semvec/pypi-packages huggingface dataset:
shirotsubaki 0.0.1a7
This package is being developed to help generate beautiful reports.
Requires Python: >=3.10

# shirotsubaki

This package is being developed to help generate beautiful reports.  
[Documentation](https://shirotsubaki.readthedocs.io/en/latest/)

### Installation (for Users)

#### From PyPI

You can install the release version from [PyPI](https://pypi.org/project/shirotsubaki/).
```
pip install shirotsubaki
```

#### From Local Source Code

If you want to use the latest version that has not been released, clone this repository and install from the local directory.

```
git clone git@github.com:CookieBox26/shirotsubaki.git
cd shirotsubaki
pip install .
```

### Development Guide (for Developers)

Please run the following commands.

```
git clone git@github.com:CookieBox26/shirotsubaki.git
cd shirotsubaki
# make some changes to the code
pytest  # Please test locally
vi docs/reference.md  # Please update documentation
mkdocs serve  # Please preview documentation locally
```
If you have run the command above, you can view the documentation at http://localhost:8000/.  
If you are not an administrator, please open a pull request at this point.

### Build and upload the distribution archives (for administrator only)

Please run the following commands. More details are [here](https://packaging.python.org/en/latest/tutorials/packaging-projects/).

```
pip install --upgrade build
pip install --upgrade twine
pip install --upgrade pkginfo  # This might be needed

python -m build
python -m twine upload dist/*
```
newton-clips 0.1.8
Clips from newton-physics simulation to Unreal Engine 5 runtime
Requires Python: >=3.9
Keywords: newton, physics, simulation, unreal engine

# newton-clips

> Clips from [newton-physics](https://github.com/newton-physics/newton) simulation to Unreal Engine 5 runtime

- exchange the simulation data with [NewtonClips](https://github.com/doidio/NewtonClips), a twin UE5 plugin
- replace renderers in `newton-physics` and convert simulation data
- support `newton-physics` examples with the least code change

## Install

```
pip install newton-clips
```

## Getting started

1. run `newtonclips/example.py`
2. find generated simulation data in `newtonclips.SAVE_DIR`
3. use this directory in [NewtonClips](https://github.com/doidio/NewtonClips)

## How to run `newton.examples`

```python
import newtonclips  # replace newton renderers implicitly

newtonclips.SAVE_DIR = '.clips'  # set directory to save simulation data

# make sure you have installed the necessary external libraries
from newton.examples.basic import example_basic_shapes as example
import runpy

runpy.run_path(example.__file__, run_name='__main__')
```
moto-testkit 0.1.3
An extended testkit for AWS services using moto, with sync/async helpers and examples.
Requires Python: >=3.8
Keywords: aws, testing, moto, pytest, unittest, dynamodb, s3, asyncio

# moto-testkit

**moto-testkit** is an enhanced testing toolkit built on top of [moto](https://github.com/getmoto/moto), providing:
- Easy setup for **unit tests** (Pytest + Unittest).
- Support for **sync and async workflows**.
- Ready-to-use **helpers** for AWS services.
- A full **examples/** directory with practical test cases.

---

## 🚀 Benefits over `moto`
- ✅ Simplified setup for both sync & async tests.
- ✅ Preconfigured decorators and fixtures for Pytest & Unittest.
- ✅ Rich **examples** for DynamoDB, S3, and other AWS services.
- ✅ Helpers for repetitive patterns (table creation, sessions, contexts).

---

## 📂 Examples
Check the [examples/](examples) folder for:
- **Pytest usage** with async/sync.
- **Unittest usage** with decorators.
- **Service-specific helpers**.

```python
import unittest
from moto_testkit import use_moto_testkit

@use_moto_testkit(auto_start=True)
class TestDynamoDB(unittest.TestCase):
    def setUp(self):
        self.repo.create_table(
            table_name="Users",
            key_schema=[{"AttributeName": "id", "KeyType": "HASH"}],
            attribute_definitions=[{"AttributeName": "id", "AttributeType": "S"}]
        )

    def test_insert_user(self):
        self.repo.put_item(table_name="Users", item={"id": "123", "name": "Alice"})
        result = self.repo.get_item(table_name="Users", key={"id": "123"})
        assert result["Item"]["name"] == "Alice"