75 self._input = actor_input76 self._store = store77 self._frontier = frontier78 self._stopped = False79 # Counters are restored so that a migrated run keeps counting towards `maxPages` and reports totals80 # for the whole crawl rather than for the current attempt.81 self._succeeded = counts.get('pushed', 0)82 self._failed = counts.get('failed', 0)83 self._deferred = counts.get('deferred', 0)84
85 async def run(self) -> None:86 """Crawl until the frontier empties, the page limit is hit, or the platform pulls the plug."""87 config = build_run_config(self._input)88 browser_config = build_browser_config(self._input, await _new_proxy_info(self._input))89
90 dispatcher = build_dispatcher(self._input)91 Actor.on(Event.SYSTEM_INFO, dispatcher.track_memory_usage)92
93 async with AsyncWebCrawler(config=browser_config) as crawl4ai:94 while not self._done():95 batch = await self._frontier.next_batch()96 if not batch:97 break98
99 by_url = {request.url: request for request in batch}100 results = await crawl4ai.arun_many(list(by_url), config=config, dispatcher=dispatcher)101
102 async for result in results:103 if request := by_url.pop(result.url, None):104 if await self._process_result(result, request):105 await self._frontier.mark_handled(request)106 else:107 await self._frontier.reclaim(request)108
109 if self._done():110 break111
112 # Whatever never produced a result, or arrived after the page limit was hit, goes back on113 # the queue instead of waiting for its lock to expire.114 for request in by_url.values():115 await self._frontier.reclaim(request)116
117 async def persist_state(self, _: object = None) -> None:118 """Snapshot the counters so that they survive a migration."""119 await self._store.set_value(120 STATE_KEY, {'pushed': self._succeeded, 'failed': self._failed, 'deferred': self._deferred}121 )122
123 async def stop(self, _: object = None) -> None:124 """Wind the crawl down. Whatever is left in the queue is picked up by the next run."""125 self._stopped = True126 await self.persist_state()127
128 async def status_message(self) -> str:129 """Summarize the run for the Actor run list."""130 message = f'✅ {self._succeeded} pages · ⚠️ {self._failed} failed · {await self._frontier.progress()}'131
132 if self._deferred:133 message += ' · 🧠 low memory'134
135 return f'{message} · interrupted, resumable' if self._stopped else message136
137 def _done(self) -> bool:138 limit = self._input.max_pages139 return self._stopped or (limit is not None and self._succeeded >= limit)140
141 async def _process_result(self, result: CrawlResult, request: Request) -> bool:142 """Record a crawled page. Returns False when crawl4ai deferred it and it still needs crawling."""143 metadata = result.metadata or {}144 metadata['depth'] = request.user_data.get('depth')145 metadata['parent_url'] = request.user_data.get('parentUrl')146
147 # When the dispatcher defers a URL under memory pressure it emits a placeholder result that looks148 # like a failed page. Reporting it would put a phantom failure in the dataset, and marking it handled149 # would lose the page outright.150 if metadata.get('status') == 'requeued':151 Actor.log.debug(f'Deferred {result.url} - not enough memory to crawl it right now')152 self._deferred += 1153
154 if self._deferred == 1:155 Actor.log.warning(156 'Out of memory - pages are being deferred and retried more slowly. Raise the '157 "Actor's memory allocation or lower Maximum concurrency."158 )159
160 return False161
162 if result.success:163 self._succeeded += 1164 Actor.log.info(f'Crawled {result.url} (depth {metadata["depth"]})')165 await self._frontier.enqueue_discovered(result, request)166 else:167 self._failed += 1168 Actor.log.warning(f'Failed to crawl {result.url}: {result.error_message}')169
170 item: dict[str, Any] = {171 'url': result.url,172 'success': result.success,173 'statusCode': result.status_code,174 'errorMessage': result.error_message or None,175 'depth': metadata['depth'],176 'parentUrl': metadata['parent_url'],177 'redirectedUrl': result.redirected_url if result.redirected_url != result.url else None,178 'metadata': metadata,179 'extracted_content': _parse_extracted_content(result.extracted_content),180 'markdown': None,181 'fitMarkdown': None,182 'html': None,183 'screenshot_url': None,184 'pdf_url': None,185 }186
187 if result.success:188 digest = sha256(result.url.encode()).hexdigest()189
190 item['markdown'] = await self._store_artifact(191 f'content_{digest}.md', str(result.markdown), 'text/markdown; charset=utf-8'192 )193 item['html'] = await self._store_artifact(f'content_{digest}.html', result.html, 'text/html; charset=utf-8')194
195 if fit_markdown := getattr(result.markdown, 'fit_markdown', None):196 item['fitMarkdown'] = await self._store_artifact(197 f'fit_{digest}.md', fit_markdown, 'text/markdown; charset=utf-8'198 )199
200 if result.screenshot:201 item['screenshot_url'] = await self._store_artifact(202 f'screenshot_{digest}.jpg', b64decode(result.screenshot), 'image/jpeg'203 )204
205 if result.pdf:206 item['pdf_url'] = await self._store_artifact(f'document_{digest}.pdf', result.pdf, 'application/pdf')207
208 await Actor.push_data(item)209 return True210
211 async def _store_artifact(self, key: str, value: str | bytes, content_type: str) -> str:212 await self._store.set_value(key, value, content_type=content_type)213 return await self._store.get_public_url(key)214
215
216async def _resolve_start_urls(actor_input: ActorInput) -> list[str]:217 """Expand the `requestListSources`-shaped input into a plain list of URLs."""218 request_list = await ApifyRequestList.open(request_list_sources_input=actor_input.start_urls)219
220 urls = []221 while request := await request_list.fetch_next_request():222 urls.append(request.url)223 await request_list.mark_request_as_handled(request)224
225 if not urls:226 raise ValueError('No start URLs were resolved from the `startUrls` input field.')227
228 return urls229
230
231async def _new_proxy_info(actor_input: ActorInput) -> ProxyInfo | None:232 # Passing an empty input to `create_proxy_configuration` still yields a default Apify Proxy233 # configuration, so an unset input field has to short-circuit here.234 if not actor_input.proxy_configuration:235 return None236
237 proxy_configuration = await Actor.create_proxy_configuration(actor_proxy_input=actor_input.proxy_configuration)238 return await proxy_configuration.new_proxy_info() if proxy_configuration else None239
240
241def _parse_extracted_content(extracted_content: str | None) -> Any:242 """Return the extraction strategy output as structured data instead of a JSON string."""243 if not extracted_content:244 return None245
246 try:247 return json.loads(extracted_content)248 except json.JSONDecodeError:249 return extracted_content1
1import asyncio2
3from .main import main4
5if __name__ == '__main__':6 asyncio.run(main())1"""The crawl frontier, backed by an Apify request queue."""2
3from __future__ import annotations4
5from typing import TYPE_CHECKING6from urllib.parse import urlparse7
8from apify import Actor9from crawl4ai.utils import normalize_url_for_deep_crawl10from crawlee import Request11
12if TYPE_CHECKING:13 from apify.storages import RequestQueue14 from crawl4ai import CrawlResult, FilterChain, URLScorer15
16 from .input_model import ActorInput17
18
19async def build_frontier(actor_input: ActorInput, filter_chain: FilterChain, url_scorer: URLScorer | None) -> Frontier:20 """Open the request queue and wrap it in a frontier."""21 return Frontier(22 queue=await Actor.open_request_queue(),23 actor_input=actor_input,24 filter_chain=filter_chain,25 url_scorer=url_scorer,26 )27
28
29class Frontier:30 """Decides what gets crawled next, and remembers it in an Apify request queue.31
32 Keeping the frontier in the queue instead of in memory means discovery survives a migration without33 snapshotting it, deduplication happens server-side rather than in an ever-growing `visited` set, and the34 queue's counters make the run's progress visible in the Apify console.35 """36
37 def __init__(38 self,39 queue: RequestQueue,40 actor_input: ActorInput,41 filter_chain: FilterChain,42 url_scorer: URLScorer | None,43 ) -> None:44 self._queue = queue45 self._max_depth = actor_input.max_crawl_depth46 self._include_external = actor_input.include_external_links47 self._strategy = actor_input.crawl_strategy48 self._filter_chain = filter_chain49 self._url_scorer = url_scorer50
51 # Depth-first only holds if the next page crawled is a child of the last one, which rules out52 # crawling a batch at a time. Every other strategy takes as much work as the dispatcher will accept.53 self._batch_size = 1 if self._strategy == 'dfs' else actor_input.max_concurrency * 254
55 async def add_start_urls(self, urls: list[str]) -> None:56 """Enqueue the start URLs. Safe to repeat - the queue ignores URLs it has already seen."""57 await self._queue.add_requests(58 [Request.from_url(url, user_data={'depth': 0, 'parentUrl': None}) for url in urls]59 )60
61 async def next_batch(self) -> list[Request]:62 """Take the next chunk of work. An empty result means the crawl is done."""63 batch = []64
65 while len(batch) < self._batch_size:66 request = await self._queue.fetch_next_request()67 if request is None:68 break69
70 batch.append(request)71
72 return batch73
74 async def mark_handled(self, request: Request) -> None:75 """Record that a request is done, so a resumed run does not crawl it again."""76 await self._queue.mark_request_as_handled(request)77
78 async def reclaim(self, request: Request) -> None:79 """Put a request back for a later attempt, when it could not be crawled this time round."""80 await self._queue.reclaim_request(request)81
82 async def enqueue_discovered(self, result: CrawlResult, request: Request) -> None:83 """Enqueue the links found on a crawled page."""84 depth = request.user_data.get('depth', 0)85 assert isinstance(depth, int) # noqa: S10186
87 if depth >= self._max_depth:88 return89
90 links = list(result.links.get('internal', []))91 if self._include_external:92 links += result.links.get('external', [])93
94 # Best-first wants the promising URLs crawled first. The queue has no priority ordering, only a95 # front and a back, so a URL that scores at all jumps ahead of everything discovered so far.96 ordinary: list[Request] = []97 prioritized: list[Request] = []98
99 for url in await self._eligible_urls(links, result.url):100 score = self._url_scorer.score(url) if self._url_scorer else 0101 discovered = Request.from_url(102 url,103 user_data={'depth': depth + 1, 'parentUrl': result.url, 'score': score},104 )105
106 target = prioritized if self._is_prioritized(score) else ordinary107 target.append(discovered)108
109 if ordinary:110 await self._queue.add_requests(ordinary)111
112 if prioritized:113 # Without waiting, `add_requests` can return before the queue has the URLs, and the next fetch114 # hands back a sibling instead of the child that was just put in front - which is not depth-first115 # in any recognisable sense. The extra round-trip only applies to strategies that jump the queue.116 await self._queue.add_requests(prioritized, forefront=True, wait_for_all_requests_to_be_added=True)117
118 async def progress(self) -> str:119 """Describe how much of the queue is left, for the run status message."""120 metadata = await self._queue.get_metadata()121 return f'{metadata.handled_request_count}/{metadata.total_request_count} requests'122
123 def _is_prioritized(self, score: float) -> bool:124 if self._strategy == 'dfs':125 # Putting children in front of their siblings is what makes the traversal depth-first.126 return True127
128 return self._strategy == 'bestFirst' and score > 0129
130 async def _eligible_urls(self, links: list[dict], source_url: str) -> list[str]:131 """Normalize the discovered links and drop the ones the crawl is not interested in."""132 eligible = []133 seen = set()134
135 for link in links:136 url = normalize_url_for_deep_crawl(link.get('href'), source_url)137
138 if not url or url in seen or not _is_crawlable(url):139 continue140
141 seen.add(url)142
143 if await self._filter_chain.apply(url):144 eligible.append(url)145
146 return eligible147
148
149def _is_crawlable(url: str) -> bool:150 parsed = urlparse(url)151 return parsed.scheme in {'http', 'https'} and '.' in parsed.netloc1"""Translation layer between the Actor input and crawl4ai's configuration objects."""2
3from __future__ import annotations4
5import json6from typing import TYPE_CHECKING7
8from crawl4ai import (9 BM25ContentFilter,10 BrowserConfig,11 CacheMode,12 CrawlerRunConfig,13 DefaultMarkdownGenerator,14 DomainFilter,15 ExtractionStrategy,16 FilterChain,17 JsonCssExtractionStrategy,18 KeywordRelevanceScorer,19 LLMConfig,20 LLMExtractionStrategy,21 ProxyConfig,22 PruningContentFilter,23 URLFilter,24 URLPatternFilter,25)26
27if TYPE_CHECKING:28 from apify import ProxyInfo29
30 from .input_model import ActorInput31
32
33def build_browser_config(actor_input: ActorInput, proxy_info: ProxyInfo | None) -> BrowserConfig:34 """Build the browser configuration.35
36 The proxy is configured here rather than on `CrawlerRunConfig`, because crawl4ai keys its browser37 context cache on the run config's proxy - a per-request proxy would spawn a browser context per request.38 Apify Proxy rotates the exit IP on its own, so a single static upstream URL is enough.39 """40 return BrowserConfig(41 headless=True,42 verbose=actor_input.debug_log,43 proxy_config=ProxyConfig(44 server=f'{proxy_info.scheme}://{proxy_info.hostname}:{proxy_info.port}',45 username=proxy_info.username,46 password=proxy_info.password,47 )48 if proxy_info49 else None,50 )51
52
53def build_run_config(actor_input: ActorInput) -> CrawlerRunConfig:54 """Build the per-run crawl configuration."""55 return CrawlerRunConfig(56 stream=True,57 cache_mode=CacheMode.BYPASS,58 semaphore_count=actor_input.max_concurrency,59 max_retries=actor_input.max_retries,60 page_timeout=actor_input.page_timeout_secs * 1000,61 wait_until=actor_input.wait_until,62 wait_for=actor_input.wait_for,63 js_code=actor_input.js_code,64 magic=actor_input.magic_mode,65 scan_full_page=actor_input.scan_full_page,66 check_robots_txt=actor_input.respect_robots_txt,67 css_selector=actor_input.css_selector,68 excluded_tags=actor_input.excluded_tags,69 screenshot=actor_input.save_screenshots,70 pdf=actor_input.save_pdfs,71 markdown_generator=_build_markdown_generator(actor_input),72 extraction_strategy=build_extraction_strategy(actor_input),73 verbose=actor_input.debug_log,74 )75
76
77def build_extraction_strategy(actor_input: ActorInput) -> ExtractionStrategy | None:78 """Build the structured data extraction strategy, if any."""79 if actor_input.extraction_strategy is None:80 return None81
82 if actor_input.extraction_strategy == 'cosine':83 raise ValueError(84 'The cosine extraction strategy has been removed - it required PyTorch and sentence-transformers, '85 'which would have made this Actor several gigabytes larger. '86 'Use the LLM or JsonCSS extraction strategy instead.'87 )88
89 if actor_input.extraction_strategy == 'jsonCss':90 if not actor_input.json_css_schema:91 raise ValueError('The jsonCss extraction strategy requires the `jsonCssSchema` input field to be set.')92
93 return JsonCssExtractionStrategy(schema=json.loads(actor_input.json_css_schema))94
95 schema = json.loads(actor_input.llm_schema) if actor_input.llm_schema else None96
97 llm_config = LLMConfig(api_token=actor_input.llm_api_token, base_url=actor_input.llm_base_url)98 if actor_input.llm_provider:99 llm_config.provider = actor_input.llm_provider100
101 return LLMExtractionStrategy(102 llm_config=llm_config,103 instruction=actor_input.llm_instruction,104 schema=schema,105 extraction_type='schema' if schema else 'blocks',106 )107
108
109def _build_markdown_generator(actor_input: ActorInput) -> DefaultMarkdownGenerator:110 """Build the markdown generator, optionally with a content filter producing `fit_markdown`."""111 content_filter = None112
113 if actor_input.markdown_content_filter == 'pruning':114 content_filter = PruningContentFilter()115 elif actor_input.markdown_content_filter == 'bm25':116 if not actor_input.markdown_content_filter_query:117 raise ValueError('The bm25 markdown content filter requires the `markdownContentFilterQuery` input field.')118
119 content_filter = BM25ContentFilter(user_query=actor_input.markdown_content_filter_query)120
121 return DefaultMarkdownGenerator(content_filter=content_filter)122
123
124def build_url_scorer(actor_input: ActorInput) -> KeywordRelevanceScorer | None:125 """Build the scorer that decides which discovered links look most promising."""126 return KeywordRelevanceScorer(keywords=actor_input.keywords) if actor_input.keywords else None127
128
129def build_filter_chain(actor_input: ActorInput) -> FilterChain:130 """Build the filters deciding which discovered links are followed."""131 filters: list[URLFilter] = []132
133 if actor_input.allowed_domains or actor_input.blocked_domains:134 filters.append(135 DomainFilter(136 allowed_domains=actor_input.allowed_domains,137 blocked_domains=actor_input.blocked_domains,138 )139 )140
141 if actor_input.include_url_globs:142 filters.append(URLPatternFilter(patterns=actor_input.include_url_globs))143
144 if actor_input.exclude_url_globs:145 filters.append(URLPatternFilter(patterns=actor_input.exclude_url_globs, reverse=True))146
147 return FilterChain(filters)1"""Memory-adaptive concurrency driven by the Apify platform's own memory accounting."""2
3from __future__ import annotations4
5from typing import TYPE_CHECKING, Any6
7import psutil8from apify import Actor9from crawl4ai import MemoryAdaptiveDispatcher, RateLimiter10
11if TYPE_CHECKING:12 from apify import EventSystemInfoData13
14 from .input_model import ActorInput15
16
17def build_dispatcher(actor_input: ActorInput) -> ApifyMemoryAdaptiveDispatcher:18 """Build the dispatcher that decides how many pages are crawled at once."""19 return ApifyMemoryAdaptiveDispatcher(20 memory_limit_bytes=_memory_limit_bytes(),21 max_session_permit=actor_input.max_concurrency,22 # When the allocation is too small to crawl even one page, nothing ever drains and the crawl simply23 # stops. crawl4ai gives that ten minutes before failing; three is plenty to ride out a real spike,24 # and the rest is just billed idling.25 memory_wait_timeout=180,26 # Mirrors the rate limiter crawl4ai would have built for the dispatcher it creates implicitly,27 # so that supplying our own does not silently change the pacing between requests.28 rate_limiter=RateLimiter(base_delay=(0.1, 0.4)),29 )30
31
32class ApifyMemoryAdaptiveDispatcher(MemoryAdaptiveDispatcher):33 """crawl4ai's memory-adaptive dispatcher, fed the Actor's memory usage instead of the whole machine's.34
35 crawl4ai measures pressure with `psutil.virtual_memory()`, which inside a container reports the host.36 The Actor's own limit is invisible to it, so it would happily keep launching browser tabs right up to37 an OOM kill - or throttle for no reason because an unrelated tenant is busy.38
39 Overriding the attribute crawl4ai's monitor loop writes to leaves all of its pressure, recovery and40 critical-mode handling in place and only replaces the number it reacts to.41 """42
43 def __init__(self, memory_limit_bytes: float, **kwargs: Any) -> None:44 # Must precede `super().__init__`, which assigns to `current_memory_percent`.45 self._used_percent = 0.046 self._memory_limit_bytes = memory_limit_bytes47 self._reported_pressure = False48 super().__init__(**kwargs)49
50 @property51 def current_memory_percent(self) -> float:52 """Share of the Actor's memory allocation currently in use, as a percentage."""53 return self._used_percent54
55 @current_memory_percent.setter56 def current_memory_percent(self, _: float) -> None:57 """Discard crawl4ai's host-wide reading; `track_memory_usage` is the only writer."""58
59 async def track_memory_usage(self, event_data: EventSystemInfoData) -> None:60 """Record the latest platform memory snapshot. Register as an `Event.SYSTEM_INFO` listener."""61 # `current_size` covers this process and its children, so the browser subprocesses are included.62 self._used_percent = 100 * event_data.memory_info.current_size.bytes / self._memory_limit_bytes63
64 # Under pressure crawl4ai silently stops starting new pages, which looks like a stall from outside.65 if self.memory_pressure_mode != self._reported_pressure:66 self._reported_pressure = self.memory_pressure_mode67 state = 'paused, memory pressure' if self.memory_pressure_mode else 'resumed'68 Actor.log.info(f'Crawling {state} ({self._used_percent:.0f}% of the memory allocation in use)')69
70
71def _memory_limit_bytes() -> float:72 """Determine how much memory this run is allowed to use, the same way Crawlee's snapshotter does."""73 configuration = Actor.configuration74
75 if configuration.memory_mbytes:76 return configuration.memory_mbytes * 1024 * 102477
78 # Outside the platform there is no allocation to speak of, so fall back to a slice of the machine.79 return psutil.virtual_memory().total * configuration.available_memory_ratio1from __future__ import annotations2
3from typing import Annotated, Any, Literal4
5from pydantic import AliasGenerator, BaseModel, ConfigDict, Field6from pydantic.alias_generators import to_camel7
8CrawlStrategyName = Literal['bfs', 'dfs', 'bestFirst']9ExtractionStrategyName = Literal['llm', 'jsonCss', 'cosine']10MarkdownContentFilterName = Literal['none', 'pruning', 'bm25']11WaitUntil = Literal['domcontentloaded', 'load', 'networkidle', 'commit']12
13
14class ActorInput(BaseModel):15 """Actor input, mirroring `.actor/input_schema.json`."""16
17 model_config = ConfigDict(18 alias_generator=AliasGenerator(validation_alias=to_camel),19 populate_by_name=True,20 extra='ignore',21 )22
23 start_urls: Annotated[list[dict[str, Any]], Field(min_length=1)]24
25 max_crawl_depth: int = 226 max_pages: int | None = None27 crawl_strategy: CrawlStrategyName = 'bfs'28 keywords: list[str] | None = None29 include_external_links: bool = False30
31 include_url_globs: list[str] | None = None32 exclude_url_globs: list[str] | None = None33 allowed_domains: list[str] | None = None34 blocked_domains: list[str] | None = None35 respect_robots_txt: bool = False36
37 proxy_configuration: dict[str, Any] | None = None38 max_concurrency: Annotated[int, Field(ge=1)] = 539 max_retries: Annotated[int, Field(ge=0)] = 240 page_timeout_secs: Annotated[int, Field(ge=1)] = 6041 wait_until: WaitUntil = 'domcontentloaded'42 magic_mode: bool = True43 scan_full_page: bool = False44
45 css_selector: str | None = None46 excluded_tags: list[str] | None = None47 markdown_content_filter: MarkdownContentFilterName = 'none'48 markdown_content_filter_query: str | None = None49 wait_for: str | None = None50 js_code: str | None = None51
52 save_screenshots: bool = False53 save_pdfs: bool = False54
55 extraction_strategy: ExtractionStrategyName | None = None56 llm_provider: str | None = None57 llm_api_token: str | None = None58 llm_base_url: str | None = None59 llm_instruction: str | None = None60 llm_schema: str | None = None61 json_css_schema: str | None = None62
63 debug_log: bool = False{ "$schema": "https://apify.com/schemas/v1/input.ide.json", "title": "Crawl4AI settings", "description": "See https://docs.crawl4ai.com/ for an explanation of the individual options.", "type": "object", "schemaVersion": 1, "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "URLs to start with", "prefill": [{ "url": "https://docs.crawl4ai.com" }], "editor": "requestListSources" }, "maxCrawlDepth": { "title": "Maximum crawl depth", "type": "integer", "description": "How many levels of links should the crawler follow. The Start URLs have a depth of 0, all links found there have a depth of 1, and so on.", "minimum": 0, "default": 2 }, "maxPages": { "title": "Maximum pages", "type": "integer", "description": "Stop the crawl after this many pages have been crawled successfully. Leave empty for no limit.", "minimum": 1, "nullable": true }, "crawlStrategy": { "title": "Crawl strategy", "type": "string", "description": "How the crawler traverses the link graph. `bestFirst` visits the most promising URLs first and requires **Keywords** to be useful.", "enum": ["bfs", "dfs", "bestFirst"], "enumTitles": ["Breadth-first", "Depth-first", "Best-first (keyword scored)"], "editor": "select", "default": "bfs" }, "keywords": { "title": "Keywords", "type": "array", "description": "Used by the `bestFirst` strategy to score URLs. URLs containing these words are crawled sooner.", "editor": "stringList", "nullable": true }, "includeExternalLinks": { "title": "Follow external links", "type": "boolean", "description": "Follow links pointing outside of the domain of the page they were found on. Combine with **Allowed domains** to keep the crawl bounded.", "default": false }, "includeUrlGlobs": { "sectionCaption": "Crawl scope", "title": "Include URL globs", "type": "array", "description": "Only follow links matching at least one of these glob patterns, e.g. `*/docs/*`. Start URLs are always crawled.", "editor": "stringList", "nullable": true }, "excludeUrlGlobs": { "title": "Exclude URL globs", "type": "array", "description": "Never follow links matching any of these glob patterns.", "editor": "stringList", "nullable": true }, "allowedDomains": { "title": "Allowed domains", "type": "array", "description": "Only follow links on these domains. Leave empty to allow all.", "editor": "stringList", "nullable": true }, "blockedDomains": { "title": "Blocked domains", "type": "array", "description": "Never follow links on these domains.", "editor": "stringList", "nullable": true }, "respectRobotsTxt": { "title": "Respect robots.txt", "type": "boolean", "description": "Skip URLs disallowed by the target website's robots.txt.", "default": false }, "proxyConfiguration": { "sectionCaption": "Browser and network", "title": "Proxy configuration", "type": "object", "editor": "proxy", "description": "Select proxies to be used by your crawler.", "prefill": { "useApifyProxy": true } }, "maxConcurrency": { "title": "Maximum concurrency", "type": "integer", "description": "Upper limit on how many pages are crawled in parallel. The crawler backs off below this on its own when the run approaches its memory allocation, so treat it as a ceiling rather than a target.", "minimum": 1, "default": 5 }, "maxRetries": { "title": "Maximum retries", "type": "integer", "description": "How many times to retry a page that failed to load.", "minimum": 0, "default": 2 }, "pageTimeoutSecs": { "title": "Page timeout", "type": "integer", "description": "How long to wait for a page to load before giving up, in seconds.", "minimum": 1, "default": 60, "unit": "seconds" }, "waitUntil": { "title": "Wait until", "type": "string", "description": "Which page lifecycle event to consider as \"loaded\".", "enum": ["domcontentloaded", "load", "networkidle", "commit"], "editor": "select", "default": "domcontentloaded" }, "magicMode": { "title": "Use magic mode", "type": "boolean", "default": true, "description": "Masks browser automation signals, simulates human-like behavior, overrides navigator properties, handles cookie consent popups, manages browser fingerprinting and randomizes timing patterns." }, "scanFullPage": { "title": "Scroll through the whole page", "type": "boolean", "default": false, "description": "Scroll to the bottom of the page before extracting content. Necessary for lazy-loaded and infinite-scroll pages." }, "cssSelector": { "sectionCaption": "Content processing", "title": "CSS selector", "description": "Ensures only a part of the website is processed", "type": "string", "nullable": true, "editor": "textfield" }, "excludedTags": { "title": "Excluded tags", "type": "array", "description": "HTML tags to strip before extracting content, e.g. `nav`, `footer`, `aside`.", "editor": "stringList", "nullable": true }, "markdownContentFilter": { "title": "Markdown content filter", "type": "string", "description": "Produces an additional pruned `fit_markdown` alongside the raw one. `pruning` drops low-density boilerplate, `bm25` keeps content relevant to a query.", "enum": ["none", "pruning", "bm25"], "enumTitles": ["None", "Pruning", "BM25 (query relevance)"], "editor": "select", "default": "none" }, "markdownContentFilterQuery": { "title": "Markdown content filter query", "type": "string", "description": "Query used by the BM25 markdown content filter.", "editor": "textfield", "nullable": true }, "waitFor": { "title": "Wait for", "description": "CSS selector or JS function to wait for before processing a page", "editor": "textarea", "type": "string", "nullable": true }, "jsCode": { "title": "Javascript code to execute on each page", "type": "string", "description": "Function executed for each request", "nullable": true, "editor": "javascript" }, "saveScreenshots": { "sectionCaption": "Saved artifacts", "title": "Save screenshots", "description": "Should the crawler save screenshots?", "type": "boolean", "default": false }, "savePdfs": { "title": "Save PDFs", "description": "Render each page to a PDF and store it in the key-value store.", "type": "boolean", "default": false }, "extractionStrategy": { "sectionCaption": "Structured data extraction", "title": "Extraction strategy", "description": "Specifies how structured data is extracted from each page", "type": "string", "enum": ["llm", "jsonCss", "cosine"], "enumTitles": ["LLM", "JsonCSS", "Cosine (removed)"], "editor": "select", "nullable": true }, "llmProvider": { "sectionCaption": "LLM extraction settings", "title": "LLM provider", "description": "LiteLLM-style model identifier of the LLM used to extract data, e.g. `openai/gpt-4o` or `anthropic/claude-sonnet-4-5`.", "type": "string", "nullable": true, "editor": "textfield" }, "llmApiToken": { "title": "API token", "description": "Token used for authentication with the LLM provider", "type": "string", "editor": "textfield", "isSecret": true, "nullable": true }, "llmBaseUrl": { "title": "Base URL", "description": "Custom API endpoint of the LLM provider.", "type": "string", "editor": "textfield", "nullable": true }, "llmInstruction": { "title": "Instruction", "description": "Instructions (prompt) for the LLM", "editor": "textarea", "type": "string", "nullable": true }, "llmSchema": { "title": "Schema", "description": "JSON schema describing the shape of the data the LLM should return. Leave empty to let the LLM decide.", "editor": "textarea", "type": "string", "nullable": true }, "jsonCssSchema": { "sectionCaption": "JsonCSS extraction settings", "title": "JsonCss schema", "description": "Description of the data to be extracted, see https://docs.crawl4ai.com/extraction/no-llm-strategies/", "type": "string", "editor": "textarea", "nullable": true }, "cosineSemanticFilter": { "sectionCaption": "Cosine extraction settings (removed)", "title": "Semantic filter", "description": "**Removed.** The cosine extraction strategy required PyTorch and is no longer supported. Use the LLM or JsonCSS strategy instead.", "type": "string", "nullable": true, "editor": "textfield" }, "cosineWordCountThreshold": { "title": "Word count threshold", "description": "**Removed.** See above.", "type": "integer", "nullable": true }, "cosineLinkageMethod": { "title": "Linkage method", "description": "**Removed.** See above.", "type": "string", "nullable": true, "editor": "textfield" }, "cosineTopK": { "title": "Top K", "description": "**Removed.** See above.", "type": "integer", "nullable": true }, "cosineModelName": { "title": "Model name", "description": "**Removed.** See above.", "type": "string", "nullable": true, "editor": "textfield" }, "debugLog": { "sectionCaption": "Developer settings", "title": "Debug logging", "description": "Print debug-level log messages", "type": "boolean", "default": false } }, "required": ["startUrls"]}{ "$schema": "https://apify.com/schemas/v1/dataset.ide.json", "actorSpecification": 1, "fields": {}, "views": { "overview": { "title": "Overview", "transformation": { "fields": ["url", "depth", "statusCode", "markdown", "html"] }, "display": { "component": "table", "properties": { "url": { "label": "URL", "format": "link" }, "depth": { "label": "Depth", "format": "number" }, "statusCode": { "label": "Status", "format": "number" }, "markdown": { "label": "Markdown", "format": "link" }, "html": { "label": "HTML", "format": "link" } } } } }}{ "$schema": "https://apify.com/schemas/v1/output.ide.json", "actorOutputSchemaVersion": 1, "title": "Output schema", "properties": { "results": { "type": "string", "title": "Crawled pages", "template": "{{links.apiDefaultDatasetUrl}}/items" }, "content": { "type": "string", "title": "Markdown, HTML and screenshots", "template": "{{links.apiDefaultKeyValueStoreUrl}}/keys" } }}{ "$schema": "https://apify.com/schemas/v1/actor.ide.json", "actorSpecification": 1, "name": "crawl4ai", "title": "Crawl4AI", "description": "🔥🕷️ Crawl4AI: Open-source LLM Friendly Web Crawler & scraper", "version": "0.1", "buildTag": "latest", "inputSchema": "./input_schema.json", "outputSchema": "./output_schema.json", "storages": { "dataset": "./dataset_schema.json" }, "dockerfile": "../Dockerfile"}name: Checkson: workflow_call:
jobs: lint: name: Lint runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - uses: astral-sh/setup-uv@v6 - uses: actions/setup-python@v5 with: python-version: "3.13" - run: uv sync --frozen - run: uv run ruff check . - run: uv run ruff format --check .
typos: name: Typos runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - uses: crate-ci/typos@v1
actionlint: name: Actionlint runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - uses: rhysd/actionlint@v1.7.12name: CI (main)on: push: branches: - main
jobs: checks: uses: ./.github/workflows/_checks.yaml
deploy: name: Deploy to Apify needs: checks runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - uses: apify/push-actor-action@v1 with: token: ${{ secrets.APIFY_TOKEN }}name: CI (PR)on: pull_request: branches: - main
jobs: checks: uses: ./.github/workflows/_checks.yaml