Markets Scraper

Overview

The Markets scraper retrieves ranked stock lists from TradingView's scanner API across multiple market regions. Stocks can be sorted by market cap, volume, price change, closing price, or volatility.

Quick Start

from tv_scraper.scrapers.market_data import Markets

markets = Markets()
result = markets.get_markets(market="america", sort_by="market_cap", limit=20)

for stock in result["data"]:
    print(stock["symbol"], stock["close"], stock["market_cap_basic"])

API Reference

Constructor

Markets(export_result: bool = False, export_type: str = "json", timeout: int = 10)

Parameter	Type	Default	Description
`export_result`	`bool`	`False`	Whether to export results to file
`export_type`	`str`	`"json"`	Export format (`"json"` or `"csv"`)
`timeout`	`int`	`10`	HTTP request timeout in seconds

`get_markets()`

get_markets(
    market: str = "america",
    sort_by: str = "market_cap",
    fields: Optional[List[str]] = None,
    sort_order: str = "desc",
    limit: int = 50,
) -> Dict[str, Any]

Parameter	Type	Default	Description
`market`	`str`	`"america"`	Market region to scan
`sort_by`	`str`	`"market_cap"`	Sort criterion key
`fields`	`List[str]\|None`	`None`	Scanner fields; defaults to built-in
`sort_order`	`str`	`"desc"`	`"desc"` or `"asc"`
`limit`	`int`	`50`	Maximum number of results

Supported Markets

Key	Region
`america`	United States
`australia`	Australia
`canada`	Canada
`germany`	Germany
`india`	India
`uk`	United Kingdom
`crypto`	Cryptocurrency
`forex`	Forex
`global`	All markets

Sort Criteria

Key	Scanner Field	Description
`market_cap`	`market_cap_basic`	Market capitalization
`volume`	`volume`	Trading volume
`change`	`change`	Price change percentage
`price`	`close`	Current closing price
`volatility`	`Volatility.D`	Daily volatility

Default Fields

name, close, change, change_abs, volume, Recommend.All, market_cap_basic, price_earnings_ttm, earnings_per_share_basic_ttm, sector, industry

Response Format

{
    "status": "success",
    "data": [
        {
            "symbol": "NASDAQ:AAPL",
            "name": "Apple Inc.",
            "close": 150.25,
            "change": 2.5124,
            "change_abs": 3.68,
            "volume": 54231200,
            "Recommend.All": 0.5,
            "market_cap_basic": 2500000000000.0,
            "price_earnings_ttm": 28.5,
            "earnings_per_share_basic_ttm": 5.2,
            "sector": "Electronic Technology",
            "industry": "Telecommunications Equipment"
        },
        {
            "symbol": "NASDAQ:MSFT",
            "name": "Microsoft Corp.",
            "close": 310.15,
            "change": -1.2,
            "change_abs": -3.75,
            "volume": 28145000,
            "Recommend.All": 0.45,
            "market_cap_basic": 2300000000000.0,
            "price_earnings_ttm": 32.1,
            "earnings_per_share_basic_ttm": 9.5,
            "sector": "Technology Services",
            "industry": "Packaged Software"
        }
    ],
    "metadata": {
        "market": "america",
        "sort_by": "market_cap",
        "total": 2,
        "total_count": 5000
    },
    "error": null
}

Examples

Most Active Stocks by Volume

result = markets.get_data(market="america", sort_by="volume", limit=15)

Top Indian Stocks Ascending by Price

result = markets.get_data(market="india", sort_by="price", sort_order="asc", limit=10)

Custom Fields

result = markets.get_data(
    fields=["name", "close", "volume", "market_cap_basic", "sector"],
    limit=10,
)

Export to CSV

markets = Markets(export_result=True, export_type="csv")
result = markets.get_data(market="uk", sort_by="market_cap")