semvec/pypi-packages huggingface dataset:
bsdk-python 0.1.0
A placeholder Python SDK package for BML
License: MIT
Requires Python: >=3.8
Keywords: sdk, bml, placeholder

# BML SDK

A placeholder Python SDK package for BML.

## Installation

```bash
pip install bsdk-python
```

## Usage

```python
from bml import hello_world, add

# Say hello
print(hello_world())

# Add numbers
result = add(2, 3)
print(result)  # Output: 5
```

## Development

To set up a development environment:

```bash
# Clone the repository
git clone https://github.com/yourorg/bml.git
cd bml

# Install in development mode with dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Format code
black .

# Type check
mypy bml
```

## Building and Publishing

To build the package:

```bash
python -m build
```

To publish to PyPI:

```bash
# First, install build tools
pip install build twine

# Build the package
python -m build

# Upload to PyPI (test first with testpypi)
twine upload dist/*
```

## License

MIT License - see LICENSE file for details.

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.
autoresume 0.1.3
Crash-safe ML model runner that automatically resumes unfinished models
License: MIT
Requires Python: >=3.8
Keywords: machine-learning, resume, experiment, crash, autoresume

# AutoResume

AutoResume is a crash-safe, resume-safe ML model runner.

It allows you to run many models sequentially and **automatically resumes**
from the first unfinished model if your Python session crashes.

## Example

```python
from autoresume import AutoResume

runner = AutoResume("lstm_experiment")

models = [lstm1, lstm2, lstm3]

def train(model):
    model.fit(X_train, y_train, epochs=20)
    return model.evaluate(X_test, y_test)

runner.run(models, train)
If your script crashes during model 2, AutoResume will resume at model 2.

MIT License
Copyright (c) 2025 Tej Gorde
ai-agents-wrapper 0.1.0
A lightweight and extensible agent framework for LLM-powered automation.
License: MIT
Requires Python: >=3.8

# agenticpy

A lightweight and extensible agent framework for LLM-powered automation.

## Installation
pip install agenticpy

## Usage
```python
from agenticpy import Agent

agent = Agent("TestAgent")
print(agent.run("Say Hello"))
bml-sdk 0.1.0
A placeholder Python SDK package for BML
License: MIT
Requires Python: >=3.8
Keywords: sdk, bml, placeholder

# BML SDK

A placeholder Python SDK package for BML.

## Installation

```bash
pip install bml-sdk
```

## Usage

```python
from bml import hello_world, add

# Say hello
print(hello_world())

# Add numbers
result = add(2, 3)
print(result)  # Output: 5
```

## Development

To set up a development environment:

```bash
# Clone the repository
git clone https://github.com/yourorg/bml.git
cd bml

# Install in development mode with dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Format code
black .

# Type check
mypy bml
```

## Building and Publishing

To build the package:

```bash
python -m build
```

To publish to PyPI:

```bash
# First, install build tools
pip install build twine

# Build the package
python -m build

# Upload to PyPI (test first with testpypi)
twine upload dist/*
```

## License

MIT License - see LICENSE file for details.

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.