semvec/pypi-packages huggingface dataset:
numberConversion 0.3
A simple package to convert decimal to binary and binary to decimal
Requires Python: >=3.6

## numberConversion

A simple Python package for converting binary to decimal and decimal to binary.

## Installation

Install the package using pip:

pip install numberConversion

## Usage
## Convert Binary to Decimal

from numberConversion import binaryToDecimal

binary_number = "1010"
decimal_number = binaryToDecimal(binary_number)
print(decimal_number)  # Output: 10

## Convert Decimal to Binary

from numberConversion import decimalToBinary

decimal_number = 10
binary_number = decimalToBinary(decimal_number)
print(binary_number)  # Output: "1010"

## License

This package is licensed under the MIT License.
datasci-utils 0.1.0
A comprehensive Python package designed for efficient manipulation and analysis of time series data at scale. Whether you’re working with financial data, retail metrics, or any time-based datasets, tsacme provides the tools you need to clean, analyze, and preprocess your data effectively.
Requires Python: >=3.10

# Create a python environment
poetry config --list
poetry config virtualenvs.in-project true
poetry env activate
poetry run which python

# Install dependencies
poetry install
poetry lock

# Poetry publish package
poetry pubñish
wcnm 0.1.1
A command line tool to get a random quote when you input "cnm".

## Dependencies

dh-python, python3-setuptools, python3-stdeb, lolcat

Use

```bash
sudo apt install dh-python python3-setuptools python3-stdeb lolcat
```

## Build

Use

```bash
python3 setup.py --command-packages=stdeb.command bdist_deb
```

to build the debian package.

It will be located in the `deb_dist` directory.
event-trader 0.1.16
量化交易-选股策略-自定义参数指标
Requires Python: <3.13,>=3.10

# 股票交易策略系统

## 项目意图

本项目旨在提供一个灵活的股票交易策略框架，允许用户通过多种策略对股票进行分析和交易。该系统支持多种技术指标和策略，用户可以根据自己的需求进行优化和调整。

## 项目特点

- **多策略支持**：内置多种交易策略，包括布林带、KDJ、MACD、移动平均等，用户可以根据市场情况选择合适的策略。
- **灵活的参数优化**：支持对策略参数进行优化，帮助用户找到最佳的交易参数。
- **模拟交易账户**：提供模拟账户功能，用户可以在不承担风险的情况下测试策略的有效性。
- **数据可视化**：使用mplfinance库进行数据可视化，帮助用户更直观地理解市场动态。
- **多线程处理**：使用线程池来提高数据处理效率，支持并发获取多个股票的数据。

## 功能概述

- **股票数据管理**：通过`StocksManager`类管理股票数据，支持从不同的股票市场获取数据。
- **策略实现**：每种策略都继承自`BaseStrategy`类，用户可以自定义自己的策略。
- **账户管理**：`DemoAccount`类用于管理模拟交易账户，包括买入、卖出、计算利润等功能。
- **结果展示**：提供结果展示功能，用户可以查看每种策略的表现和相关指标。

## 安装与使用

### 安装依赖

在使用本项目之前，请确保安装了以下依赖库：

```bash
pip install event_trader
```

### 使用步骤
1. 分析个股的各选股策略的表现
```python
from event_trader.strategies import  MA2Strategy, KDJStrategy, MA1Strategy, BollStrategy, MACDStrategy, PriceDeviationStrategy
from china_stock_data import StockData
from event_trader import friendly_number
stock = StockData('601688')
print(f"{stock['股票简称']}, 市值:{friendly_number(stock['总市值'])}")

for strategy in [MA2Strategy, KDJStrategy, MA1Strategy, BollStrategy, MACDStrategy, PriceDeviationStrategy]:
    st = strategy(stock)
    st.show(transaction = False, days = 30)
```

或者输出各个策略的交易信息
```python
for strategy in [MA2Strategy, KDJStrategy, MA1Strategy, BollStrategy, MACDStrategy, PriceDeviationStrategy]:
    st = strategy(stock)
    print(st.transactions())
```

2. 分析个股
```python
from event_trader import StockInfo
stock = StockInfo('600489')
stock.get_result(t)
```

## 贡献

欢迎任何形式的贡献！如果您有建议或发现了问题，请提交issue或pull request。

## 许可证

本项目采用MIT许可证，详细信息请查看LICENSE文件。

## 联系

如有任何问题或建议，请通过以下方式联系我：

- 邮箱: 122828837@qq.com
- <img src="assets/wx.jpg" alt="微信二维码" width="200">


感谢您的支持，欢迎赞助我喝杯咖啡！
forth_kernel 0.4.1
A Jupyter kernel for the Forth programming language. Allows running Forth in interactive Jupyter Notebook.
Requires Python: >=3.8

# IForth

Forth kernel for Jupyter notebook / lab. This is a fork of [github.com/jdfreder/iforth](https://github.com/jdfreder/iforth).

[Open in Colab](https://colab.research.google.com/github/sohang3112/iforth/blob/master/forth_jupyter_tour.ipynb)

![Example Notebook Screenshot](notebook_screenshot.png)

**Note:** Check the [changelog](CHANGELOG.md) to see the latest changes in development as well as in releases.

## Installation

Ensure `python` and `gforth` are available in environment PATH:

```bash
$ pip install forth_kernel
$ python -m forth_kernel.self_install --user
```

**Note:** Currently supported on Linux only because on Windows, `gforth` doesn't work.

### Development Installation

Git clone this repo, then do editable install using [uv](https://github.com/astral-sh/uv): `uv run python -m forth_kernel.self_install --user`.

## Usage

- Run `jupyter notebook` (or `jupyter lab`, whichever you prefer).
- In a new or existing notebook, use the kernel selector (located at the top right of the notebook) to select `IForth`.

```

```
sbcli-hmdi 0.0.57
CLI for managing SimplyBlock cluster


# Simply Block
[![Docker Image Build](https://github.com/simplyblock-io/sbcli/actions/workflows/docker-image.yml/badge.svg)](https://github.com/simplyblock-io/sbcli/actions/workflows/docker-image.yml)

[![Python Unit Testing](https://github.com/simplyblock-io/sbcli/actions/workflows/python-testing.yml/badge.svg)](https://github.com/simplyblock-io/sbcli/actions/workflows/python-testing.yml)


## Install
Add the package repo from AWS CodeArtifact using [awscli](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html)

```bash
aws codeartifact login --tool pip --repository sbcli --domain simplyblock --domain-owner 565979732541 --region eu-west-1
```
Install package
```bash
pip install --extra-index-url https://pypi.org/simple sbcli-dev
```

# Components

## Simply Block Core
Contains core logic and controllers for the simplyblock cluster

## Simply Block CLI
Please see this document
[README.md](../main/simplyblock_cli/README.md)


## Simply Block Web API
Please see this document
[README.md](../main/simplyblock_web/README.md)



### local development

FoundationDB requires a client library (libfdb_c.dylib) for the Python bindings to interact with the database.
Depending on the OS architecture, please install the appropriate version from the official github repo

```
wget https://github.com/apple/foundationdb/releases/download/7.3.3/FoundationDB-7.3.3_arm64.pkg
```

setup the code on a management node and the webApp code can be developed by building the `docker-compose-dev.yml` file.


```
sudo docker compose -f docker-compose-dev.yml up --build -d
```