semvec/pypi-packages huggingface dataset:
getkrxcode 0.1.2
a package to get KRX stock code using data.go.kr API
Requires Python: >=3.8

# getkrxcode
[공공데이터포탈](data.go.kr) 금융위원회_KRX상장종목정보 API를 사용해 한국 거래소(KRX) 상장 기업의 종목 코드를 조회하는 프로젝트입니다.
최신 상장 기업 정보를 자동으로 가져와 금융 데이터 분석이나 애플리케이션 개발에 활용할 수 있도록 돕습니다.

Retrieve KRX-listed company stock codes using the official data.go.kr API

This project retrieves stock codes for companies listed on the Korea Exchange (KRX) using the official API provided by data.go.kr. It simplifies accessing financial data by automating the retrieval process, ensuring that users have up-to-date information on KRX-listed companies for further analysis or integration into financial applications.

### 사용법 use guide

1. 먼저 https://www.data.go.kr/data/15094775/openapi.do 에서 서비스 키를 발급 받으세요
- first, get your service key from https://www.data.go.kr/en/data/15094775/openapi.do
2. 발급 받은 서비스 키를 project.py가 있는 폴더에 serviceKey.txt라는 파일에 저장하세요
- store your service key in a txt file called serviceKey.txt in the same folder as project.py

### 주요 기능 functions

- read_service_key_from_text
- fetch_stock_by_name
- fetch_code_by_name
- fetch_all_listings

#### Video Demo:  <URL [HERE](https://youtu.be/JV72hRNXSDc)>
pydialogs 1.0
Python library for terminal-based dialogs

# pydialogs
Python Library for making Dialogs
## Requirements
- Python 3.x
- `curses` and `textwrap` libraries
## Functions
### 1. `alert(title, message, width=50, height=10, button="OK")`
Displays a simple alert box in the console.
#### Parameters:
- `title` (str): The title of the box.
- `message` (str): The message to display in the box.
- `width` (int, optional): The width of the box. Default is 50.
- `height` (int, optional): The height of the box. Default is 10.
- `button` (str, optional): The label of the button. Default is "OK".
#### Example Usage:
```python
alert("Welcome", "Welcome to my script, press OK to continue.")
```
### 2. `select(title, message, width=50, height=10, options=None)` `(returns str)`
Displays a box in the console where the user can use the arrow keys to navigate through choices the user can select.
#### Parameters:
- `title` (str): The title of the selection box.
- `message` (str): The message to display in the box.
- `width` (int, optional): The width of the box. Default is 50.
- `height` (int, optional): The height of the box. Default is 10.
- `options` (list, optional): A list of options to choose from. Default is `["Yes", "No"]`.
#### Example Usage:
```python
selection = select("IMPORTANT", "All data will be erased on drive Z:\, do you want to continue?", options=["Yes", "No"])
alert(f"You selected: {selection}")
```
ASBPredictor 0.1.1
A Python package for predicting ASB risk from clinical data.
Requires Python: >=3.6

# **ASBPredictor**

`ASBPredictor` is a Python package for predicting **ASB (Asymptomatic Bacteriuria)** risk. It uses a pre-trained `RandomForestClassifier` model and generates predictions based on clinical data in CSV format. This package is suitable for medical data analysis and clinical research.

---

## **Features**

- **Fast Prediction**: Supports batch input data and generates ASB risk predictions.
- **Easy to Use**: Command-line interface for straightforward operation.
- **Flexible Input**: Supports multi-row CSV input files, with results saved to a new file with predicted probabilities.
- **Customizable**: Allows replacement of the default model with custom-trained models.

---

## **Installation**

### Install from PyPI
Run the following command:
```bash
pip install ASBPredictor
```

## **Usage**

Command-Line Interface
Once installed, you can run ASBPredictor directly from the command line.

Basic Command:
```bash
ASBPredictor -i <input_csv_path> -o <output_csv_path>
```

## **Example**

```bash
git clone https://github.com/yangfangs/ASBPredictor.git
cd ASBPredictor/examples/
ASBPredictor -i input_data.csv -o output_data.csv
```

## **Requirements**
```angular2html
Python version >= 3.6
Required libraries:
pandas >= 1.0.0
scikit-learn >= 1.5.0
```