<div align="center">
<img alt="logo tradingview screener api library" src="https://raw.githubusercontent.com/houseofai/tvscreener/main/.github/img/logo-tradingview-screener-api.png"><br>
</div>
-----------------
# TradingView Screener API: simple Python library to retrieve data from TradingView Screener
[](https://badge.fury.io/py/tvscreener)
[](https://pepy.tech/project/tvscreener)
[](https://codecov.io/gh/houseofai/tvscreener)
Get the results as a Pandas Dataframe
# Main Features
- Query **Stock**, **Forex** and **Crypto** Screener
- All the **fields available**: ~300 fields - even hidden ones)
- **Any time interval** (`no need to be a registered user` - 1D, 5m, 1h, etc.)
- Filters by any fields, symbols, markets, countries, etc.
- Get the results as a Pandas Dataframe
## Installation
The source code is currently hosted on GitHub at:
https://github.com/houseofai/tvscreener
Binary installers for the latest released version are available at the [Python
Package Index (PyPI)](https://pypi.org/project/tvscreener)
```sh
# or PyPI
pip install tvscreener
```
From pip + GitHub:
```sh
$ pip install git+https://github.com/houseofai/tradingview-screener@main
```
## Usage
For Stocks screener:
```python
import tvscreener as tvs
ss = tvs.StockScreener()
df = ss.get()
# ... returns a dataframe with 150 rows by default
```
For Forex screener:
```python
import tvscreener as tvs
fs = tvs.ForexScreener()
df = fs.get()
```
For Crypto screener:
```python
import tvscreener as tvs
cs = tvs.CryptoScreener()
df = cs.get()
```
## Parameters
For Options and Filters, please check the [notebooks](https://github.com/houseofai/tvscreener/tree/main/notebooks) for examples.
Raw data
{
"_id": null,
"home_page": "https://github.com/houseofai/tvscreener",
"name": "tvscreener",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.10",
"maintainer_email": "",
"keywords": "finance tradingview technical-analysis",
"author": "House of AI",
"author_email": "",
"download_url": "https://files.pythonhosted.org/packages/07/b1/e5b2ff0e1cb4d6de3be16e265a277de53020247c71688373e44883639e20/tvscreener-0.0.12.tar.gz",
"platform": null,
"description": "<div align=\"center\">\n <img alt=\"logo tradingview screener api library\" src=\"https://raw.githubusercontent.com/houseofai/tvscreener/main/.github/img/logo-tradingview-screener-api.png\"><br>\n</div>\n\n-----------------\n\n# TradingView Screener API: simple Python library to retrieve data from TradingView Screener\n\n[](https://badge.fury.io/py/tvscreener)\n[](https://pepy.tech/project/tvscreener)\n[](https://codecov.io/gh/houseofai/tvscreener)\n\n\nGet the results as a Pandas Dataframe\n\n\n\n# Main Features\n- Query **Stock**, **Forex** and **Crypto** Screener\n- All the **fields available**: ~300 fields - even hidden ones)\n- **Any time interval** (`no need to be a registered user` - 1D, 5m, 1h, etc.)\n- Filters by any fields, symbols, markets, countries, etc.\n- Get the results as a Pandas Dataframe\n\n\n## Installation\nThe source code is currently hosted on GitHub at:\nhttps://github.com/houseofai/tvscreener\n\nBinary installers for the latest released version are available at the [Python\nPackage Index (PyPI)](https://pypi.org/project/tvscreener)\n```sh\n# or PyPI\npip install tvscreener\n```\nFrom pip + GitHub:\n```sh\n$ pip install git+https://github.com/houseofai/tradingview-screener@main\n```\n\n## Usage\n\nFor Stocks screener:\n```python\nimport tvscreener as tvs\n\nss = tvs.StockScreener()\ndf = ss.get()\n\n# ... returns a dataframe with 150 rows by default\n``` \nFor Forex screener:\n```python\nimport tvscreener as tvs\n\nfs = tvs.ForexScreener()\ndf = fs.get()\n```\nFor Crypto screener:\n```python\nimport tvscreener as tvs\n\ncs = tvs.CryptoScreener()\ndf = cs.get()\n```\n\n## Parameters\n\nFor Options and Filters, please check the [notebooks](https://github.com/houseofai/tvscreener/tree/main/notebooks) for examples.\n",
"bugtrack_url": null,
"license": "Apache License 2.0",
"summary": "TradingView Screener API",
"version": "0.0.12",
"project_urls": {
"Homepage": "https://github.com/houseofai/tvscreener"
},
"split_keywords": [
"finance",
"tradingview",
"technical-analysis"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "937a98c352909cc17dafe5aa2eb36eb75eaadac9192509003981c0f61198e715",
"md5": "88072f88f1a477ead89836b2c14af088",
"sha256": "0aa983abfb7b83f5cb64c91f7fef6ca95f2e6e0e1630e0705a7a9aa9ec60a2a7"
},
"downloads": -1,
"filename": "tvscreener-0.0.12-py3-none-any.whl",
"has_sig": false,
"md5_digest": "88072f88f1a477ead89836b2c14af088",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.10",
"size": 33383,
"upload_time": "2023-08-09T16:24:01",
"upload_time_iso_8601": "2023-08-09T16:24:01.082127Z",
"url": "https://files.pythonhosted.org/packages/93/7a/98c352909cc17dafe5aa2eb36eb75eaadac9192509003981c0f61198e715/tvscreener-0.0.12-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "07b1e5b2ff0e1cb4d6de3be16e265a277de53020247c71688373e44883639e20",
"md5": "1d6f940bdd8825d8de1420ff427b9806",
"sha256": "ffa3847c7a23355c6698f123124063207287c59db3fbf4a7cfd24c5625657497"
},
"downloads": -1,
"filename": "tvscreener-0.0.12.tar.gz",
"has_sig": false,
"md5_digest": "1d6f940bdd8825d8de1420ff427b9806",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.10",
"size": 25193,
"upload_time": "2023-08-09T16:24:02",
"upload_time_iso_8601": "2023-08-09T16:24:02.924231Z",
"url": "https://files.pythonhosted.org/packages/07/b1/e5b2ff0e1cb4d6de3be16e265a277de53020247c71688373e44883639e20/tvscreener-0.0.12.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-08-09 16:24:02",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "houseofai",
"github_project": "tvscreener",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"requirements": [],
"lcname": "tvscreener"
}
JSON
