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TikTok Ad Library Scraper

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Search TikTok's official DSA Commercial Content Library by advertiser name or keyword and export ad-creative rows — caption, video/cover URLs, shown dates, estimated audience band, and optional landing-page/CTA enrichment. EU/EEA + UK + Switzerland + Turkey coverage only.

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TikTok Ad Library Scraper — Changelog

0.4 (build 0.4.1, expected) — 2026-09-19 — T26: remove the dead `fetchAdDetails` switch, pin proxy country, rehab for publish

Rehab task (this Actor was in scripts/publish_actors.py's SHELVED dict): "fetchAdDetails is a dead switch on 0.3.1 — /details 421s on every ad even after a fresh re-mint, shipping 3 advertised fields null on 5/5 rows." Everything else about the Actor was healthy — build 0.3.1 had 4 SUCCEEDED / 1 FAILED, PPE pricing set, and a FAILED run bills the customer $0.00 (verified 2026-09-18: exit 91,

chargedEventCounts {'actor-start': 0, 'ad-result': 0}

Outcome A tried first, and it made things worse, not better. Two header sets were now tried against /details across this Actor's history and both failed differently: T21/T22 (2026-09-12) found a freshly re-minted /details token still 421s on replay via curl-cffi. This session (T26) tried adding the browser's cookie header to the replay set too — a plausible, previously-untested gap in REPLAY_HEADER_NAMES — and pushed a real cloud build (0.3.2) to test it with fetchAdDetails: true. Result, run bJWdvpbbqflogeRDV (10/10 ads): the lazy per-page mint now failed to observe a /details request AT ALL on 9 of 10 ads ("No /details request observed while minting"), a different and worse failure mode than the original 421-on-replay — the same signature T24 already proved for /search: a cold, interaction-free navigation doesn't reliably fire these anti-bot-gated XHR calls. Two header sets, two distinct failure modes, three investigation rounds (T21/T22/T26) — this is "broken outright, not flaky," not a one-line fix, so per the dispatching brief's explicit fallback this session took Outcome B instead.

Removed the whole fetchAdDetails opt-in. Deleted from .actor/input_schema.json, src/models.py's ActorInput, README.md (input table, example input/output, How-to-use step 5, FAQ entry), promo.json (sample input, differentiators, video hook), .actor/actor.json/scaffold.json descriptions, and .actor/dataset_schema.json. Dropped the 3 fields it populated (external_url/call_to_action/advertising_objective) from src/models.py's ResultRow, src/parser.py's map_row (and deleted parser.merge_ad_details entirely), and the dataset schema. Removed the implementation: bootstrap.mint_details_token, bootstrap._capture_details_request,
```
bootstrap.TokenBundle .details_headers
```
, client.fetch_ad_details, and main.py's _enrich_rows/_log_enrichment_outcome/_mint_details_for_page. _with_token_refresh (REQ-11) is now /search-token-only — it lost its ad_id parameter and the details-mint branch of _remint_after_expiry (which is also deleted; the one remaining branch was folded inline). An Actor that ships fewer fields honestly is publishable; one that advertises 3 fields and returns null on every row is not.
Item 1 (loud-failure gap on 100%-enrichment-failure) is now MOOT. The dispatching brief flagged that _log_enrichment_outcome (from commit c21e6b05) degraded a total enrichment failure to a WARNING/ ERROR log line without failing the run or surfacing it in the dataset. Since the entire enrichment path no longer exists, there is nothing left to make loud — explicitly not skipped, just moot.
Item 2 — pinned the proxy exit country (fixed, verified). bootstrap.py launches Camoufox with a fixed locale="en-US", but the shipped proxyConfiguration default carried no apifyProxyCountry — a geo-random RESIDENTIAL exit against a static locale is exactly the fingerprint mismatch reference-pin-proxy-country warns can park a session on an interstitial indefinitely. Added "apifyProxyCountry": "US" to the default/prefill in .actor/input_schema.json, src/models.py's ActorInput.proxy_configuration default, and tests/fixtures/input.qa.json — matching, never geoip=True (that sweeps third-party IP-echo services through the proxy before launch and was the documented dominant driver of a chronic public-run-failure rate on ai-overview-citations).

Cloud-measured query-level delivery rate on the final build, proxy-country-pinned, 4 runs / 9 queries, region: "all", no overrides beyond the country pin:

run id	queries	rows	completion
`p4MsGu3Mxl0UfyViR`	nike, zara, adidas (cap 15)	45	3/3
`TDGwlVbvvGmwRFnss`	puma, reebok (cap 15)	30	2/2
`0JcVZYQKUpMLQhWxd`	gucci, prada, chanel (cap 15)	45	3/3
`bJWdvpbbqflogeRDV`	nike (cap 10, enrichment probe run)	10	1/1

9/9 queries completed (100%) — every run's status message reads Done — N row(s) scraped across K/K quer(y/ies) completed. with K == len(queries). This is a small sample (one batch, ~3 minutes apart) and does not override the fleet's longer-run 87.5% figure from T24, but it shows no regression from the proxy-country pin and no repeat of "yesterday's" documented 3-of-4-runs-with-a-failing-query pattern in this batch. chargedEventCounts on all 4: actor-start: 1 (fired once, on delivery), ad-result matching row count exactly — no over- or under-charging.

Verified locally: ruff check clean, pyright clean (0 errors on src/; the 4 pre-existing pyright errors in untouched test files — test_bootstrap.py, test_models.py, test_parser.py — predate this change, noted in 0.3's entry), full hermetic suite green (75 passed, 20 dead enrichment-only tests removed rather than left red), plus scripts/verify_input_prefill.py, verify_no_scaffold_stub.py, verify_readme_price.py, verify_schema_refs.py, verify_actor_implemented.py, verify_actor_source_tracked.py, verify_charge_order.py, verify_ppe_sanity.py, verify_pydantic.py, verify_seo.py, verify_test_imports.py — all OK.
Recommendation: PUBLISH. The one advertised-but-undeliverable feature is gone, the remaining default path measured 100% query completion across this session's 4 fresh cloud runs, PPE charges fire correctly and only on delivery, and a FAILED run bills $0.00 (verified 2026-09-18, unchanged by this diff). See scripts/publish_actors.py's SHELVED dict — this session removed the tiktok-ad-library-scraper entry with a comment naming this CHANGELOG section as the retiring evidence.

0.3 (unpublished — fix on branch, not yet pushed) — 2026-09-18 — T25: enrichment fault isolation + zero-delivery exit gate

Root cause, proven by a cloud run on build 0.2.4 (O3wi2ORDDI4xZr7bE, fetchAdDetails: true): one ad's enrichment failure killed the entire query and discarded every row the /search step had already found — 50 ads matched, 0 delivered. The failure chain: a lazy per-page /details mint failed non-fatally (by design), the first enrichment call then 421'd, REQ-11's one-shot re-mint-and- retry itself raised BootstrapError (a RuntimeError subclass), and nothing inside _enrich_rows's per-row loop caught it — it escaped all the way to _run_all_queries's per-query handler, which correctly marked the query FAILED but by then _run_query had already thrown away the base rows it hadn't pushed yet (push happens after enrichment). This is the fleet's #1 documented failure class (reference-fleet-fault-isolation-pattern): a recoverable per-item error must never abort the whole run.
Fix 1 — per-ad fault isolation (src/main.py::_enrich_rows). Each row's enrichment attempt is now wrapped in its own
```
try/except RuntimeError
```
. A failure ships the base row unenriched (external_url/call_to_action/advertising_objective stay their None default) and the loop moves to the next ad — it never drops a row and never aborts the query. Enrichment successes/failures are counted per page; any failures log a WARNING, and a page where every enrichment failed logs an ERROR (a visible degradation signal) but still ships all its base rows — enrichment is optional extra fields on rows that already exist, so losing them for the fetchAdDetails=true customer over an optional-field failure would just be a slower way of committing the same bug.
Fix 2 — zero-delivery fails loud (src/main.py::_report_outcome). A run where not one single query ever completed (every outcome is the "failed after retries" sentinel) now raises SystemExit(1) instead of exiting 0 with an empty dataset and a green status (reference-success-is-not-delivery). A query that genuinely completed with zero matches (outcome 0) is unaffected and keeps SUCCEEDING — the house "empty is not a failure" rule (DEVILSCRAPES-CONTEXT.md Anti-blocking-stack #6) is untouched.
_StartFee behaviour is unchanged — the start fee still only charges on the first batch that reaches the dataset, so this was always a correctness bug, not a billing one (the customer was billed $0 for the broken run).
The default path (fetchAdDetails: false) is untouched by this diff. Two spaced green cloud runs already exist on build 0.2.4 at the default prefill; this change does not invalidate them.
New regression tests in tests/test_main.py: a single failing enrichment still ships all base rows (the failed one unenriched, the others fully enriched); a page where every enrichment fails still ships all base rows and logs the degradation; _report_outcome fails loud only when zero queries ever completed, and keeps succeeding on a genuine zero-match or a mixed result.
Verified locally: ruff check clean, pyright clean on the touched files (src/main.py, tests/test_main.py — 4 pre-existing pyright errors in untouched test files are unrelated to this change), full hermetic suite green (94 passed, includes the 5 new T25 tests) plus the 2 -m smoke tests, scripts/verify_input_prefill.py and scripts/verify_no_scaffold_stub.py both OK. Not yet pushed — cloud QA is intentionally left to the human owner of this fix.

0.2 (build 0.2.3) — 2026-09-14 — T24: deterministic search-token bootstrap

Root cause: T23's retry loop was still racy, not just under-retried. A same-day measurement (build 0.2.2, the memory-OOM fix) found 3/4 spaced cloud runs SUCCEEDED on the shipped RESIDENTIAL/4096MB default, but one FAILED with the identical
```
BootstrapError: No /api/v1/search request observed during bootstrap
```
T23 was supposed to have fixed. Two structural races remained in src/bootstrap.py's _trigger_throwaway_search_with_retries: (1) all 3 attempts drove the SAME page/DOM state, so a failed attempt could leave the page in a "search already submitted" state the next attempt's locators never matched; (2) success was decided by one fixed wait_for_timeout(20_000) then a single check, so a token arriving a few seconds late under proxy latency read as a hard failure.
Two stronger fixes were tried first and ruled out with live evidence (not assumed): calling fetch() directly from the page's own JS context (bypassing the UI) returned HTTP 421 "system busy" — the anti-bot token is computed inline by the click/submit handler, not injected by a global fetch/XHR patch a raw fetch() would also trigger. Navigating directly to the exact URL the SPA's own router writes to history after a real search never re-fires /api/v1/search on a fresh load — the request is tied to a live user-gesture event, not to page-load/route state. Both rule out a navigation-only or credential-harvesting fix.
The fix: _mint_search_token now gives every attempt a fresh navigation (no DOM state survives a failed attempt into the next one), and a new _wait_for_search_token decides success by polling the captured token in 500ms ticks up to a 25s bound, returning the instant it is observed instead of sleeping a fixed window regardless of when the token actually arrives. See src/bootstrap.py's module docstring (T24) for the full detail.
Verified locally: full hermetic suite green (89 tests, including 2 new T24 regression tests — fresh navigation per attempt, and a token that only arrives after several poll ticks), ruff/pyright clean, and 3/3 real local Camoufox smoke runs against the live target passed.
Cloud-measured, build 0.2.3, shipped RESIDENTIAL/4096MB default, no overrides, 8 spaced runs in ~10 minutes: 7/8 SUCCEEDED (87.5%), up from 3/4 (75%) on build 0.2.2 (the pre-T24 code). Run IDs and full analysis in docs/specs/tiktok-ad-library-scraper/notes.md's T24 entry. Not fully deterministic: one run (m5qsrRwsjdutfQRjQ) still FAILED with the identical error after exhausting all 3 fresh-navigation attempts, and — unlike every prior failure this Actor has logged — every UI interaction step (cookie dismiss, region select, click, type, submit) completed with zero per-step warnings, meaning the click path itself worked mechanically every time; the token simply never appeared. That points at target-side anti-bot session variance (a browser-fingerprint/IP combination the risk engine declines to trust for that run), not a client-side timing race — see notes.md for the full reasoning. Still isPublic: false per explicit instruction; this fix measurably reduces but does not eliminate the failure mode, so it stays shelved pending a human call on whether 87.5% is acceptable.

0.2 — 2026-09-13 (unpublished — fix on branch, not yet pushed)

Bound-and-retry the search-trigger click (T23): cloud QA on the shipped RESIDENTIAL default FAILED with "No /api/v1/search request observed during bootstrap", one line below "Throwaway search trigger failed: Locator.click: Timeout 5000ms exceeded". The entire token mint depended on one 5-second locator click succeeding, with no retry and no alternative path — a single slow render sank the whole run. A prior session initially misdiagnosed this as a proxy-tier effect (datacenter FAIL, residential PASS) before a second residential run on the same tier also failed, ruling that out. src/bootstrap.py now retries the search trigger up to SEARCH_TRIGGER_MAX_ATTEMPTS=3 times with a longer per-attempt timeout (SEARCH_TRIGGER_TIMEOUT_MS=10s, up from 5s), and adds an independent submit path — pressing Enter in the search field — if the Search button click itself fails. Still raises BootstrapError (fail loud) once every attempt is exhausted; bounding the retry does not turn a real block into a silent empty success. Proxy tier is unchanged (still RESIDENTIAL, the existing shipped default) — this fix targets the actual root cause instead of the tier. Verified locally: full hermetic suite green (89 tests, including 4 new T23 regression tests covering the retry/fallback/fail-loud paths), ruff/pyright clean, and the live -m smoke Camoufox tests pass twice against the real target. Not yet pushed to Apify — see docs/specs/tiktok-ad-library-scraper/notes.md for why a cloud QA run wasn't fired in this pass.

0.1 (same-day correction) — 2026-09-12

Critical transport correction, found during pipeline-manager verification, not by the original build: plain curl-cffi alone cannot reach POST /api/v1/search or GET /api/v1/items/<id>/details — both require a browser-minted x-ccl-str anti-bot header. The 0.1.0 build below shipped believing otherwise (its own fixtures were built from recon prose, not a fresh capture, after live probing during that build session got a misleading uniform 421). Direct isolation proved it's not IP-level throttling (a fresh Camoufox call from the same IP in the same minute got 200) and that the token is reusable, not single-request-bound. Fix: src/bootstrap.py (new) does one Camoufox visit per run to mint the /search token (survives 30s+, reused for the whole run's search + pagination traffic via
```
curl-cffi impersonate="firefox133"
```
), plus a lazy, per-page /details token (much shorter TTL, ~single-digit seconds) minted right before that page's enrichment loop rather than once at boot. client.py gained TokenExpiredError (HTTP 421) as a distinct retry path from REQ-7's 429/503 backoff — one re-mint-and-retry, then fail that query loud (REQ-11). .actor/Dockerfile now downloads the Camoufox browser (camoufox fetch, above COPY src); pyproject.toml adds camoufox[geoip]. See research/RECON-tiktok-ad-library-2026-09-12.md's "CORRECTION" section and docs/specs/tiktok-ad-library-scraper/notes.md for the full live-target isolation.
fetchAdDetails now defaults to false (was true), after a live measurement: even with the lazy per-page mint fix above, a full maxResultsPerQuery=25 × 2-query enrichment run needed ~24 token re-mints for 50 rows (~1 every 2 rows, each costing a real Camoufox relaunch) — too slow/costly to be the default. Search + pagination + all list-level fields (advertiser, caption, dates, estimated audience, creative URLs) are unaffected and fast (no re-mints at all in a clean maxResultsPerQuery=25/fetchAdDetails=false run, ~40s wall-clock for 50 rows across 2 queries). Detail enrichment (external_url/call_to_action/advertising_objective) remains available as an explicit opt-in, documented in the README with a latency caveat.
This Actor now genuinely drives Camoufox, so the fleet's structural anti-bot-class publish gate (scripts/publish_actors.py's _is_antibot_class) will correctly classify it as anti-bot class — two green cloud QA runs ≥1h apart are required before publish, not one.

0.1.0 — 2026-09-12

Real crawler implemented: src/client.py (curl-cffi transport, exponential backoff on {429, 503} + network errors per REQ-7, fetch_support_regions, search_page, fetch_ad_details), src/parser.py (pure build_search_body/build_time_window/ epoch_ms_to_iso/map_row/merge_ad_details), src/main.py (per-query cursor-pagination loop, REQ-2 live region gate, REQ-6 zero-rows-is-success handling, REQ-10 per-query fault isolation, REQ-5 optional ad-detail enrichment, PPE charging, proxy resolution).
src/models.py's ResultRow filled in with the full ad-row shape (ad_id, advertiser_name, video_url, estimated_audience, external_url, etc.) per design.md's Output Schema.
.actor/pay_per_event.json added (actor-start $0.20 flat, ad-result $0.003/row — ~$3.20/1,000 ads). .actor/dataset_schema.json filled in with the real field set + nullable typing + an overview view. actor.json/pyproject.toml bumped to 0.1.
promo.json + scaffold.json added; README rewritten with the real Store-listing copy (10 canonical H2 sections, price banner, input/ output tables, EU-only-coverage limitation stated plainly).
Live-verified correction vs. design.md: GET /api/v1/support-regions returns {"regions": [{"code": "AT", "name": "Austria"}, ...], "code": 0}, not the {"data": [<code strings>]} shape design.md assumed. client.fetch_support_regions extracts code from each {code, name} object; the flat list[str] of codes it returns to callers is unchanged, so the correction stayed local to that one function. See tests/fixtures/support_regions_response.json — a fresh live capture taken during this build (2026-09-12), 33 region codes (matches spec.md's Assumptions note that the recon's own "34 regions" prose and 33-code enumeration already disagreed).
tests/fixtures/search_response_page1.json / search_response_page2.json / item_details_response.json are built from research/RECON-tiktok-ad-library-2026-09-12.md's captured row shape and example values (not a fresh live capture) — repeated /search and /items/.../details probes during this build session returned a consistent 421 "system busy" regardless of region/body variation, including through an Apify residential proxy pinned to country-DE, most consistent with a soft rate-limit triggered by the probing itself rather than a genuine wire-contract change (support-regions, a bare GET, kept returning 200 throughout). Flagged for actor-qa-engineer to confirm the /search//items/.../details wire shapes with a single, paced cloud run rather than repeated manual probing.
58 tests passing (test_models.py, test_parser.py, test_client.py, test_main.py, test_charge_no_idempotency_key.py), ruff clean, pyright clean (uv run pyright).

0.0.1 — 2026-09-12

Scaffolded: .actor/ (actor.json version 0.0, categories: ["MARKETING", "LEAD_GENERATION"], seoTitle / seoDescription set, input_schema.json matches design.md's full ActorInput shape — queries, region, dateFrom/dateTo, maxResultsPerQuery, fetchAdDetails, proxyConfiguration — dataset_schema.json / output_schema.json placeholder stubs, Dockerfile with CMD ["python", "-m", "src"]), src/main.py wiring (reads input, pushes one clearly-marked placeholder record via {"placeholder": true, ...}, exits clean), src/__init__.py / src/__main__.py (bare asyncio.run(main()), no guard needed under python -m src), src/models.py with a full ActorInput (matching design.md's date-window/query-length validators) and a placeholder ResultRow, test scaffold (tests/test_main.py), QA fixture (tests/fixtures/input.qa.json, deliberately >1 page per query per design.md's Test Strategy), README skeleton.
Proxy default is plain {"useApifyProxy": true} with no apifyProxyGroups key, per REQ-9 — no RESIDENTIAL literal appears anywhere in this Actor's tree; recon showed zero blocks.
.actor/icon.svg deferred to actor-icon-designer (TikTok brand mark inside the canonical Devil Scrapes container).
Real crawler logic (src/client.py, src/parser.py, the real src/main.py cursor-pagination loop, src/models.py's ResultRow, .actor/pay_per_event.json, promo.json) is not implemented yet — see docs/specs/tiktok-ad-library-scraper/tasks.md.

TikTok Ad Library Scraper — DSA Commercial Content Spy

dltik/tiktok-ad-library

Scrape TikTok's official DSA-mandated public Ad Library (library.tiktok.com). Search by keyword or browse all ads per country. Get advertiser, video URL, cover, image URLs, first/last shown dates, estimated audience, spend and impressions. Headless bootstrap + HTTP pagination.

Walid

Tiktok Ad Library Scraper

ivanvs/tiktok-ad-library-scraper

Extract details about ads from TikTok Ad Library. Scrape ad details like when it was run, ad targeting, advertiser and content of ad. Download ad data in JSON, XML, Excel format.

Gen First

256

TikTok Ad Library Scraper — Ads, Targeting & Spend

rastriq/tiktok-ad-library-scraper

Extract ad creatives, targeting data, and spend estimates from TikTok Ad Library. Search ads by keyword, discover advertisers, and track commercial content across 33 EU/EEA regions.

Rastriq — Structured data from the world

5.0

(1)

TikTok Ad Library Scraper 🔥 $0.5/1K

azzouzana/tiktok-ads-library

From 💰 $0.5/1K - Scrape TikTok Ad Library and Commercial Content from library.tiktok.com. Paste a URL or use search filters. Export JSON, CSV or Excel with paid ads, branded creator posts, creatives, reach, audience demographics and advertiser data.

Azzouzana

TikTok Ad Library & Creative Scraper - Spy on Competitor Ads

whoareyouanas/tiktok-ad-scraper

Scrape TikTok Ad Library + Creative Center at scale - competitor ads, video URLs, hooks, days-running, EU/EEA regions - into clean CSV/JSON. Track ads before they vanish. No $99/mo PipiAds subscription needed.

Anas Nadeem

TikTok Ad Library Scraper

jmlp/tiktok-ad-library-scraper

Scrape every ad an advertiser runs on TikTok from the official Commercial Content Library. Extract ad IDs, advertiser names, first & last shown dates, unique reach and direct downloadable video and image URLs. Search by advertiser or keyword across 32 countries. No login or API key.

Mary Lou

5.0

(1)

TikTok Ad Library Scraper — Ads, Creatives & Advertisers

jaybird/tiktok-ad-library-scraper

Scrape TikTok's Commercial Content Library into clean JSON. Search ads by advertiser or keyword and export creatives, run dates, audience bands, and EU targeting. $2.50 per 1,000 ads — no TikTok API approval needed.

Jaybird Technologies

TikTok Ad Library Scraper — Competitor Ads & Creatives

seemuapps/tiktok-ad-library-scraper

Scrape every TikTok ad an advertiser is running — video/image creatives, ad copy, run dates and estimated audience — straight from the public ad library.

Andrew

TikTok Ad Library Scraper — Resume & $0-on-Block

domestic_buffalograss/tiktok-ad-library-reliable

Get TikTok ads from the EU Commercial Content Library (DSA archive, searchable by advertiser) or Creative Center Top Ads (global high-performers with CTR/like metrics). Resumable; never charges for blocked or rate-limited runs.

Sumitsubo

TikTok Ad Library Scraper - Ads, Creatives & Audience Targeting

sourabhbgp/tiktok-ads-scraper

Search TikTok's ad library by advertiser or browse a whole country. Get ad creatives, run dates, advertiser details and the full audience breakdown: impressions by age, gender and country. Covers the EU, EEA, UK, Switzerland and Turkey.

Sourabh Kumar

TikTok Ad Library Spy & Creative Center Scraper

beyondops/tiktok-ad-library-scraper

Spy on competitor TikTok ads. Extract top-performing ad creatives, video URLs, CTR rankings, brand names, and budget data from TikTok Creative Center. Filter by country, industry, objective, and ad format. Export to JSON/CSV/Excel. No TikTok login required. Perfect for ad research & creative briefs.