semvec/pypi-packages huggingface dataset:
sdeIU 0.0.1
A simple tool for numerical stochastic differential equations
Requires Python: >=3.9

# Stochastic Differential Equations

![Logo](/assets/logo.png)

![forthebadge](/assets/numerical-sde.svg)
![forthebadge](/assets/fokker-planck.svg)

| Package | Documentation | Code Coverage |
| --- | --- | --- |
| sde |  [![Documentation Status](https://readthedocs.org/projects/sde/badge/?version=latest)](https://sde.readthedocs.io/en/latest/?badge=latest) | [![codecov](https://codecov.io/gh/Yuqiu-Yang/sde/branch/main/graph/badge.svg?token=KW3cp0XJky)](https://codecov.io/gh/Yuqiu-Yang/sde) |

So you say you are interested in stochastic differential equations? And you also subscribe to the idea of learning by example? Well, you are in luck!
<b>sde</b> provides basic tools for simulating brownian motions which is the basic ingredients to lots of SDE models, performing different types of stochastic integrations, Eular-Maruyama methods and so much more (to come...). 

We have also built a detailed [online documentation](https://sde.readthedocs.io/en/latest/) where we guide you step-by-step on how to use our package.

The origin of this project is this wonderful introductory [paper](https://epubs.siam.org/doi/pdf/10.1137/S0036144500378302) by Desmond J. Higham.

## Dependencies
- numpy==1.22.4
- tqdm==4.64.1
- matplotlib==3.7.1
- pandas==2.0.0
- seaborn==0.12.2

## Enviroment Setup
We highly recommend creating a virtual environment before proceeding to installing the package. For how to manage virtual
environment via conda, check out 
[their tutorial](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#).

```shell
pip install -r requirements.txt
```

## Installation 
```shell
pip install sde
```
pysecurecircuit 0.0.4
Python library for secure multi-party computation using garbled circuits
Keywords: python,mpc,secure mpc,garbled circuit,multi party computation

# pySecureCircuit

pySecureCircuit is a Python library that allows secure multiparty computation using Yao's garbled circuit technique. The library provides a way for multiple parties to securely compute a function on their private inputs without revealing them to each other, using a combination of encryption, randomization, and computation over circuits.

## Getting Started

### Installation

Run the following command to install the library: 
```sh
pip install pysecurecircuit
```

## Usage

Here's a simple example of how to use pySecureCircuit for the Millionaire's Problem for two parties.

Write your function logic in a python script.

```python
from pysecurecircuit.circuit import Circuit
from pysecurecircuit.server import Server


def main():
    # Create circuit with 2 party
    circuit = Circuit(name="Millionaires' Problem", num_parties=2)

    # Define input variable
    alice_wealth = circuit.newSecureInteger()
    bob_wealth = circuit.newSecureInteger()

    # Circuit logic
    alice_richer_than_bob = alice_wealth > bob_wealth

    # Assign input variables to alice and bob
    circuit.assign_to_party(party_idx=0, name="Wealth (Alice)", variable=alice_wealth)
    circuit.assign_to_party(party_idx=1, name="Wealth (Bob)", variable=bob_wealth)

    # Set circuit's output
    circuit.set_output(name="Alice richer than Bob", variable=alice_richer_than_bob)

    # Start server
    Server(circuit).start()

main()
```

#### Server

To start server for the circuit creator run

```sh
python3 script.py --host 0.0.0.0 --port PORT
```

#### Client

For circuit evaluator, run the following command

```sh
python3 -m pysecurecircuit --client-id CLIENT_ID --host HOST --port PORT
```

Where `CLIENT_ID` is the identifier of the client that starts from 1, `HOST` is the IP address or hostname of the server, and `PORT` is the port number to connect to.

## Contributing

Contributions are welcome! If you'd like to contribute to pySecureCircuit, please fork the repository and create a pull request.

## Acknowledgments

This library is based on Yao's garbled circuit technique, and builds on existing work in secure multiparty computation. Thank you to the researchers and developers who have contributed to this field.
cloudflarestatus 0.0.2
Parse Cloudflare System Status from https://www.cloudflarestatus.com
Requires Python: >=3.11

# Cloudflarestatus
Python package to parse Cloudflare System Status from https://www.cloudflarestatus.com

## Quickstart

### Install

```
$ pip install cloudflarestatus
```

### Command-line usage 1

Get status for a data center:

```
$ cloudflarestatus -d hba
{"HBA": {"code": "HBA", "name": "Hobart, Australia", "status": "partial_outage", "timestamp": 1682596723}}
```

### Command-line usage 2

Pipe to `jq` (a separate program) to format the JSON output:

```
$ cloudflarestatus -d hba syd | jq
{
  "HBA": {
    "code": "HBA",
    "name": "Hobart, Australia",
    "status": "partial_outage",
    "timestamp": 1682596723
  },
  "SYD": {
    "code": "SYD",
    "name": "Sydney, NSW, Australia",
    "status": "operational",
    "timestamp": 1682596723
  }
}
```

### Python usage 1

Get status for all data centers.

```
>>> import cloudflarestatus
>>> cloudflarestatus.dc()
{'ACC': {'code': 'ACC', 'name': 'Accra, Ghana', 'status': 'operational', 'timestamp': 1682596723},
..
'ZRH': {'code': 'ZRH', 'name': 'Zürich, Switzerland', 'status': 'operational', 'timestamp': 1682596723}
```

### Python usage 2

Get status for a data center:

```
>>> import cloudflarestatus
>>> cloudflarestatus.dc('HBA')
{'HBA': {'code': 'HBA', 'name': 'Hobart, Australia', 'status': 'partial_outage', 'timestamp': 1682596723}}
```

### Note

- Internally, `cloudflarestatus` caches response from https://www.cloudflarestatus.com for up to 60 seconds.
- Input for data center code is case-insensitive.

## Package development

### Setup

```
~/.pyenv/versions/3.11.2/bin/python -m venv venv
source venv/bin/activate
pip install -r requirements-dev.txt
```

### Test

```
./test.sh
```

### Format

```
./format.sh
```

### Build

```
./build.sh
```