semvec/pypi-packages huggingface dataset:
order-matching-engine 0.2.4
Add your description here
Requires Python: >=3.12

# Order-Matching-Engine
High-performance order matching engine for backtesting and real-time simulation workloads.

## Features
- Limit and market orders
- Order cancelling
- Configurable price-time or price-size priority per orderbook
- GTC, IOC, FOK options for limit orders
- Midpoint-pegged orders with automatic repricing on quote updates

## Install

Install from Pypi with pip:

```
pip install order-matching-engine
```

## Usage

```python
>>> from order_matching_engine import LimitOrder, MatchingEngine, Orderbook, PriorityType, Side
>>> orderbook = Orderbook()
>>> engine = MatchingEngine(orderbook=orderbook)
>>> engine.process_order(LimitOrder(1, Side.BUY, 10, 100))
[]
>>> engine.process_order(LimitOrder(2, Side.BUY, 15, 100))
[]
>>> engine.process_order(LimitOrder(3, Side.SELL, 20, 99.5))
[Trade(timestamp=1761593166103727, side=SELL, price=100, size=10, incoming_order_id=3, book_order_id=1), Trade(timestamp=1761593166103727, side=SELL, price=100, size=10, incoming_order_id=3, book_order_id=2)]
```

## Local Development

### Installation
Ensure [uv](https://github.com/astral-sh/uv) is installed, then install project dependencies:

```bash
uv sync
```

### Single orderbook on one thread:
On average, the engine takes 2.5μs to process an order. This means that the engine can ingest and process 400k orders per second (on 3 GHz Intel Core i7, 16 GB 1600 MHz DDR3) using the pypy interpreter. More benchmarks to come.

### Multiple orderbooks, one thread per orderbook:
On average, the engine takes 1.18μs to process an order. This means that the engine can ingest and process 850k orders per second (on 3 GHz Intel Core i7, 16 GB 1600 MHz DDR3) using the pypy interpreter. More benchmarks to come.

### Testing
Install dev dependencies and execute the unit/performance suites through uv:

```bash
uv sync --group dev
uv run pytest -s
```
taxion-commons 0.1.0
Add your description here
Requires Python: >=3.10

# create a venv (optional but recommended)
python -m venv .venv
source .venv/bin/activate

# install tools
pip install --upgrade pip build twine pytest

# run tests
pytest -q

# clean previous builds (optional)
rm -rf dist build *.egg-info

# build sdist + wheel
python -m build

# verify dist contents
ls -la dist
# example output: your-package-name-0.0.1-py3-none-any.whl, your-package-name-0.0.1.tar.gz
plotly-bootstrap-templates 2.1.0.post1
A collection of Plotly figure templates with a Bootstrap theme
Requires Python: >=3.9

# Plotly Bootstrap Templates

> [!NOTE]
> has been forked from <https://github.com/AnnMarieW/dash-bootstrap-templates>. All dependencies on `dash` and `dash-bootstrap-components` have been removed from the installable package to allow usage with plain plotly graphing library without the need to install dash. Package management has been modernized to `uv` and the package code has been cleaned up for the targeted purpose.

## Figure Template Quickstart

> [!TIP]
> Learn more about Plotly figure templates and themes at: <https://plotly.com/python/templates/>

Install the package as usual with your favorite Python package manager, the package name is `plotly-bootstrap-templates`.
Then, use the main package function `load_figure_template` to load the template.
It is automatically stored in the `plotly.io.templates` dictionary.
`plotly.io.templates.default` will be automatically set to the requested template afterwards.

```python
from plotly_bootstrap_templates import load_figure_template

load_figure_template("flatly")
```

You may load several theme at once by giving a list, the default template will then be the first in this list.

```python
load_figure_template(["flatly", "solar"])
```

To get a full list of the available templates, print the `TEMPLATES` constant.
For each of them, also a `*_dark` variant exists, which are listed in the `TEMPLATES_DARK` constant.

```python
from plotly_bootstrap_templates import TEMPLATES, TEMPLATES_DARK

print("templates:\n", TEMPLATES)
print("dark templates:\n", TEMPLATES_DARK)
```

## Development

To create the project virtual environment using `uv` run:

```shell
uv sync
```

To regenerate the template data files, run:

```shell
./_create_templates.py
```

The script is equipped with a respective shebang to tell uv which dependencies to use for that (which are not necessary at runtime of the package).

To run the test suite, use:

```python
uv run pytest
```

This will generate an example plot of the gapminder test data set for every available theme and open the result in your default browser using the `webbrowser` package.

## Further Information

For further reading visit the [original repository](https://github.com/AnnMarieW/dash-bootstrap-templates).
gbg-remote-sdk 0.1.2
Software Development Kit for the SOAP-based API for Green Button Go Remote Control
Requires Python: >=3.12.7

[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
[![uv](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json)](https://github.com/astral-sh/uv)
[![Checked with pyright](https://microsoft.github.io/pyright/img/pyright_badge.svg)](https://microsoft.github.io/pyright/)
[![Actions status](https://github.com/lab-sync/gbg-remote-sdk/actions/workflows/ci.yaml/badge.svg?branch=main)](https://github.com/lab-sync/gbg-remote-sdk/actions)
[![Open in Dev Containers](https://img.shields.io/static/v1?label=Dev%20Containers&message=Open&color=blue)](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/lab-sync/gbg-remote-sdk)
[![PyPI Version](https://img.shields.io/pypi/v/gbg-remote-sdk.svg)](https://pypi.org/project/gbg-remote-sdk/)
[![Downloads](https://pepy.tech/badge/gbg-remote-sdk)](https://pepy.tech/project/gbg-remote-sdk)
[![Python Versions](https://img.shields.io/pypi/pyversions/gbg-remote-sdk.svg)](https://pypi.org/project/gbg-remote-sdk/)
[![Codecov](https://codecov.io/gh/lab-sync/gbg-remote-sdk/branch/main/graph/badge.svg)](https://codecov.io/gh/lab-sync/gbg-remote-sdk)

# Usage
Documentation is hosted on [ReadTheDocs](https://gbg-remote-sdk.readthedocs.io/en/latest/?badge=latest).

# Development
This project has a dev container. If you already have VS Code and Docker installed, you can click the badge above or [here](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/lab-sync/gbg-remote-sdk) to get started. Clicking these links will cause VS Code to automatically install the Dev Containers extension if needed, clone the source code into a container volume, and spin up a dev container for use.

To publish a new version of the repository, you can run the `Publish` workflow manually and publish to the staging registry from any branch, and you can check the 'Publish to Primary' option when on `main` to publish to the primary registry and create a git tag.

### For doing testing of the GBG Remote interface:
Open a connection to the EC2 instance hosting GBG in AWS:
```bash
aws ssm start-session --target i-033eef3ccfbe82829 --document-name AWS-StartPortForwardingSession --parameters '{"portNumber":["8080"],"localPortNumber":["8080"]}'
```

### Snapshots during testing
When running the unit test suite, `pytest-recording` library is used. If it gives you errors about a cassette missing, the parameter to invoke a live HTTP request is `--record-mode=once` (add on to the end of the `pytest` command)



## Updating from the template
This repository uses a copier template. To pull in the latest updates from the template, use the command:
`copier update --trust --conflict rej --defaults`