Thanks, I’ll revamp my code when I start testing it later. I think eventually I’ll put together a python library for interacting with Lemmy, or at least give enough of an example that someone else can get a good start.

I just use ChatGPT with JetBrains tools, it works pretty well. Make sure you go for the paid model, though. It really is better than the free one, and I often use it to lay groundwork that I flesh out in the free model.

Here’s a kind of guess on how to create a post using python’s requests library:

import requests
import json

# Define the URL for the API endpoint
url = "https://lemmy.ml/api/v1/post"

# Define the headers for the request
headers = {'Content-Type': 'application/json'}

# Define the data for the new post
data = {
 "name": "Your Post Title",
 "community_id": 123,  # Replace with your community ID
 "url": "https://your-url.com",  # Optional
 "body": "Your post content",  # Optional
 "nsfw": False,  # Optional
 "language_id": 1,  # Optional, replace with your language ID
 "auth": "your_auth_token_here"
}

# Send the POST request
response = requests.post(url, headers=headers, data=json.dumps(data))

# Print the response
print(response.json())

Does this look right? I understand that I’ll have to authenticate to the server to do this, but I’m really not sure how to do that.

That is awesome! how soon until Beehaw is federated with them?

How about extending the software so that communities replicate between sets of servers over time? That way, things are more robust even if one server goes down.

Has anyone considered creating a bridging API interface for lemmy? Something that can translate between the lemmy and reddit API to make this easier?

There was one time a good while back where I used window functions to perform edge detection in a dataset. I’ll see if I can dig up that query later.

Those work, but require a lot of careful structuring to get right, and can be a pain to debug. With a CTE, you can just call on the intermediate steps to trace down problems.