> ## Documentation Index
> Fetch the complete documentation index at: https://docs.fetchin.io/llms.txt
> Use this file to discover all available pages before exploring further.
# Apify Compatibility
> Drop-in replacement for Apify actors — keep your apify-client code, just change the base URL
## Overview
Fetchin exposes an **Apify-compatible endpoint**. If you already run B2B data
actors through Apify, you can keep your existing code and the official Apify
client libraries — you only change the **base URL** to Fetchin and use your
Fetchin API key as the token.
Everything runs **asynchronously**, exactly like Apify: you start an actor run,
we queue it, and you poll for the result and read the dataset. Batches are
buffered and drained at your plan's RPS.
`https://api.fetchin.io/v1/apify`
Point any Apify client at that base URL and pass your Fetchin API key as the
token. That's the whole change.
## Supported actors
The following Apify actors are supported today. Reference an actor by its raw
**actor ID** or by the `username/actor-name` form your existing integration
already uses — both resolve.
| Apify actor | Actor ID | What it returns |
| ---------------------------------------------------------------------------------------------------- | ------------------- | --------------------------------------------------------------------------------------------------------------- |
| [`supreme_coder/linkedin-profile-scraper`](https://apify.com/supreme_coder/linkedin-profile-scraper) | `yZnhB5JewWf9xSmoM` | A full professional profile (one item per profile). Input `scrapeCompany: true` adds the current-company block. |
| [`supreme_coder/linkedin-post`](https://apify.com/supreme_coder/linkedin-post) | `Wpp1BZ6yGWjySadk3` | A profile's posts. Input `deepScrape: true` adds reactions + comments per post. |
| [`apimaestro/linkedin-profile-comments`](https://apify.com/apimaestro/linkedin-profile-comments) | `7TNcROe1C2CQDO3wl` | Comments made by a profile (paginated). |
| [`apimaestro/linkedin-profile-reactions`](https://apify.com/apimaestro/linkedin-profile-reactions) | `FNhKFjeL8hWQtMeZI` | Reactions made by a profile (paginated). |
We map the output fields to match each actor as closely as possible, so your
downstream code keeps working unchanged.
**Need another actor?** If you rely on an actor that isn't in this list,
reach out via the chat on [fetchin.io](https://fetchin.io) or email us — we
add actors on request.
## Usage
### JavaScript / Node (`apify-client`)
```js theme={null}
import { ApifyClient } from 'apify-client';
const client = new ApifyClient({
token: process.env.FETCHIN_API_KEY,
baseUrl: 'https://api.fetchin.io/v1/apify', // the only change
});
// Start a run and wait for it to finish
const run = await client
.actor('yZnhB5JewWf9xSmoM')
.call({ urls: [{ url: 'https://www.linkedin.com/in/williamhgates/' }], scrapeCompany: true });
// Read the dataset
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
```
### Python (`apify-client`)
```python theme={null}
from apify_client import ApifyClient
import os
client = ApifyClient(
token=os.environ["FETCHIN_API_KEY"],
api_url="https://api.fetchin.io/v1/apify", # the only change
)
run = client.actor("yZnhB5JewWf9xSmoM").call(
run_input={"urls": [{"url": "https://www.linkedin.com/in/williamhgates/"}], "scrapeCompany": True}
)
items = client.dataset(run["defaultDatasetId"]).list_items().items
print(items)
```
### HTTP (any language)
```bash theme={null}
# 1. Start a run
curl -s -X POST \
'https://api.fetchin.io/v1/apify/v2/acts/yZnhB5JewWf9xSmoM/runs' \
-H 'Authorization: Bearer '"$FETCHIN_API_KEY" \
-H 'Content-Type: application/json' \
-d '{"urls":[{"url":"https://www.linkedin.com/in/williamhgates/"}],"scrapeCompany":true}'
# -> { "data": { "id": "", "defaultDatasetId": "", "status": "READY", ... } }
# 2. Poll the run until status is SUCCEEDED (waitForFinish long-polls up to 60s)
curl -s \
'https://api.fetchin.io/v1/apify/v2/actor-runs/?waitForFinish=60' \
-H 'Authorization: Bearer '"$FETCHIN_API_KEY"
# 3. Read the dataset (a JSON array of items)
curl -s \
'https://api.fetchin.io/v1/apify/v2/datasets//items' \
-H 'Authorization: Bearer '"$FETCHIN_API_KEY"
```
## Pagination (comments & reactions)
The paginated actors return **one page per run**. To page, re-run the actor
with the `pagination_token` from the previous page's items and an incremented
`page_number` — exactly as with Apify:
```js theme={null}
let pageNumber = 1;
let token = null;
do {
const run = await client
.actor('FNhKFjeL8hWQtMeZI')
.call({ username: 'williamhgates', page_number: pageNumber, pagination_token: token });
const { items } = await client.dataset(run.defaultDatasetId).listItems();
// ... process items ...
token = items[0]?.pagination_token ?? null;
pageNumber += 1;
} while (token);
```
A profile with no reactions returns a single sentinel item
`{ "message": "No reaction found for this profile" }`, matching Apify.
## Billing, timeouts & retention
* **Billing**: 1 dataset item = 1 Fetchin credit (the same per-result accounting
as Apify). A batch of 25 profiles = 25 credits. **Exception:** a post fetched
with `deepScrape: true` costs **3 credits per post** — the post itself plus the
two extra requests for its comments and its reactions. A shallow post
(`deepScrape: false` / omitted) costs 1 credit.
* **Timeout**: the `timeout` input (seconds) bounds a run. If it elapses, the run
ends `TIMED-OUT` and the items already produced remain in the dataset.
* **Retention**: run records and datasets are retained for 24 hours. Fetch your
results within that window.
* **Rate**: your account RPS controls how fast we drain your queued items (not
how many runs you can create). Creating runs far faster than your RPS returns
`429` with `Retry-After`; the Apify client backs off automatically.
## Differences vs Apify
We validate every actor against real Apify output field-by-field. The reactions,
comments and post actors reach **zero field errors** on matched items; the
differences below are values that either **cannot be reproduced byte-for-byte**
(live counts, signed URLs, per-request tokens) or that we approximate where the
source data isn't exposed. Everything here is stable and documented so you can
decide whether it affects your integration. If a specific field blocks you,
contact us and we'll prioritise it.
### Applies to all actors
* **Live engagement counts** (reactions/comments/reposts totals) drift second to
second — they reflect the source at fetch time, so two fetches rarely match to
the digit. This is identical to Apify.
* **Relative timestamps** (`"15h"`, `"2w"`) are wall-clock-relative to the moment
of the request. Absolute timestamps (`timestamp`, `postedAtISO`, `formatted`)
are exact.
* **Signed media URLs** carry an expiring signature (`?e=…&v=…&t=…`). The host +
path are stable; the signature differs every request.
* **Pagination tokens** are opaque and positional — use them, don't compare them.
### `supreme_coder/linkedin-profile-scraper` (profile)
| Field | Difference |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `currentCompany` | With `scrapeCompany: true` we return a compact block (`name`, `universalName`, `url`). Apify's full company sub-tree (employee counts, industries, HQ, affiliated pages…) is not fully reproduced yet. |
| `pictureUrl`, `coverImageUrl`, logos | Dimension-keyed objects (`{"800x800": "…"}`). We currently populate the largest rendition keyed by its real size; other size keys may be absent. |
| `courses`, `honors`, `volunteerExperiences`, `projects`, `publications`, `patents`, `testScores`, `organizations`, `certifications`, `languages`, `volunteerCauses` | Returned as `[]` (extraction of these sections is in progress). |
| `mutualConnections` | Always `[]` — depends on the viewer's network and isn't available to a service account. |
| `fullName` | Derived as `firstName + " " + lastName`. |
### `supreme_coder/linkedin-post` (post)
| Field | Difference |
| --------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `author.id`, `authorUrn` | The numeric member id / member-scheme urn isn't present in the source feed. We return the public handle (`author.publicId`, `authorProfileId`) and the profile id (`author.profileId`). |
| `author.trackingId`, `author.backgroundImage` | Not reproduced (per-request token / not in the feed). |
| `resharedPost` | Reshared posts are **not nested**. The underlying feed returns a profile's own posts; pure reshares are filtered. |
| `url` | Canonical post permalink. The trailing `?rcm=…` token is per-viewer and will differ. |
| `linkedinVideo.videoPlayMetadata` | Core fields (streams, duration, thumbnail, aspect ratio) are reproduced; `transcripts`, `adaptiveStreams` and `trackingId` are omitted. |
| `attributes`, comment `entities` | Inline @mention / hashtag annotation ranges are returned as `[]`. |
| **Deep `comments[]` / `reactions[]`** | These are **relevance-ranked live lists** — the exact top-N set differs between any two fetches (true on Apify too). Per engager: `firstName`/`lastName` are split best-effort from the display name (Apify uses the source's structured name fields); `publicId` is the profile id (the engager lockup doesn't expose the handle); `id`, `trackingId`, `backgroundImage`, `distance`, `originalLanguage` are omitted. Names, occupation, picture and `profileId` match. |
### `apimaestro/linkedin-profile-comments` (comments)
* **Full field parity** on matched items. Only the volatile values above (live
comment/post reaction counts, relative time) differ.
* Items do **not** carry a root `pagination_token` — this actor pages by
`page_number` (this matches Apify's actor).
### `apimaestro/linkedin-profile-reactions` (reactions)
| Field | Difference |
| ---------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `action` | We return the **reaction type enum** (`LIKE`, `EMPATHY`, `APPRECIATION`, `INTEREST`, `PRAISE`, `ENTERTAINMENT`). Apify emits a header **sentence** (e.g. `"Bill Gates likes this"`). Tell us if you need the sentence form. |
| `post_url` | The canonical post permalink — same post, may be a different valid URL form than Apify's. |
| `post_stats` per-type counts | Reproduced (`like`/`appreciation`/`empathy`/`interest`/`praise`), subject to the live-count drift noted above. |