sharpstock


Namesharpstock JSON
Version 0.1.0 PyPI version JSON
download
home_pageNone
SummaryA simple Python library to calculate the Sharpe Ratio of a stock.
upload_time2024-11-21 10:12:13
maintainerNone
docs_urlNone
authortim-hub
requires_python<4.0,>=3.12
licenseNone
keywords
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # Sharpe Stock


A simple Python library to calculate the Sharpe Ratio of a stock.

## How to use

```
pip install sharpestock
```

```python
from sharpestock.sharpe_ratio import calculate_sharpe_ratio
df = pd.read_csv('data.csv')
calculate_sharpe_ratio(df)
```



## Features

- [x] Sharpe Ratio Calculation
- [ ] Calculate Sharpe Ratio for multiple stocks

            

Raw data

            {
    "_id": null,
    "home_page": null,
    "name": "sharpstock",
    "maintainer": null,
    "docs_url": null,
    "requires_python": "<4.0,>=3.12",
    "maintainer_email": null,
    "keywords": null,
    "author": "tim-hub",
    "author_email": "tim-hub@users.noreply.github.com",
    "download_url": "https://files.pythonhosted.org/packages/5d/f6/75476da2603ce73d826abd706242eb6cfb3255c4bf6b2c7c162effa000e5/sharpstock-0.1.0.tar.gz",
    "platform": null,
    "description": "# Sharpe Stock\n\n\nA simple Python library to calculate the Sharpe Ratio of a stock.\n\n## How to use\n\n```\npip install sharpestock\n```\n\n```python\nfrom sharpestock.sharpe_ratio import calculate_sharpe_ratio\ndf = pd.read_csv('data.csv')\ncalculate_sharpe_ratio(df)\n```\n\n\n\n## Features\n\n- [x] Sharpe Ratio Calculation\n- [ ] Calculate Sharpe Ratio for multiple stocks\n",
    "bugtrack_url": null,
    "license": null,
    "summary": "A simple Python library to calculate the Sharpe Ratio of a stock.",
    "version": "0.1.0",
    "project_urls": null,
    "split_keywords": [],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "7a70dcedc389209394a881e6b54d28b0139b44e76ba000f7256606db8efc7e88",
                "md5": "3e3ca0f352a0316873e0d322c5bebc85",
                "sha256": "9f5f7ba2fceaddeb6dace1226c54b0afebf87b1585a1b766447fc6b321894ecf"
            },
            "downloads": -1,
            "filename": "sharpstock-0.1.0-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "3e3ca0f352a0316873e0d322c5bebc85",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": "<4.0,>=3.12",
            "size": 6716,
            "upload_time": "2024-11-21T10:12:12",
            "upload_time_iso_8601": "2024-11-21T10:12:12.637506Z",
            "url": "https://files.pythonhosted.org/packages/7a/70/dcedc389209394a881e6b54d28b0139b44e76ba000f7256606db8efc7e88/sharpstock-0.1.0-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "5df675476da2603ce73d826abd706242eb6cfb3255c4bf6b2c7c162effa000e5",
                "md5": "dacabedfee1607f82e4f2ed8b6fb4c63",
                "sha256": "f1292152068eff01a8fe95cace09ec10722eda258ef68f33a959e00a26a1201d"
            },
            "downloads": -1,
            "filename": "sharpstock-0.1.0.tar.gz",
            "has_sig": false,
            "md5_digest": "dacabedfee1607f82e4f2ed8b6fb4c63",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": "<4.0,>=3.12",
            "size": 5676,
            "upload_time": "2024-11-21T10:12:13",
            "upload_time_iso_8601": "2024-11-21T10:12:13.846166Z",
            "url": "https://files.pythonhosted.org/packages/5d/f6/75476da2603ce73d826abd706242eb6cfb3255c4bf6b2c7c162effa000e5/sharpstock-0.1.0.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2024-11-21 10:12:13",
    "github": false,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "lcname": "sharpstock"
}
        
Elapsed time: 1.66290s