### Install tradingview-ta using pip

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/docs/overview.md

Installs the tradingview-ta package using pip. Requires Python 3.6 or newer and internet access.

```console
pip install tradingview-ta
```

--------------------------------

### Install TradingView TA Python Library

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

Instructions for installing the tradingview_ta Python library from PyPI for stable releases or directly from GitHub for the latest version. Includes commands for initial installation and upgrading.

```bash
pip install tradingview_ta

pip install git+https://github.com/analyzerrest/python-tradingview-ta.git

pip install -U tradingview_ta
```

--------------------------------

### Install tradingview-ta using pip

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/README.md

Installs the stable version of the tradingview-ta library from PyPI. This is the recommended installation method for general use.

```bash
pip install tradingview_ta
```

--------------------------------

### Simple Trading Bot Example with TradingView TA (Python)

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

A basic example of an automated trading bot that uses TradingView TA recommendations to make trading decisions. It continuously fetches analysis, checks the recommendation, and simulates buy/sell orders. This requires the 'tradingview_ta' library and 'time' module. It's a simplified example and needs integration with an actual exchange API for real trading.

```python
from tradingview_ta import TA_Handler, Interval
import time

# Initialize handler
handler = TA_Handler(
    symbol="BTCUSDT",
    exchange="BINANCE",
    screener="crypto",
    interval=Interval.INTERVAL_1_HOUR
)

last_order = "sell"

while True:
    try:
        analysis = handler.get_analysis()
        recommendation = analysis.summary["RECOMMENDATION"]

        print(f"Current recommendation: {recommendation}")
        print(f"Buy signals: {analysis.summary['BUY']}")
        print(f"Sell signals: {analysis.summary['SELL']}")

        if recommendation in ["BUY", "STRONG_BUY"] and last_order == "sell":
            # Execute buy order via exchange API
            print("Signal: BUY")
            last_order = "buy"

        elif recommendation in ["SELL", "STRONG_SELL"] and last_order == "buy":
            # Execute sell order via exchange API
            print("Signal: SELL")
            last_order = "sell"

    except Exception as e:
        print(f"Error: {e}")

    # Wait interval before next check (match your interval setting)
    time.sleep(3600)  # 1 hour for INTERVAL_1_HOUR
```

--------------------------------

### Install latest tradingview-ta from GitHub

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/README.md

Installs the latest development version of the tradingview-ta library directly from its GitHub repository. Use this for access to the newest features and bug fixes.

```bash
pip install git+https://github.com/analyzerrest/python-tradingview-ta.git
```

--------------------------------

### Get TradingView TA Library Version (Python)

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

Retrieves the currently installed version of the tradingview_ta Python library. This is useful for debugging and ensuring compatibility. It requires the 'tradingview_ta' library to be installed.

```python
import tradingview_ta

print(tradingview_ta.__version__)
# Output: 3.3.0
```

--------------------------------

### Get Technical Analysis Summary for TSLA

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/docs/overview.md

Fetches the technical analysis summary for the TSLA stock on NASDAQ for daily intervals using the TA_Handler class. Outputs a dictionary containing recommendation and counts for buy, neutral, and sell signals. Requires the tradingview-ta package.

```python3
from tradingview_ta import TA_Handler, Interval, Exchange

tesla = TA_Handler(
    symbol="TSLA",
    screener="america",
    exchange="NASDAQ",
    interval=Interval.INTERVAL_1_DAY
)
print(tesla.get_analysis().summary)
# Example output: {"RECOMMENDATION": "BUY", "BUY": 8, "NEUTRAL": 6, "SELL": 3}
```

--------------------------------

### Initialize TA_Handler and Get Analysis (Python)

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

Demonstrates how to initialize the TA_Handler class to fetch technical analysis for a single stock symbol. Shows how to access the summary, oscillators, moving averages, and raw indicator values.

```python
from tradingview_ta import TA_Handler, Interval, Exchange

# Create handler for Tesla stock
tesla = TA_Handler(
    symbol="TSLA",
    screener="america",
    exchange="NASDAQ",
    interval=Interval.INTERVAL_1_DAY,
    timeout=10  # Optional: timeout in seconds
)

# Get complete analysis
analysis = tesla.get_analysis()

# Access analysis results
print(analysis.summary)
# Output: {'RECOMMENDATION': 'BUY', 'BUY': 12, 'SELL': 7, 'NEUTRAL': 9}

print(analysis.oscillators)
# Output: {'RECOMMENDATION': 'BUY', 'BUY': 2, 'SELL': 1, 'NEUTRAL': 8, 'COMPUTE': {'RSI': 'NEUTRAL', 'STOCH.K': 'NEUTRAL', ...}}

print(analysis.moving_averages)
# Output: {'RECOMMENDATION': 'BUY', 'BUY': 9, 'SELL': 5, 'NEUTRAL': 1, 'COMPUTE': {'EMA10': 'SELL', 'SMA10': 'SELL', ...}}

# Access raw indicator values
print(analysis.indicators["RSI"])
print(analysis.indicators["close"])
print(analysis.indicators["volume"])
```

--------------------------------

### Define Time Intervals for TA_Handler (Python)

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

Illustrates the use of the Interval class to specify various time intervals for technical analysis. Shows example initializations of TA_Handler with different intervals for crypto and stocks.

```python
from tradingview_ta import Interval

# Available intervals
# Interval.INTERVAL_1_MINUTE   # "1m"
# Interval.INTERVAL_5_MINUTES  # "5m"
# Interval.INTERVAL_15_MINUTES # "15m"
# Interval.INTERVAL_30_MINUTES # "30m"
# Interval.INTERVAL_1_HOUR     # "1h"
# Interval.INTERVAL_2_HOURS    # "2h"
# Interval.INTERVAL_4_HOURS    # "4h"
# Interval.INTERVAL_1_DAY      # "1d" (default)
# Interval.INTERVAL_1_WEEK     # "1W"
# Interval.INTERVAL_1_MONTH    # "1M"

# Example usage with different intervals
handler_hourly = TA_Handler(
    symbol="BTCUSDT",
    screener="crypto",
    exchange="BINANCE",
    interval=Interval.INTERVAL_1_HOUR
)

handler_weekly = TA_Handler(
    symbol="AAPL",
    screener="america",
    exchange="NASDAQ",
    interval=Interval.INTERVAL_1_WEEK
)
```

--------------------------------

### Use Exchange Constants for Forex and CFD (Python)

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

Demonstrates how to use the Exchange class constants to specify forex and CFD markets when initializing TA_Handler. Includes examples for EURUSD and GOLD.

```python
from tradingview_ta import TA_Handler, Interval, Exchange

# Forex example
forex_handler = TA_Handler(
    symbol="EURUSD",
    screener="forex",
    exchange=Exchange.FOREX,  # "FX_IDC"
    interval=Interval.INTERVAL_4_HOURS
)
print(forex_handler.get_analysis().summary)

# CFD example
cfd_handler = TA_Handler(
    symbol="GOLD",
    screener="cfd",
    exchange=Exchange.CFD,  # "TVC"
    interval=Interval.INTERVAL_1_DAY
)
print(cfd_handler.get_analysis().summary)
```

--------------------------------

### Get Multiple Cryptocurrency Analyses with Indicators

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

Fetches technical analysis for multiple cryptocurrency symbols, including additional custom indicators like RSI and MACD. Requires specifying the screener, interval, and a list of symbols.

```python
from tradingview_ta import get_multiple_analysis, Interval

crypto_analyses = get_multiple_analysis(
    screener="crypto",
    interval=Interval.INTERVAL_1_DAY,
    symbols=["BINANCE:BTCUSDT", "BINANCE:ETHUSDT", "BINANCE:SOLUSDT"],
    additional_indicators=["RSI", "MACD.macd", "MACD.signal"]
)

```

--------------------------------

### Import TradingView TA Library

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/docs/usage.md

Imports necessary classes and modules from the tradingview_ta library. Ensure the library is installed or updated to the latest version.

```python
from tradingview_ta import TA_Handler, Interval, Exchange
import tradingview_ta
```

--------------------------------

### Check TradingView TA Library Version

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/docs/usage.md

Retrieves the installed version of the tradingview_ta library using the __version__ attribute. This feature is available from version 3.1.3 onwards.

```python
print(tradingview_ta.__version__)
# Example output: 3.1.3
```

--------------------------------

### Get Raw Indicator Values with TA_Handler

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

Retrieves raw indicator values for a given symbol, exchange, screener, and interval without performing a full analysis. Supports fetching a default set or a custom list of indicators.

```python
from tradingview_ta import TA_Handler, Interval

handler = TA_Handler(
    symbol="BTCUSDT",
    screener="crypto",
    exchange="BINANCE",
    interval=Interval.INTERVAL_1_DAY
)

# Get default indicators
all_indicators = handler.get_indicators()
print(f"RSI: {all_indicators['RSI']}")
print(f"MACD: {all_indicators['MACD.macd']}")
print(f"Close: {all_indicators['close']}")

# Get specific indicators only
specific_indicators = handler.get_indicators(["RSI", "close", "volume", "MACD.macd"])
print(specific_indicators)
# Output: {'RSI': 55.23, 'close': 45326.97, 'volume': 32744.42, 'MACD.macd': 2444.73}

```

--------------------------------

### Get Multiple Analysis

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/docs/usage.md

Fetches technical analysis data for multiple symbols across a specified screener and interval. Note that you cannot mix different screeners and intervals in a single request.

```APIDOC
## GET /analyzerrest/python-tradingview-ta/get_multiple_analysis

### Description
Fetches technical analysis data for multiple symbols. Ensure all symbols belong to the same screener and interval.

### Method
GET

### Endpoint
/analyzerrest/python-tradingview-ta/get_multiple_analysis

### Parameters
#### Query Parameters
- **symbols** (list) - Required - List of exchange and ticker symbols separated by a colon. Example: ["NASDAQ:TSLA", "NYSE:DOCN"]
- **screener** (str) - Required - Screener type (e.g., "america", "indonesia", "forex", "crypto").
- **interval** (str) - Required - Time frame. Use constants from the Interval class (e.g., Interval.INTERVAL_1_DAY).
- **timeout** (float) - Optional - How long to wait (in seconds) for the server to return a response.
- **additional_indicators** (list) - Optional - List of additional indicators to retrieve. Example: ["RSI", "Mom"].

### Request Example
```python
from tradingview_ta import TA_Handler, Interval

analysis = TA_Handler.get_multiple_analysis(
    symbols=["NASDAQ:TSLA", "NYSE:DOCN"],
    screener="america",
    interval=Interval.INTERVAL_1_DAY
)
print(analysis)
```

### Response
#### Success Response (200)
- **dict** - A dictionary where keys are the symbols (e.g., "NASDAQ:TSLA") and values are either an `Analysis` object or `None` if no analysis is found for that symbol.

#### Response Example
```json
{
  "NASDAQ:TSLA": {"RECOMMENDATION": "BUY", "BUY": 8, "NEUTRAL": 6, "SELL": 3},
  "NYSE:DOCN": {"RECOMMENDATION": "SELL", "BUY": 2, "NEUTRAL": 5, "SELL": 9}
}
```

#### Error Response (e.g., 400)
- **dict** - Error message detailing the issue.
```json
{
  "error": "Invalid screener or interval combination."
}
```
```

--------------------------------

### Get Multiple TradingView Analysis Data

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/docs/usage.md

Fetches technical analysis data for multiple symbols from TradingView. Requires specifying the screener, interval, and a list of symbols. The result is a dictionary where keys are symbols and values are Analysis objects.

```python
from tradingview_ta import *
analysis = get_multiple_analysis(screener="america", interval=Interval.INTERVAL_1_HOUR, symbols=["nasdaq:tsla", "nyse:docn", "nasdaq:aapl"])
```

--------------------------------

### Configure Proxy for Analysis Requests

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

Shows how to configure proxy settings for both single and multiple analysis requests. Proxies can be specified as a dictionary with 'http' and 'https' keys.

```python
from tradingview_ta import TA_Handler, Interval, get_multiple_analysis

# Single analysis with proxy
handler = TA_Handler(
    symbol="TSLA",
    screener="america",
    exchange="NASDAQ",
    interval=Interval.INTERVAL_1_DAY,
    proxies={'http': 'http://proxy.example.com:8080', 'https': 'https://proxy.example.com:443'}
)
print(handler.get_analysis().summary)

# Multiple analysis with proxy
analyses = get_multiple_analysis(
    screener="crypto",
    interval=Interval.INTERVAL_1_HOUR,
    symbols=["BINANCE:BTCUSDT", "BINANCE:ETHUSDT"],
    proxies={'http': 'http://proxy.example.com:8080'}
)

```

--------------------------------

### Create a Trading Bot with Python TradingView TA

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/docs/faq.md

This Python code snippet demonstrates how to create a basic trading bot using the TradingView TA library. It continuously fetches analysis recommendations and simulates buy/sell orders based on predefined logic. Ensure you replace placeholder comments with your actual exchange API calls for order execution. The `last_order` variable is not persistent across program restarts.

```python
# Import packages.
from tradingview_ta import TA_Handler, Interval, Exchange
import time

# Store the last order.
last_order = "sell"

# Instantiate TA_Handler.
handler = TA_Handler(
    symbol="SYMBOL",
    exchange="EXCHANGE",
    screener="SCREENER",
    interval="INTERVAL",
)

# Repeat forever.
while True:
    # Retrieve recommendation.
    rec = handler.get_analysis()["RECOMMENDATION"]

    # Create a buy order if the recommendation is "BUY" or "STRONG_BUY" and the last order is "sell".
    # Create a sell order if the recommendation is "SELL" or "STRONG_SELL" and the last order is "buy".
    if "BUY" in rec and last_order == "sell":
        # REPLACE COMMENT: Create a buy order using your exchange's API.

        last_order = "buy"
    elif "SELL" in rec and last_order == "buy":
        # REPLACE COMMENT: Create a sell order using your exchange's API.

        last_order = "sell"

    # Wait for x seconds before retrieving new analysis.
    # The time should be the same as the interval.
    time.sleep(x)
```

--------------------------------

### TA_Handler Instantiation and Parameters

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/docs/usage.md

Demonstrates how to instantiate the TA_Handler class and explains its various parameters for configuring symbol, exchange, screener, interval, and timeout.

```APIDOC
## POST /analyzerrest/python-tradingview-ta

### Description
Instantiate the TA_Handler to configure and retrieve financial analysis data from TradingView.

### Method
POST

### Endpoint
/analyzerrest/python-tradingview-ta

### Parameters
#### Request Body
- **symbol** (str) - Required - Ticker symbol (e.g., "AAPL", "TLKM", "USDEUR", "BTCUSDT").
- **exchange** (str) - Required - Exchange (e.g., "nasdaq", "idx", "forex", "binance"). Use `Exchange` enum for predefined values.
- **screener** (str) - Required - Screener (e.g., "america", "indonesia", "forex", "crypto").
  - For stocks, use the exchange's country.
  - For cryptocurrency, use "crypto".
  - For forex, use "forex".
- **interval** (str) - Required - Time frame. Use `Interval` enum for available intervals (e.g., "1m", "5m", "1h", "1d", "1W", "1M").
- **timeout** (float) - Optional - How long to wait (in seconds) for the server to return a response.

### Request Example
```json
{
  "symbol": "AAPL",
  "exchange": "nasdaq",
  "screener": "america",
  "interval": "1d",
  "timeout": 10
}
```

### Response
#### Success Response (200)
- **analysis** (object) - Contains the technical analysis data.

#### Response Example
```json
{
  "analysis": {
    "summary": {
      "RECOMMENDATION": "BUY",
      "BUY": 10,
      "SELL": 5,
      "NEUTRAL": 11
    },
    "oscillators": {
      "RECOMMENDATION": "SELL",
      "BUY": 2,
      "SELL": 9,
      "NEUTRAL": 5
    },
    "moving_averages": {
      "RECOMMENDATION": "STRONG_BUY",
      "BUY": 16,
      "SELL": 0,
      "NEUTRAL": 0
    }
  }
}
```
```

--------------------------------

### Configure Screener Types with TradingView TA Methods (Python)

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

Demonstrates how to configure different screener types (stocks, cryptocurrency, forex, CFD) using explicit methods on a TA_Handler object. This allows for precise control over the data source for technical analysis. It requires the 'tradingview_ta' library.

```python
from tradingview_ta import TA_Handler, Interval

# Create handler and configure using methods
handler = TA_Handler()

# For stocks - set country as screener
handler.set_screener_as_stock("america")
handler.set_exchange_as_crypto_or_stock("NASDAQ")
handler.set_symbol_as("AAPL")
handler.set_interval_as(Interval.INTERVAL_1_DAY)
print(handler.get_analysis().summary)

# For cryptocurrency
crypto_handler = TA_Handler()
crypto_handler.set_screener_as_crypto()
crypto_handler.set_exchange_as_crypto_or_stock("BINANCE")
crypto_handler.set_symbol_as("BTCUSDT")
crypto_handler.set_interval_as(Interval.INTERVAL_4_HOURS)
print(crypto_handler.get_analysis().summary)

# For forex
forex_handler = TA_Handler()
forex_handler.set_screener_as_forex()
forex_handler.set_exchange_as_forex()
forex_handler.set_symbol_as("EURUSD")
forex_handler.set_interval_as(Interval.INTERVAL_1_HOUR)
print(forex_handler.get_analysis().summary)

# For CFD
cfd_handler = TA_Handler()
cfd_handler.set_screener_as_cfd()
cfd_handler.set_exchange_as_cfd()
cfd_handler.set_symbol_as("GOLD")
cfd_handler.set_interval_as(Interval.INTERVAL_1_DAY)
print(cfd_handler.get_analysis().summary)
```

--------------------------------

### Proxy Configuration

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

Use proxies for requests with both single and multiple analysis functions.

```APIDOC
## Proxy Configuration

### Description
Configure proxy settings to route requests through a proxy server when performing financial market analysis.

### Method
Proxies are configured by passing a `proxies` dictionary to the `TA_Handler` constructor or the `get_multiple_analysis` function.

### Parameters
#### Request Body
- **proxies** (dict) - Required - A dictionary where keys are protocol names ('http', 'https') and values are proxy URLs (e.g., 'http://proxy.example.com:8080').

### Request Example
```python
from tradingview_ta import TA_Handler, Interval, get_multiple_analysis

# Single analysis with proxy
handler = TA_Handler(
    symbol="TSLA",
    screener="america",
    exchange="NASDAQ",
    interval=Interval.INTERVAL_1_DAY,
    proxies={'http': 'http://proxy.example.com:8080', 'https': 'https://proxy.example.com:443'}
)
print(handler.get_analysis().summary)

# Multiple analysis with proxy
analyses = get_multiple_analysis(
    screener="crypto",
    interval=Interval.INTERVAL_1_HOUR,
    symbols=["BINANCE:BTCUSDT", "BINANCE:ETHUSDT"],
    proxies={'http': 'http://proxy.example.com:8080'}
)
```

### Response
This feature configures the underlying HTTP client to use the specified proxies. The response structure depends on the analysis function being called (e.g., `get_analysis()` or `get_multiple_analysis()`).

### Response Example
(The response will be the result of the analysis function, e.g., the `Analysis` object or a dictionary of analyses, with requests routed through the configured proxy.)
```

--------------------------------

### Fetch Multiple Symbol Analysis (Python)

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

Shows how to use the get_multiple_analysis function to retrieve technical analysis data for several symbols in a single request. Explains how to access individual results and iterate through the returned dictionary.

```python
from tradingview_ta import get_multiple_analysis, Interval

# Fetch analysis for multiple US stocks
analyses = get_multiple_analysis(
    screener="america",
    interval=Interval.INTERVAL_1_HOUR,
    symbols=["NASDAQ:TSLA", "NYSE:DOCN", "NASDAQ:AAPL"]
)

# Access individual analysis (use UPPERCASE)
tesla_analysis = analyses["NASDAQ:TSLA"]
print(f"Tesla: {tesla_analysis.summary['RECOMMENDATION']}")

apple_analysis = analyses["NASDAQ:AAPL"]
print(f"Apple: {apple_analysis.summary['RECOMMENDATION']}")

# Iterate through all results
for symbol, analysis in analyses.items():
    if analysis is not None:
        print(f"{symbol}: {analysis.summary['RECOMMENDATION']}")
    else:
        print(f"{symbol}: No analysis available")
```

--------------------------------

### get_indicators Method

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

Retrieve raw indicator values without computed analysis. Supports custom indicator lists.

```APIDOC
## get_indicators Method

### Description
Retrieve raw indicator values without computed analysis. Supports custom indicator lists.

### Method
`handler.get_indicators(indicators: Optional[List[str]] = None)`

### Parameters
#### Query Parameters
- **indicators** (List[str]) - Optional - A list of specific indicator names to retrieve. If not provided, all default indicators are returned.

### Request Example
```python
from tradingview_ta import TA_Handler, Interval

handler = TA_Handler(
    symbol="BTCUSDT",
    screener="crypto",
    exchange="BINANCE",
    interval=Interval.INTERVAL_1_DAY
)

# Get default indicators
all_indicators = handler.get_indicators()
print(f"RSI: {all_indicators['RSI']}")
print(f"MACD: {all_indicators['MACD.macd']}")
print(f"Close: {all_indicators['close']}")

# Get specific indicators only
specific_indicators = handler.get_indicators(["RSI", "close", "volume", "MACD.macd"])
print(specific_indicators)
```

### Response
#### Success Response (200)
- **indicator_name** (float) - The raw value of the requested indicator.

#### Response Example
```json
{
  "RSI": 55.23,
  "close": 45326.97,
  "volume": 32744.42,
  "MACD.macd": 2444.73
}
```
```

--------------------------------

### add_indicators Method

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

Add custom indicators to the handler's indicator list for retrieval.

```APIDOC
## add_indicators Method

### Description
Add custom indicators to the handler's indicator list for retrieval.

### Method
`handler.add_indicators(indicators: List[str])`

### Parameters
#### Request Body
- **indicators** (List[str]) - Required - A list of custom indicator names to add.

### Request Example
```python
from tradingview_ta import TA_Handler, Interval

handler = TA_Handler(
    symbol="AAPL",
    screener="america",
    exchange="NASDAQ",
    interval=Interval.INTERVAL_1_DAY
)

# Add custom indicators to the list
handler.add_indicators(["RSI7", "VWMA", "Pivot.M.Classic.S1", "Pivot.M.Classic.R1"])

# Now get_analysis will include the custom indicators
analysis = handler.get_analysis()
print(analysis.indicators.get("RSI7"))
print(analysis.indicators.get("Pivot.M.Classic.S1"))
```

### Response
This method does not return a value directly but modifies the internal state of the `TA_Handler` object to include the specified indicators for subsequent analysis.

### Response Example
(No direct response body, but subsequent calls to `get_analysis().indicators` will contain the added indicators.)
```

--------------------------------

### TradingView.search Method

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

Search for symbols using TradingView's symbol search API. Returns matching symbols, exchanges, types, descriptions, and logo URLs.

```APIDOC
## TradingView.search Method

### Description
Search for symbols using TradingView's symbol search API. Returns matching symbols, exchanges, types, descriptions, and logo URLs.

### Method
`TradingView.search(symbol: str, exchange: Optional[str] = None, type: Optional[str] = None)`

### Parameters
#### Query Parameters
- **symbol** (str) - Required - The symbol or name to search for (e.g., "tesla", "bitcoin").
- **exchange** (str) - Optional - The exchange to filter the search by (e.g., "NASDAQ", "BINANCE").
- **type** (str) - Optional - The asset type to filter by (e.g., "stock", "crypto", "forex").

### Request Example
```python
from tradingview_ta import TradingView

# Search for Tesla
results = TradingView.search("tesla", "america")
print(results)

# Search for Bitcoin across all types
btc_results = TradingView.search("bitcoin")
for result in btc_results[:5]:
    print(f"{result['exchange']}:{result['symbol']} - {result['description']}")

# Search for specific asset type
crypto_results = TradingView.search("ethereum", type="crypto")
stock_results = TradingView.search("apple", type="stock")
```

### Response
#### Success Response (200)
- **symbol** (str) - The trading symbol.
- **exchange** (str) - The exchange where the symbol is listed.
- **type** (str) - The type of asset (e.g., 'stock', 'crypto').
- **description** (str) - A description of the symbol.
- **logo** (str) - URL of the symbol's logo.

#### Response Example
```json
[
  {
    "symbol": "TSLA",
    "exchange": "NASDAQ",
    "type": "stock",
    "description": "Tesla, Inc.",
    "logo": "https://s3-symbol-logo.tradingview.com/tesla.svg"
  }
]
```
```

--------------------------------

### Access Analysis Object Attributes

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

Demonstrates how to access various attributes of the Analysis object returned by get_analysis(), including metadata, summary recommendations, oscillator and moving average analyses, and raw indicator values.

```python
from tradingview_ta import TA_Handler, Interval

handler = TA_Handler(
    symbol="GOOGL",
    screener="america",
    exchange="NASDAQ",
    interval=Interval.INTERVAL_1_DAY
)

analysis = handler.get_analysis()

# Metadata
print(f"Symbol: {analysis.symbol}")       # "GOOGL"
print(f"Exchange: {analysis.exchange}")   # "NASDAQ"
print(f"Screener: {analysis.screener}")   # "america"
print(f"Interval: {analysis.interval}")   # "1d"
print(f"Time: {analysis.time}")           # datetime object

# Summary recommendation (combined oscillators + moving averages)
print(analysis.summary)
# {'RECOMMENDATION': 'BUY', 'BUY': 12, 'SELL': 7, 'NEUTRAL': 9}

# Oscillators analysis
print(analysis.oscillators)
# {'RECOMMENDATION': 'NEUTRAL', 'BUY': 2, 'SELL': 1, 'NEUTRAL': 8,
#  'COMPUTE': {'RSI': 'NEUTRAL', 'STOCH.K': 'NEUTRAL', 'CCI': 'NEUTRAL',
#              'ADX': 'NEUTRAL', 'AO': 'NEUTRAL', 'Mom': 'BUY', 'MACD': 'SELL', ...}}

# Moving averages analysis
print(analysis.moving_averages)
# {'RECOMMENDATION': 'BUY', 'BUY': 9, 'SELL': 5, 'NEUTRAL': 1,
#  'COMPUTE': {'EMA10': 'SELL', 'SMA10': 'SELL', 'EMA20': 'SELL',
#              'EMA50': 'BUY', 'SMA50': 'BUY', 'EMA200': 'BUY', ...}}

# Raw indicator values
indicators = analysis.indicators
print(f"RSI: {indicators['RSI']}")
print(f"MACD: {indicators['MACD.macd']}")
print(f"Stochastic K: {indicators['Stoch.K']}")
print(f"Close: {indicators['close']}")
print(f"Open: {indicators['open']}")
print(f"High: {indicators['high']}")
print(f"Low: {indicators['low']}")
print(f"Volume: {indicators['volume']}")
print(f"Change %: {indicators['change']}")

```

--------------------------------

### TA Handler with Proxy

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/docs/usage.md

Demonstrates how to use the TA_Handler with proxy settings to retrieve technical analysis for a specific symbol.

```APIDOC
## POST /analyzerrest/python-tradingview-ta/TA_Handler

### Description
Initializes a TA_Handler object to fetch technical analysis for a specific symbol, allowing for proxy configuration.

### Method
POST

### Endpoint
/analyzerrest/python-tradingview-ta/TA_Handler

### Parameters
#### Request Body
- **symbol** (str) - Required - The ticker symbol (e.g., "TSLA").
- **screener** (str) - Required - The screener type (e.g., "america").
- **exchange** (str) - Required - The exchange where the symbol is listed (e.g., "NASDAQ").
- **interval** (str) - Required - The time frame. Use constants from the Interval class (e.g., Interval.INTERVAL_1_DAY).
- **proxies** (dict) - Optional - A dictionary containing proxy configurations for HTTP and HTTPS. Example: `{'http': 'http://0.0.0.0:8080', 'https': 'https://0.0.0.0:443'}`.

### Request Example
```python
from tradingview_ta import TA_Handler, Interval

handler = TA_Handler(
    symbol="TSLA",
    screener="america",
    exchange="NASDAQ",
    interval=Interval.INTERVAL_1_DAY,
    proxies={
        'http': 'http://your_proxy_address:port',
        'https': 'https://your_proxy_address:port'
    }
)

analysis = handler.get_analysis()
print(analysis.summary)
```

### Response
#### Success Response (200)
- **Analysis object** - An object containing the technical analysis summary.

#### Response Example
```json
{
  "RECOMMENDATION": "BUY",
  "BUY": 8,
  "NEUTRAL": 6,
  "SELL": 3
}
```

#### Error Response (e.g., 400)
- **dict** - Error message detailing the issue, potentially related to proxy configuration or invalid parameters.
```json
{
  "error": "Failed to connect to the server. Check proxy settings."
}
```
```

--------------------------------

### Retrieving Analysis

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/docs/usage.md

Shows how to retrieve the technical analysis data using the instantiated TA_Handler object.

```APIDOC
## GET /analyzerrest/python-tradingview-ta/analysis

### Description
Retrieves the technical analysis for the configured symbol, exchange, screener, and interval.

### Method
GET

### Endpoint
/analyzerrest/python-tradingview-ta/analysis

### Parameters
#### Query Parameters
- **symbol** (str) - Required - Ticker symbol.
- **exchange** (str) - Required - Exchange.
- **screener** (str) - Required - Screener.
- **interval** (str) - Required - Time frame.
- **timeout** (float) - Optional - Timeout in seconds.

### Request Example
```
GET /analyzerrest/python-tradingview-ta/analysis?symbol=AAPL&exchange=nasdaq&screener=america&interval=1d&timeout=10
```

### Response
#### Success Response (200)
- **analysis** (object) - Contains the technical analysis data.

#### Response Example
```json
{
  "analysis": {
    "summary": {
      "RECOMMENDATION": "BUY",
      "BUY": 10,
      "SELL": 5,
      "NEUTRAL": 11
    },
    "oscillators": {
      "RECOMMENDATION": "SELL",
      "BUY": 2,
      "SELL": 9,
      "NEUTRAL": 5
    },
    "moving_averages": {
      "RECOMMENDATION": "STRONG_BUY",
      "BUY": 16,
      "SELL": 0,
      "NEUTRAL": 0
    }
  }
}
```
```

--------------------------------

### Instantiate TA_Handler for Financial Analysis

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/docs/usage.md

Creates an instance of the TA_Handler class to fetch financial analysis data. Requires specifying symbol, exchange, screener, and interval. A timeout can also be set.

```python
handler = TA_Handler(
    symbol="",
    exchange="",
    screener="",
    interval="",
    timeout=None
)
```

--------------------------------

### Add Custom Indicators with TA_Handler

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

Allows adding custom indicator names to the TA_Handler's internal list. Once added, these custom indicators can be retrieved using get_analysis().

```python
from tradingview_ta import TA_Handler, Interval

handler = TA_Handler(
    symbol="AAPL",
    screener="america",
    exchange="NASDAQ",
    interval=Interval.INTERVAL_1_DAY
)

# Add custom indicators to the list
handler.add_indicators(["RSI7", "VWMA", "Pivot.M.Classic.S1", "Pivot.M.Classic.R1"])

# Now get_analysis will include the custom indicators
analysis = handler.get_analysis()
print(analysis.indicators.get("RSI7"))
print(analysis.indicators.get("Pivot.M.Classic.S1"))

```

--------------------------------

### Fetch Technical Analysis Summary in Python

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/README.md

Demonstrates how to fetch the technical analysis summary for a given stock symbol using the TA_Handler class. It requires specifying the symbol, screener, exchange, and interval. The output is a dictionary containing recommendation and counts for buy, neutral, and sell signals.

```python
from tradingview_ta import TA_Handler, Interval, Exchange

tesla = TA_Handler(
    symbol="TSLA",
    screener="america",
    exchange="NASDAQ",
    interval=Interval.INTERVAL_1_DAY,
    # proxies={'http': 'http://example.com:8080'} # Uncomment to enable proxy (replace the URL).
)
print(tesla.get_analysis().summary)
# Example output: {"RECOMMENDATION": "BUY", "BUY": 8, "NEUTRAL": 6, "SELL": 3}
```

--------------------------------

### Search Symbols with TradingView.search

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

Searches for financial symbols using TradingView's symbol search API. It can filter by symbol name, exchange, and asset type. Returns a list of dictionaries, each containing symbol details.

```python
from tradingview_ta import TradingView

# Search for Tesla
results = TradingView.search("tesla", "america")
print(results)
# Output: [{'symbol': 'TSLA', 'exchange': 'NASDAQ', 'type': 'stock',
#           'description': 'Tesla, Inc.',
#           'logo': 'https://s3-symbol-logo.tradingview.com/tesla.svg'}, ...]

# Search for Bitcoin across all types
btc_results = TradingView.search("bitcoin")
for result in btc_results[:5]:
    print(f"{result['exchange']}:{result['symbol']} - {result['description']}")

# Search for specific asset type
crypto_results = TradingView.search("ethereum", type="crypto")
stock_results = TradingView.search("apple", type="stock")

```

--------------------------------

### Fetch Analysis with Proxy

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/docs/usage.md

Retrieves market analysis for a given symbol using the TA_Handler, incorporating proxy settings. This allows users to route requests through a specified proxy server. A faulty proxy can lead to request rejection by TradingView.

```python
from tradingview_ta import TA_Handler, Interval, Exchange

tesla = TA_Handler(
    symbol="TSLA",
    screener="america",
    exchange="NASDAQ",
    interval=Interval.INTERVAL_1_DAY,
    proxies={'http': 'http://0.0.0.0:8080', 'https': 'https://0.0.0.0:443'}
)

print(tesla.get_analysis().summary)
```

--------------------------------

### Analysis Object Attributes

Source: https://context7.com/analyzerrest/python-tradingview-ta/llms.txt

The Analysis object returned by get_analysis() contains comprehensive technical analysis data.

```APIDOC
## Analysis Object Attributes

### Description
The Analysis object returned by `get_analysis()` contains comprehensive technical analysis data, including metadata, summary recommendations, oscillator and moving average analysis, and raw indicator values.

### Attributes
- **symbol** (str) - The trading symbol.
- **exchange** (str) - The exchange where the symbol is listed.
- **screener** (str) - The screener used for the analysis.
- **interval** (str) - The time interval for the analysis (e.g., "1d", "1h").
- **time** (datetime) - The timestamp of the analysis.
- **summary** (dict) - A dictionary containing the overall recommendation and counts for buy, sell, and neutral signals.
- **oscillators** (dict) - A dictionary containing the recommendation and counts for oscillators, along with detailed compute results for each oscillator.
- **moving_averages** (dict) - A dictionary containing the recommendation and counts for moving averages, along with detailed compute results for each moving average.
- **indicators** (dict) - A dictionary containing the raw values of all computed indicators.

### Request Example
```python
from tradingview_ta import TA_Handler, Interval

handler = TA_Handler(
    symbol="GOOGL",
    screener="america",
    exchange="NASDAQ",
    interval=Interval.INTERVAL_1_DAY
)

analysis = handler.get_analysis()

# Metadata
print(f"Symbol: {analysis.symbol}")
print(f"Exchange: {analysis.exchange}")
print(f"Screener: {analysis.screener}")
print(f"Interval: {analysis.interval}")
print(f"Time: {analysis.time}")

# Summary recommendation
print(analysis.summary)

# Oscillators analysis
print(analysis.oscillators)

# Moving averages analysis
print(analysis.moving_averages)

# Raw indicator values
indicators = analysis.indicators
print(f"RSI: {indicators['RSI']}")
print(f"MACD: {indicators['MACD.macd']}")
print(f"Stochastic K: {indicators['Stoch.K']}")
print(f"Close: {indicators['close']}")
```

### Response Example
```json
{
  "symbol": "GOOGL",
  "exchange": "NASDAQ",
  "screener": "america",
  "interval": "1d",
  "time": "2023-10-27T10:00:00Z",
  "summary": {
    "RECOMMENDATION": "BUY",
    "BUY": 12,
    "SELL": 7,
    "NEUTRAL": 9
  },
  "oscillators": {
    "RECOMMENDATION": "NEUTRAL",
    "BUY": 2,
    "SELL": 1,
    "NEUTRAL": 8,
    "COMPUTE": {
      "RSI": "NEUTRAL",
      "STOCH.K": "NEUTRAL",
      "CCI": "NEUTRAL",
      "ADX": "NEUTRAL",
      "AO": "NEUTRAL",
      "Mom": "BUY",
      "MACD": "SELL",
      "Stoch.RSI": "NEUTRAL",
      "Bulls": "BUY",
      "WillR": "SELL"
    }
  },
  "moving_averages": {
    "RECOMMENDATION": "BUY",
    "BUY": 9,
    "SELL": 5,
    "NEUTRAL": 1,
    "COMPUTE": {
      "EMA10": "SELL",
      "SMA10": "SELL",
      "EMA20": "SELL",
      "EMA50": "BUY",
      "SMA50": "BUY",
      "EMA100": "BUY",
      "SMA100": "BUY",
      "EMA200": "BUY",
      "SMA200": "BUY",
      "Ichimoku.B": "BUY",
      "VWMA": "BUY",
      "HullMA": "BUY"
    }
  },
  "indicators": {
    "RSI": 55.23,
    "MACD.macd": 2444.73,
    "Stoch.K": 75.5,
    "close": 45326.97,
    "open": 45000.00,
    "high": 45500.00,
    "low": 44800.00,
    "volume": 32744.42,
    "change": 0.75
  }
}
```
```

--------------------------------

### Define TradingView Intervals

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/docs/usage.md

Defines constants for various time intervals supported by TradingView, such as 1 minute, 5 minutes, 1 hour, and 1 day. These constants are used to specify the desired time frame for market analysis.

```python
class Interval:
    INTERVAL_1_MINUTE = "1m"
    INTERVAL_5_MINUTES = "5m"
    INTERVAL_15_MINUTES = "15m"
    INTERVAL_30_MINUTES = "30m"
    INTERVAL_1_HOUR = "1h"
    INTERVAL_2_HOURS = "2h"
    INTERVAL_4_HOURS = "4h"
    INTERVAL_1_DAY = "1d"
    INTERVAL_1_WEEK = "1W"
    INTERVAL_1_MONTH = "1M"
```

--------------------------------

### Symbol Search API

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/docs/usage.md

Searches for symbols using the TradingView symbol search API. Returns a list of symbols, exchanges, types, descriptions, and logo URLs matching the search query.

```APIDOC
## GET /analyzerrest/python-tradingview-ta/search

### Description
Searches for trading symbols based on a text query and optional asset type.

### Method
GET

### Endpoint
/analyzerrest/python-tradingview-ta/search

### Parameters
#### Query Parameters
- **text** (str) - Required - The search query string.
- **type** (str) - Optional - The type of asset to search for (e.g., "stock", "crypto", "futures", "index"). Defaults to None (searches all types).

### Request Example
```python
from tradingview_ta import TradingView

results = TradingView.search(text="tesla", type="stock")
print(results)
```

### Response
#### Success Response (200)
- **list** - A list of dictionaries, where each dictionary contains details about a found symbol:
  - **symbol** (str) - The ticker symbol.
  - **exchange** (str) - The exchange where the symbol is listed.
  - **type** (str) - The type of asset.
  - **description** (str) - A description of the symbol.
  - **logo** (str) - The URL of the symbol's logo.

#### Response Example
```json
[
  {
    "symbol": "TSLA",
    "exchange": "NASDAQ",
    "type": "stock",
    "description": "Tesla, Inc.",
    "logo": "https://s3-symbol-logo.tradingview.com/tesla.svg"
  }
]
```

#### NOTE
Symbols returned by this function may not always be compatible with the `get_analysis()` function.
```

--------------------------------

### Search TradingView Symbols

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/docs/usage.md

Searches for trading symbols on TradingView based on a query string and an optional asset type. It returns a list of matching symbols, their exchanges, types, descriptions, and logo URLs. Note that symbols returned may not always be compatible with analysis functions.

```python
from tradingview_ta import TradingView

print(TradingView.search("tesla", "america"))
```

--------------------------------

### Retrieve Financial Analysis Data

Source: https://github.com/analyzerrest/python-tradingview-ta/blob/main/docs/usage.md

Fetches the financial analysis data for the configured TA_Handler instance. This method sends a request to the TradingView servers and returns the analysis results.

```python
analysis = handler.get_analysis()
```

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