In our ongoing efforts to enhance the reliability and sustainability of our services, we have implemented a significant update regarding the scraping of missing LinkedIn profiles. Effective immediately, credits will be consumed when attempting to scrape a missing LinkedIn profile (resulting in a 404 status code). Allow us to explain the rationale behind this decision.

At Datamagnet, our API People Profile endpoint is designed to crawl public LinkedIn profiles. However, not all LinkedIn profiles, even if valid, are publicly accessible. In cases where a profile is not available to the public, our LinkedIn People Profile Endpoint returns a 404 status code.

Today, we are introducing an update to our service that charges credits when an API request is made to scrape a public LinkedIn profile that is missing from the public domain. This adjustment is crucial because the resources required to scrape both valid and invalid profiles remain consistent and equally expended.

Regrettably, we have encountered instances where our services were exploited by attackers using trial API keys to spam numerous requests to random invalid profile URLs. This malicious activity resulted in a significant strain on Datamagnet's API service, ultimately leading to a denial of service.

We sincerely appreciate your understanding and cooperation as we implement these changes to ensure the sustainability and reliability of our services. These measures are essential for supporting our users who rely on Datamagnet's services to build and grow their businesses. Thank you for your continued support as we strive to provide you with the best possible experience.

In our ongoing efforts to enhance the reliability and sustainability of our services, we have implemented a significant update regarding the scraping of missing LinkedIn profiles. Effective immediately, credits will be consumed when attempting to scrape a missing LinkedIn profile (resulting in a 404 status code). Allow us to explain the rationale behind this decision.

At Datamagnet, our API People Profile endpoint is designed to crawl public LinkedIn profiles. However, not all LinkedIn profiles, even if valid, are publicly accessible. In cases where a profile is not available to the public, our LinkedIn People Profile Endpoint returns a 404 status code.

Today, we are introducing an update to our service that charges credits when an API request is made to scrape a public LinkedIn profile that is missing from the public domain. This adjustment is crucial because the resources required to scrape both valid and invalid profiles remain consistent and equally expended.

Regrettably, we have encountered instances where our services were exploited by attackers using trial API keys to spam numerous requests to random invalid profile URLs. This malicious activity resulted in a significant strain on Datamagnet's API service, ultimately leading to a denial of service.

We sincerely appreciate your understanding and cooperation as we implement these changes to ensure the sustainability and reliability of our services. These measures are essential for supporting our users who rely on Datamagnet's services to build and grow their businesses. Thank you for your continued support as we strive to provide you with the best possible experience.

Image Credits: [Image by storyset on Freepik](https://www.freepik.com/free-vector/404-error-with-landscape-concept-illustration_20602785.htm#query=404&position=5&from_view=keyword&track=sph&uuid=7f8f0b2c-a19a-4db9-8438-15fda23759e4)

Important Update: Changes to Credit Consumption for Missing LinkedIn Profiles

### Introduction
Until now, Datamagnet's API focused on people and company data. Today, we're expanding into **LinkedIn post analytics** with 4 new endpoints that let you extract everything about a LinkedIn post—from the full post content to every comment, reaction, and repost.
Whether you're building a social listening dashboard, tracking content performance for clients, or analyzing engagement patterns at scale, these endpoints give you the raw data you need.
All you need is a LinkedIn post URL. We handle extracting the activity ID, calling the right upstream APIs, and returning clean, paginated, snake_case JSON.
---
### What's New
Here's a quick overview of the 4 new endpoints:
| Endpoint | What It Does | Cost ||---|---|---|| `POST /api/v1/linkedin/post` | Full post details, author, social counts | 5 credits || `POST /api/v1/linkedin/post/comments` | Paginated comments with commenter profiles | 5 credits || `POST /api/v1/linkedin/post/reactions` | Who reacted and reaction types (Like, Praise, etc.) | 5 credits || `POST /api/v1/linkedin/post/reposts` | Who reposted, with commentary and reshare info | 5 credits |
All endpoints accept a simple JSON body:
```json{"url": "https://www.linkedin.com/posts/username_slug-activity-7430615551086850048-XXXX"}```
We support every common LinkedIn post URL format—whether it's a `/posts/` share link, a `/feed/update/` link, or a ugcPost URL. The API auto-extracts the activity ID for you.
---
### 1. Post Details
**Endpoint:** `POST /api/v1/linkedin/post`
This is your starting point. Given any LinkedIn post URL, it returns the complete post data in a single call:
- **Post content** — full text, posted timestamp, and the post's URN- **Author info** — name, headline, profile picture, and profile link- **Social counts** — total likes, comments, shares, and a reaction-type breakdown (e.g., 108 Likes, 10 Praise, 4 Empathy)- **Article attachments** — title, subtitle, link, and thumbnail for shared articles- **Repost metadata** — if the post is a repost, you get the original post header and who reposted it- **Related URNs** — the `reactions_urn`, `comments_urn`, and `reposts_urn` you can use with the other endpoints
```pythonimport requests
response = requests.post("https://api.datamagnet.co/api/v1/linkedin/post", json={"url": "https://www.linkedin.com/feed/update/urn:li:activity:7219434359085252608"}, headers={"Authorization": "Bearer YOUR_API_KEY"})
data = response.json()print(data["message"]["post_text"])print(f"Likes: {data['message']['social_count']['num_likes']}")```
---
### 2. Post Comments
**Endpoint:** `POST /api/v1/linkedin/post/comments`
Retrieve every comment on a post with full commenter profiles. Supports cursor-based pagination to walk through all comments.
Each comment includes:- Comment text and permalink- Commenter name, headline, and profile picture- Whether the comment is pinned or edited- Reaction breakdown on the comment itself- Reply count and top replies
```pythonpage = 1all_comments = []
while page is not None: response = requests.post("https://api.datamagnet.co/api/v1/linkedin/post/comments", json={"url": "https://www.linkedin.com/posts/...","page": page }, headers={"Authorization": "Bearer YOUR_API_KEY"} )
data = response.json() all_comments.extend(data["message"]["comments"]) page = data.get("cursor")
print(f"Total comments: {len(all_comments)}")```
The `cursor` field returns the next page number. When it's `null`, you've reached the end.
---
### 3. Post Reactions
**Endpoint:** `POST /api/v1/linkedin/post/reactions`
See exactly who reacted to a post and what type of reaction they gave. LinkedIn supports 6 reaction types:
- 👍 **Like**- 👏 **Praise** (Celebrate)- ❤️ **Empathy** (Love)- 💡 **Interest** (Insightful)- 🙏 **Appreciation** (Support)- 😄 **Entertainment** (Funny)
Each reaction record includes the person's name, headline, profile URL, profile picture, and the specific reaction type. Paginated the same way as comments.
```pythonresponse = requests.post("https://api.datamagnet.co/api/v1/linkedin/post/reactions", json={"url": "https://www.linkedin.com/posts/...","page": 1 }, headers={"Authorization": "Bearer YOUR_API_KEY"})
data = response.json()for reaction in data["message"]["reactions"]:print(f"{reaction['title']} — {reaction['reaction_type']}")```
---
### 4. Post Reposts
**Endpoint:** `POST /api/v1/linkedin/post/reposts`
Track how content spreads across LinkedIn. This endpoint returns everyone who reposted a specific post, including:
- **Direct reposts** — the reposter's name, headline, profile picture, and any commentary they added- **Reshares** — when someone reposted a repost, you get a nested header showing the chain (e.g., "Michael Chen reposted this")- **Company reposts** — when a company page reshares, you get the company name, logo, and follower count
```pythonresponse = requests.post("https://api.datamagnet.co/api/v1/linkedin/post/reposts", json={"url": "https://www.linkedin.com/posts/...","page": 1 }, headers={"Authorization": "Bearer YOUR_API_KEY"})```---
### Design Decisions
A few things worth highlighting about how we built these:
**Snake case everywhere.** All response keys are in `snake_case`, even though LinkedIn's internal API uses camelCase. We convert everything automatically so your Python and Ruby code looks idiomatic without post-processing.
**Consistent pagination.** Every paginated endpoint uses the same pattern: pass `page` in the request body, read `cursor` from the response. When `cursor` is `null`, you're done. No offset math required.
**Any URL format.** We auto-detect and extract activity IDs from multiple LinkedIn URL formats — `/posts/` share links, `/feed/update/` links, `ugcPost` URLs, and more. Just paste whatever URL you have.


### Introduction

Until now, Datamagnet's API focused on people and company data. Today, we're expanding into **LinkedIn post analytics** with 4 new endpoints that let you extract everything about a LinkedIn post—from the full post content to every comment, reaction, and repost.

Whether you're building a social listening dashboard, tracking content performance for clients, or analyzing engagement patterns at scale, these endpoints give you the raw data you need.

All you need is a LinkedIn post URL. We handle extracting the activity ID, calling the right upstream APIs, and returning clean, paginated, snake_case JSON.

---

### What's New

Here's a quick overview of the 4 new endpoints:

| Endpoint | What It Does | Cost |
|---|---|---|
| `POST /api/v1/linkedin/post` | Full post details, author, social counts | 5 credits |
| `POST /api/v1/linkedin/post/comments` | Paginated comments with commenter profiles | 5 credits |
| `POST /api/v1/linkedin/post/reactions` | Who reacted and reaction types (Like, Praise, etc.) | 5 credits |
| `POST /api/v1/linkedin/post/reposts` | Who reposted, with commentary and reshare info | 5 credits |

All endpoints accept a simple JSON body:

```json
{
  "url": "https://www.linkedin.com/posts/username_slug-activity-7430615551086850048-XXXX"
}
```

We support every common LinkedIn post URL format—whether it's a `/posts/` share link, a `/feed/update/` link, or a ugcPost URL. The API auto-extracts the activity ID for you.

---

### 1. Post Details

**Endpoint:** `POST /api/v1/linkedin/post`

This is your starting point. Given any LinkedIn post URL, it returns the complete post data in a single call:

- **Post content** — full text, posted timestamp, and the post's URN
- **Author info** — name, headline, profile picture, and profile link
- **Social counts** — total likes, comments, shares, and a reaction-type breakdown (e.g., 108 Likes, 10 Praise, 4 Empathy)
- **Article attachments** — title, subtitle, link, and thumbnail for shared articles
- **Repost metadata** — if the post is a repost, you get the original post header and who reposted it
- **Related URNs** — the `reactions_urn`, `comments_urn`, and `reposts_urn` you can use with the other endpoints

```python
import requests

response = requests.post(
    "https://api.datamagnet.co/api/v1/linkedin/post",
    json={"url": "https://www.linkedin.com/feed/update/urn:li:activity:7219434359085252608"},
    headers={"Authorization": "Bearer YOUR_API_KEY"}
)

data = response.json()
print(data["message"]["post_text"])
print(f"Likes: {data['message']['social_count']['num_likes']}")
```

---

### 2. Post Comments

**Endpoint:** `POST /api/v1/linkedin/post/comments`

Retrieve every comment on a post with full commenter profiles. Supports cursor-based pagination to walk through all comments.

Each comment includes:
- Comment text and permalink
- Commenter name, headline, and profile picture
- Whether the comment is pinned or edited
- Reaction breakdown on the comment itself
- Reply count and top replies

```python
page = 1
all_comments = []

while page is not None:
    response = requests.post(
        "https://api.datamagnet.co/api/v1/linkedin/post/comments",
        json={
            "url": "https://www.linkedin.com/posts/...",
            "page": page
        },
        headers={"Authorization": "Bearer YOUR_API_KEY"}
    )

    data = response.json()
    all_comments.extend(data["message"]["comments"])
    page = data.get("cursor")

print(f"Total comments: {len(all_comments)}")
```

The `cursor` field returns the next page number. When it's `null`, you've reached the end.

---

### 3. Post Reactions

**Endpoint:** `POST /api/v1/linkedin/post/reactions`

See exactly who reacted to a post and what type of reaction they gave. LinkedIn supports 6 reaction types:

- 👍 **Like**
- 👏 **Praise** (Celebrate)
- ❤️ **Empathy** (Love)
- 💡 **Interest** (Insightful)
- 🙏 **Appreciation** (Support)
- 😄 **Entertainment** (Funny)

Each reaction record includes the person's name, headline, profile URL, profile picture, and the specific reaction type. Paginated the same way as comments.

```python
response = requests.post(
    "https://api.datamagnet.co/api/v1/linkedin/post/reactions",
    json={
        "url": "https://www.linkedin.com/posts/...",
        "page": 1
    },
    headers={"Authorization": "Bearer YOUR_API_KEY"}
)

data = response.json()
for reaction in data["message"]["reactions"]:
    print(f"{reaction['title']} — {reaction['reaction_type']}")
```

---

### 4. Post Reposts

**Endpoint:** `POST /api/v1/linkedin/post/reposts`

Track how content spreads across LinkedIn. This endpoint returns everyone who reposted a specific post, including:

- **Direct reposts** — the reposter's name, headline, profile picture, and any commentary they added
- **Reshares** — when someone reposted a repost, you get a nested header showing the chain (e.g., "Michael Chen reposted this")
- **Company reposts** — when a company page reshares, you get the company name, logo, and follower count

```python
response = requests.post(
    "https://api.datamagnet.co/api/v1/linkedin/post/reposts",
    json={
        "url": "https://www.linkedin.com/posts/...",
        "page": 1
    },
    headers={"Authorization": "Bearer YOUR_API_KEY"}
)
```
---

### Design Decisions

A few things worth highlighting about how we built these:

**Snake case everywhere.** All response keys are in `snake_case`, even though LinkedIn's internal API uses camelCase. We convert everything automatically so your Python and Ruby code looks idiomatic without post-processing.

**Consistent pagination.** Every paginated endpoint uses the same pattern: pass `page` in the request body, read `cursor` from the response. When `cursor` is `null`, you're done. No offset math required.

**Any URL format.** We auto-detect and extract activity IDs from multiple LinkedIn URL formats — `/posts/` share links, `/feed/update/` links, `ugcPost` URLs, and more. Just paste whatever URL you have.


Pratik Dani

Important Update: Changes to Credit Consumption for Missing LinkedIn Profiles

Introducing 4 New LinkedIn Post Endpoints: Full Post Analytics via API