pylyntr

A Python library for the lyntr.gizmowizard.tech API.

pylyntr is now on PyPI! This means you can do a simple uv add pylyntr or pip install pylyntr.

Installation

With uv (recommended)

uv init . # if pyproject.toml doesn't already exist
uv add pylyntr

With pip

python3 -m venv .venv # if venv doesn't already exist
source .venv/bin/activate
pip install pylyntr

Requires Python 3.11+.

Quick Start

from pylyntr import LyntrClient

client = LyntrClient(
    client_id="CLIENT_ID",
    client_secret="CLIENT_SECRET",
)

# Create a post
post = client.create_post("Hello from pylyntr!")
print(post.content)

# Get your profile
me = client.get_user()
print(f"@{me.handle} - {me.username}")

# Fetch the feed
for post in client.posts():
    print(f"@{post.user.username}: {post.content}")

Get a client ID and secret from the Developer API page.

API Reference

LyntrClient

LyntrClient(
    client_id: str,
    client_secret: str,
    api_url: str = "https://lyntr.gizmowizard.tech/api/v1",
    max_retries: int = 3,
    retry_delay: float = 1.0,
)

Constructs the client and validates credentials via test().

FeedType

An enum used with client.posts():

• FeedType.ForYou - algorithm
• FeedType.New - latest posts
• FeedType.Following - posts from followed users

Post

A dataclass with fields: id, content, created_at, reposted, has_image, views, likes, reposts, comments, liked_by_user, reposted_by_user, liked_by_followed, user, referenced_lynts, edited_at, gif_url, gif_preview_url, poll.

User

A dataclass with fields: id, handle, bio, created_at, username, iq, verified, lynt_coins, admin, contributor, login_streak, followers, follows_user, name_colour, following.

Contributing

The easiest way you can contribute to pylyntr is by finding bugs and reporting them in Codeberg issues. HTTPErrors from requests are considered bugs, as we're trying to minimise them as much as possible and raise more descriptive exception types.

Feature suggestions and pull requests are also welcome. PRs must target the next branch to be accepted.

AI

An LLM (DeepSeek V4 Pro) was used to help write this README and a portion of LyntrClient.api_request(), and to review the code.