bullishpy


Namebullishpy JSON
Version 0.69.0 PyPI version JSON
download
home_pageNone
SummaryNone
upload_time2025-08-16 16:16:45
maintainerNone
docs_urlNone
authoraan
requires_python<3.13,>=3.12
licenseNone
keywords
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # Bullish

**Bullish** is a high-powered stock screener that helps you quickly identify the best stock or trading opportunities in the market.  
It can scan **thousands of equities** across multiple markets, exchanges, and countries to uncover strong *buy* candidates.  

Bullish uses the well-known **TA-Lib** library to calculate popular technical analysis indicators—such as **RSI**, **MACD**, and moving averages—then lets you filter and select the strongest stocks from your **local database**.

---

## Why Bullish?
The main goals behind Bullish are:
- **Full control over your data** — no dependency on third-party screeners  
- **Local analysis** — run any type of screening or backtesting on your own system  

Bullish is built on:
- **bearish** – a Python library that fetches equity data from multiple sources (*yfinance*, *yahooquery*, *FMP*, …)  
- **tickermood** – retrieves recent, relevant news for screened tickers and uses LLMs to produce an investment recommendation.

---

## Prerequisites
### Install TA-Lib
Bullish depends on **TA-Lib** for technical analysis calculations.  
TA-Lib must be installed separately before using Bullish.  
See the [TA-Lib installation guide](https://ta-lib.org/) for instructions.

---

## Installation
```bash
pip install bullishpy
```

---

## Quick Start

### 1. Create a Bearish Database
A **bearish database** contains historical prices and fundamental data for all stocks in your chosen market.

Example: Create a database for the Belgian stock market:
```bash
bearish run ./bearish.db Belgium
```
You can replace `Belgium` with any supported country.  
**Note:** Building the database can take some time.

---

### 2. Run Bullish
Navigate to the folder containing your **bullish database** and run:
```bash
bullish
```
This launches a **local Streamlit app** where you can screen, filter, and analyze stocks interactively.

![img1.png](docs/img1.png)


![img.png](docs/img.png)

---

## What Bullish Is Not
Bullish is **not**:
- A real-time trading platform  
- A tool for intraday or high-frequency trading  

It is designed for **retail traders** and **swing traders** focusing on opportunities over days or weeks.

            

Raw data

            {
    "_id": null,
    "home_page": null,
    "name": "bullishpy",
    "maintainer": null,
    "docs_url": null,
    "requires_python": "<3.13,>=3.12",
    "maintainer_email": null,
    "keywords": null,
    "author": "aan",
    "author_email": "andoludovic.andriamamonjy@gmail.com",
    "download_url": "https://files.pythonhosted.org/packages/a1/b6/7f63bf53c494aa77f0898a31eb66e870a40a27ed6d5d248fe3a4ea4e7854/bullishpy-0.69.0.tar.gz",
    "platform": null,
    "description": "# Bullish\n\n**Bullish** is a high-powered stock screener that helps you quickly identify the best stock or trading opportunities in the market.  \nIt can scan **thousands of equities** across multiple markets, exchanges, and countries to uncover strong *buy* candidates.  \n\nBullish uses the well-known **TA-Lib** library to calculate popular technical analysis indicators\u2014such as **RSI**, **MACD**, and moving averages\u2014then lets you filter and select the strongest stocks from your **local database**.\n\n---\n\n## Why Bullish?\nThe main goals behind Bullish are:\n- **Full control over your data** \u2014 no dependency on third-party screeners  \n- **Local analysis** \u2014 run any type of screening or backtesting on your own system  \n\nBullish is built on:\n- **bearish** \u2013 a Python library that fetches equity data from multiple sources (*yfinance*, *yahooquery*, *FMP*, \u2026)  \n- **tickermood** \u2013 retrieves recent, relevant news for screened tickers and uses LLMs to produce an investment recommendation.\n\n---\n\n## Prerequisites\n### Install TA-Lib\nBullish depends on **TA-Lib** for technical analysis calculations.  \nTA-Lib must be installed separately before using Bullish.  \nSee the [TA-Lib installation guide](https://ta-lib.org/) for instructions.\n\n---\n\n## Installation\n```bash\npip install bullishpy\n```\n\n---\n\n## Quick Start\n\n### 1. Create a Bearish Database\nA **bearish database** contains historical prices and fundamental data for all stocks in your chosen market.\n\nExample: Create a database for the Belgian stock market:\n```bash\nbearish run ./bearish.db Belgium\n```\nYou can replace `Belgium` with any supported country.  \n**Note:** Building the database can take some time.\n\n---\n\n### 2. Run Bullish\nNavigate to the folder containing your **bullish database** and run:\n```bash\nbullish\n```\nThis launches a **local Streamlit app** where you can screen, filter, and analyze stocks interactively.\n\n![img1.png](docs/img1.png)\n\n\n![img.png](docs/img.png)\n\n---\n\n## What Bullish Is Not\nBullish is **not**:\n- A real-time trading platform  \n- A tool for intraday or high-frequency trading  \n\nIt is designed for **retail traders** and **swing traders** focusing on opportunities over days or weeks.\n",
    "bugtrack_url": null,
    "license": null,
    "summary": null,
    "version": "0.69.0",
    "project_urls": null,
    "split_keywords": [],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "9e12cc1055ba3d2ecd6d009a102156644f46d39b103095bfb5d84b1a63186fc3",
                "md5": "2427beb0395cc369cc0ba5d5fda6c642",
                "sha256": "d33799f2e7507b2a173a34a7bbfcd4f43590224391e3ea3673fac9861834bd2f"
            },
            "downloads": -1,
            "filename": "bullishpy-0.69.0-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "2427beb0395cc369cc0ba5d5fda6c642",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": "<3.13,>=3.12",
            "size": 79865,
            "upload_time": "2025-08-16T16:16:44",
            "upload_time_iso_8601": "2025-08-16T16:16:44.376982Z",
            "url": "https://files.pythonhosted.org/packages/9e/12/cc1055ba3d2ecd6d009a102156644f46d39b103095bfb5d84b1a63186fc3/bullishpy-0.69.0-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "a1b67f63bf53c494aa77f0898a31eb66e870a40a27ed6d5d248fe3a4ea4e7854",
                "md5": "9c6f8213e5e9a4f0af972ccf26d287ab",
                "sha256": "1e486153e9b5273ead10094d9dfcf11c0a6d3cdd1efc18e43b3c05d8078e8426"
            },
            "downloads": -1,
            "filename": "bullishpy-0.69.0.tar.gz",
            "has_sig": false,
            "md5_digest": "9c6f8213e5e9a4f0af972ccf26d287ab",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": "<3.13,>=3.12",
            "size": 53968,
            "upload_time": "2025-08-16T16:16:45",
            "upload_time_iso_8601": "2025-08-16T16:16:45.677902Z",
            "url": "https://files.pythonhosted.org/packages/a1/b6/7f63bf53c494aa77f0898a31eb66e870a40a27ed6d5d248fe3a4ea4e7854/bullishpy-0.69.0.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2025-08-16 16:16:45",
    "github": false,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "lcname": "bullishpy"
}
        
aan
Elapsed time: 0.81266s