https://github.com/dhruvan2006/pytoros

Download leveraged token data from Toros Finance
https://github.com/dhruvan2006/pytoros

cryptocurrency finance leverage toros

Last synced: 6 months ago
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Download leveraged token data from Toros Finance

• Host: GitHub
• URL: https://github.com/dhruvan2006/pytoros
• Owner: dhruvan2006
• License: mit
• Created: 2024-11-20T11:10:28.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-12-08T12:34:47.000Z (over 1 year ago)
• Last Synced: 2025-08-15T21:36:19.275Z (8 months ago)
• Topics: cryptocurrency, finance, leverage, toros
• Language: Python
• Homepage: https://pypi.org/project/pytoros/
• Size: 26.4 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# PyToros

Download leveraged token data from [Toros Finance](https://toros.finance/).

[![PyPI Version](https://img.shields.io/pypi/v/pytoros)](https://github.com/dhruvan2006/pytoros)

[![codecov](https://codecov.io/github/dhruvan2006/pytoros/graph/badge.svg?token=8WH1LQUOGP)](https://codecov.io/github/dhruvan2006/pytoros)

[![Monthly Downloads](https://img.shields.io/pypi/dm/pytoros)](https://github.com/dhruvan2006/pytoros)

[![License](https://img.shields.io/github/license/dhruvan2006/pytoros)](https://github.com/dhruvan2006/pytoros)

## Installation

```bash

pip install pytoros

```

## Usage

```python

import pytoros as toros

token = Token("ARB:BTCBULL3X")

history = token.history()

print(history)

```

## API Documentation

### Token Class

#### `Token(ticker: str)`

- **Parameters**:

  - `ticker` (str): The token's identifier (e.g., `ARB:BTCBULL3X`).

- **Description**:

  Initializes the Token object for fetching data.

#### `history(period: str = "1y", interval: str = "1d")`

- **Parameters**:

  - `period` (str): Time range for historical data. Options: `1d`, `1w`, `1m`, `1y` (default: `1y`).

  - `interval` (str): Time interval between data points. Options: `1h`, `4h`, `1d`, `1w` (default: `1d`).

- **Returns**:

  A `pandas.DataFrame` containing historical price data with the following columns:

  - `Date`: Timestamp of the data point.

  - `Open`: Opening price.

  - `Close`: Closing price.

  - `High`: Highest price during the interval.

  - `Low`: Lowest price during the interval.