semvec/pypi-packages huggingface dataset:
ircpy 1.1.5
IRC library for Python3
Requires Python: >=3.8

# IRC.PY

An IRC library for python.
Example code can be found in "example-bot.py".

### Keep in mind that when using the following functions to keep the correct variable order:
async def message_received(message, user, channel, **kwargs) for message_received;
async def commandname(arguments, user, channel, msg, **kwargs) for commands;
async def ready(nickname, channel) for ready.

When running your bot, keep in mind that Bot.connect() is non-asynchronous while Bot._connect() is.
logis 0.3.1
Git-based experiment tracking with semantic metadata.
Requires Python: >=3.10

<div align="center">
  
  ![logo](https://github.com/user-attachments/assets/70bdda50-51ca-453e-9098-69d6668924fd)

  [Discord](https://discord.gg/kTkF2e69fH) • [Website](https://flywhl.dev) • [Installation](#installation)
  <br/>
  <br/>
</div>

## Features

`logis` turns your commit history into a searchable scientific log.

Every time you run an experiment, your code will be auto-committed with metadata in the commit message.


## Installation

* `uv add logis`

## Usage

* Put the `@commit` decorator on your experiment function.
* `logis` will store hyperparameters and metrics as metadata in the commit message.
* Query your scientific log, e.g. `logis query metrics.accuracy < 0.8`.

```python
from logis import commit, Run

@commit
def my_experiment(run: Run) -> Metrics:

    # ... experiment stuff

    run.set_hyperparameters({
        "lr": 0.001,
        "epochs": 100,
    })

    # ... more experiment stuff

    run.set_metrics({
        "accuracy": 0.9,
    })

if __name__ == "__main__":
    my_experiment()

# --- Or use the implicit API

@commit(implicit=True)
def other_experiment(hypers: Hypers) -> Metrics:

    # ... experiment stuff

    metrics = Metrics(accuracy=0.9)
    return metrics

if __name__ == "__main__":
    other_experiment(Hypers(...))
```

Then run your experiment:

```
$ python experiment.py

Generating commit with message:

    exp: run my_experiment at 2025-02-10 18:39:18.759230

    ---

    {
      "experiment": "my_experiment",
      "hyperparameters": {
        "lr": 0.001,
        "epochs": 100,
      },
      "metrics": {
        "accuracy": 0.9,
      },
      "uuid": "94871de1-4d6c-4e70-9c9d-60ec11df1159",
      "artifacts": null,
      "annotations": null,
      "timestamp": "2025-02-10T18:39:18.759230"
    }
```

Finally, query for relevant commits:

```

$ logis query metrics.accuracy > 0.8

Found 1 commit(s):

    af6cd7

```


## Development

* `git clone https://github.com/flywhl/logis.git`
* `cd logis`
* `uv sync`
* `just test`

## Flywheel

Science needs better software tools. [Flywheel](https://flywhl.dev/) is an open source collective building simple tools to preserve scientific momentum, inspired by devtools and devops culture. Join our Discord [here](discord.gg/fd37MFZ7RS).
langgraph-checkpoint-surrealdb 0.2.1
A SurrealDB Saver for Langgraph Checkpoints
Requires Python: >=3.10

# Surreal Saver

A SurrealDB Checkpointer for Langgraph with both synchronous and asynchronous support.

## Installation

```sh
pip install langgraph-checkpoint-surrealdb
```

## Usage

### Synchronous Usage

```python
from langgraph_checkpoint_surrealdb import SurrealSaver
from langgraph.graph import StateGraph, START, END
from pydantic import BaseModel, Field
from typing import Annotated
import operator

# Initialize SurrealDB connection
memory = SurrealSaver(
    url="ws://localhost:8000/rpc",
    user="root",
    password="root",
    namespace="ns",
    database="db"
)

class ThreadState(BaseModel):
    messages: Annotated[list, operator.add] = Field(default_factory=list)

def get_model_answer(state: ThreadState, config: RunnableConfig) -> dict:
    if state.messages == [] or state.messages == [""]:
        return {"messages": []}

    model = ChatOpenAI(model="gpt-4")
    sys_prompt = "You are a helpful assistant"
    ai_message = model.invoke([sys_prompt] + state.messages)
    return {"messages": [ai_message]}

agent_state = StateGraph(ThreadState)
agent_state.add_node("get_model_answer", get_model_answer)
agent_state.add_edge(START, "get_model_answer")
agent_state.add_edge("get_model_answer", END)
graph = agent_state.compile(checkpointer=memory)

# Use synchronously
result = graph.invoke(
    input={"messages": [HumanMessage(content="Hello")]},
    config={"configurable": {"thread_id": "123"}}
)
```

### Asynchronous Usage

```python
# Same setup as above, but use async methods

# Use asynchronously
result = await graph.ainvoke(
    input={"messages": [HumanMessage(content="Hello")]},
    config={"configurable": {"thread_id": "123"}}
)

# Async methods available:
# - aget_tuple: Get a checkpoint tuple asynchronously
# - alist: List checkpoints asynchronously
# - aput: Save a checkpoint asynchronously
# - aput_writes: Save writes asynchronously
```

The SurrealSaver provides both synchronous and asynchronous methods for all operations, allowing you to choose the appropriate approach based on your application's needs.
wordimg 1.0.2
A library to generate text images with custom backgrounds.
Requires Python: >=3.6


---

# WordImg

WordImg is a Python library that generates images with custom text over a user-provided background. The background is automatically resized to 2560x1440, and text is centered for a professional look.

## Features

✅ Resize background to 2560x1440
✅ Custom text positioning
✅ Built-in font (no external dependency)
✅ Auto-save images to saved_images/
✅ Simple and lightweight

## Installation

Install WordImg using:
```bash
pip install WordImg
```

## Usage

from wordimg import WordImg

```bash
wordimg = WordImg()
image_path = wordimg.make_image("background.jpg", "Delta", "@wtfdelta")

print(f"Image saved at: {image_path}")
```
## Example Output

![Example Output](https://files.catbox.moe/yk3vw9.jpg)

If you provide "background.jpg" and "Hello World", the generated image will have:

Resized background (2560x1440)

Centered text: "Hello World"

Username in the top-left corner


## Project Links

Website: deltaop.tech

GitHub: github.com/geektyper

Telegram: wtf_daddie.t.me



---
kazuha 0.1.1
A Python package with a banner and social media details
Requires Python: >=3.6

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╚═╝  ╚═╝╚═╝  ╚═╝╚══════╝ ╚═════╝ ╚═╝  ╚═╝╚═╝  ╚═╝

GitHub: [https://github.com/Kazuha787](https://github.com/Kazuha787)  
Telegram: [https://t.me/Offical_Im_kazuha](https://t.me/Offical_Im_kazuha)
WordImg 1.0.1
A library to generate text images with custom backgrounds.
Requires Python: >=3.6


---

# WordImg

WordImg is a Python library that generates images with custom text over a user-provided background. The background is automatically resized to 2560x1440, and text is centered for a professional look.

## Features

✅ Resize background to 2560x1440
✅ Custom text positioning
✅ Built-in font (no external dependency)
✅ Auto-save images to saved_images/
✅ Simple and lightweight

## Installation

Install WordImg using:
```bash
pip install WordImg
```

## Usage

from wordimg import WordImg

```bash
wordimg = WordImg()
image_path = wordimg.make_image("background.jpg", "Delta", "@wtfdelta")

print(f"Image saved at: {image_path}")
```
## Example Output

![Example Output](https://files.catbox.moe/yk3vw9.jpg)

If you provide "background.jpg" and "Hello World", the generated image will have:

Resized background (2560x1440)

Centered text: "Hello World"

Username in the top-left corner


## Project Links

Website: deltaop.tech

GitHub: github.com/geektyper

Telegram: wtf_daddie.t.me



---
streamlit-cards 0.1.0
Card components for streamlit app.
Requires Python: >=3.6

## Streamlit Navbar Component
### Import

```python 
from streamlit_cards.streamlit_card_component import card
```
### Implementation
```python
clicked =  card(3, [
                    {"title":"1000", "text":"hello", "style":{"color":"blue"}},
                    {"title":"New","text":"2000", "style":{"color":"red"}},
                    {"title": "New", "text": "2000", "style": {"background": base64_string}}
                ]
            )
```
### Explaination
- 3 is the number of columns you want in a row.
- you can add multiple cards at a time
- You can pass following params in the style section of each card.
```python
background: "linear-gradient(135deg, #ff9a9e, #fad0c4)",
width: "80%",
height: "200px",
blur: 10,
elevation: 15,
border_radius: "10px",
color: "#ffffff",
font_size: "20px",
border: "none",
boxShadow:"0px 10px 20px rgba(0, 0, 0, 0.3)",
backdropFilter: "blur(10px)",
display: "flex",
flexDirection: "column",
justifyContent: "center",
alignItems: "center",
padding: "20px",
textAlign: "center",
cursor: "pointer",
transition: "transform 0.2s ease-in-out"
```