### Install Investiny Package

Source: https://github.com/alvarobartt/investiny/blob/main/docs/installation.md

Installs the Investiny Python package from PyPI using pip. This is the primary method for adding the library to your Python environment.

```console
$ pip install investiny
```

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

### Retrieve Historical Data

Source: https://github.com/alvarobartt/investiny/blob/main/docs/usage.md

Fetches historical data for a given asset from Investing.com using its Investing.com ID. Requires the asset's ID, a start date, and an end date.

```Python
from investiny import historical_data

data = historical_data(investing_id=6408, from_date="09/01/2022", to_date="10/01/2022") # Returns AAPL historical data as JSON (without date)
```

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

### Combined Asset Search and Data Retrieval

Source: https://github.com/alvarobartt/investiny/blob/main/docs/usage.md

Demonstrates the combined usage of search_assets and historical_data. First, it searches for an asset (e.g., AAPL), extracts its Investing.com ID, and then uses that ID to retrieve historical data.

```Python
from investiny import historical_data, search_assets

search_results = search_assets(query="AAPL", limit=1, type="Stock", exchange="NASDAQ")
investing_id = int(search_results[0]["ticker"]) # Assuming the first entry is the desired one (top result in Investing.com)

data = historical_data(investing_id=investing_id, from_date="09/01/2022", to_date="10/01/2022")
```

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

### Retrieve Historical Data

Source: https://github.com/alvarobartt/investiny/blob/main/README.md

Fetches historical data for a given asset from Investing.com. Requires the asset's Investing.com ID, a start date, and an end date. Supports intraday to monthly intervals.

```Python
from investiny import historical_data

data = historical_data(investing_id=6408, from_date="09/01/2022", to_date="10/01/2022")
```

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

### Search Assets and Retrieve ID

Source: https://github.com/alvarobartt/investiny/blob/main/docs/usage.md

Searches for assets on Investing.com based on a query, type, and exchange. It returns a list of results, including the Investing.com ID (ticker) which can be used with the historical_data function.

```Python
from investiny import search_assets

results = search_assets(query="AAPL", limit=1, type="Stock", exchange="NASDAQ") # Returns a list with all the results found in Investing.com
```

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

### Searching Assets with investiny

Source: https://github.com/alvarobartt/investiny/blob/main/docs/differences-with-investpy.md

Shows how to search for available assets using the `search_assets` function in the investiny library. This function helps in finding financial instruments on Investing.com.

```Python
from investiny import search_assets

# Example: Search for assets related to 'Apple'
search_assets(query='Apple')
```

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

### Retrieving Historical Data with investiny

Source: https://github.com/alvarobartt/investiny/blob/main/docs/differences-with-investpy.md

Demonstrates how to retrieve historical data for an asset using the `historical_data` function in the investiny library. This function allows for data retrieval from 1 minute to monthly intervals.

```Python
from investiny import historical_data

# Example: Retrieve daily historical data for Apple Inc.
historical_data(symbol='AAPL', interval='daily', outputsize='full')
```

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

### Combined Asset Search and Historical Data Retrieval

Source: https://github.com/alvarobartt/investiny/blob/main/README.md

Demonstrates how to use `search_assets` to find an asset's Investing.com ID and then use that ID with `historical_data` to retrieve its historical data.

```Python
from investiny import historical_data, search_assets

search_results = search_assets(query="AAPL", limit=1, type="Stock", exchange="NASDAQ")
investing_id = int(search_results[0]["ticker"])

data = historical_data(investing_id=investing_id, from_date="09/01/2022", to_date="10/01/2022")
```

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

### Search Assets on Investing.com

Source: https://github.com/alvarobartt/investiny/blob/main/README.md

Searches for financial assets on Investing.com based on a query, limit, asset type, and exchange. Returns a list of matching assets, including their Investing.com ID (ticker).

```Python
from investiny import search_assets

results = search_assets(query="AAPL", limit=1, type="Stock", exchange="NASDAQ")
```

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

### investiny vs investpy Feature Comparison

Source: https://github.com/alvarobartt/investiny/blob/main/docs/differences-with-investpy.md

This table outlines the key differences in functionality between the investiny and investpy Python libraries for accessing financial data from Investing.com. It details support for intraday data, historical data, asset searching, dividends, economic calendars, technical indicators, and economic news.

```APIDOC
Feature Comparison:
  | Feature                 | investiny | investpy |
  |-------------------------|-----------|----------|
  | Intraday Data           | ✅        | ❌       |
  | Any Range Historical Data | ✅        | ✅       |
  | Search Assets/Quotes    | ✅        | ✅       |
  | Dividends               | ❌        | ✅       |
  | Economic Calendar       | ❌        | ✅       |
  | Technical Indicators    | ❌        | ✅       |
  | Economic News           | ❌        | ✅       |
```

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

### Pandas Integration for Investiny Historical Data

Source: https://github.com/alvarobartt/investiny/blob/main/docs/integrations.md

Demonstrates how to fetch historical data using Investiny and convert it into a Pandas DataFrame, renaming columns and setting the index for compatibility with investpy's output format.

```Python
from investiny import historical_data
import pandas as pd

output = historical_data(investing_id=6408)
data = pd.DataFrame.from_dict(output)
data.rename(columns={
    "date": "Date",
    "open": "Open",
    "high": "High",
    "low": "Low",
    "close": "Close",
    "volume": "Volume"
}, inplace=True)
data.set_index("Date", inplace=True)
```

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

### Search Assets Function

Source: https://github.com/alvarobartt/investiny/blob/main/docs/api/search.md

The `search_assets` function allows users to find financial assets by name or ticker symbol. It returns a list of matching assets.

```Python
def search_assets(query: str, limit: int = 10) -> list:
    """Searches for assets by query.

    Args:
        query: The search query (asset name or ticker).
        limit: The maximum number of results to return.

    Returns:
        A list of dictionaries, where each dictionary represents an asset.
    """
    pass
```

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

### Fetch Historical Data

Source: https://github.com/alvarobartt/investiny/blob/main/docs/api/historical.md

Retrieves historical data for a given asset. This function likely handles the core logic of querying financial data sources, processing the results, and returning them in a structured format. It may accept parameters such as asset ticker, date range, and data frequency.

```Python
from investiny.historical import historical_data

# Example usage (assuming 'AAPL' is a valid ticker and dates are valid)
# historical_data.get_historical_data(ticker='AAPL', start_date='2023-01-01', end_date='2023-12-31', interval='1d')
```

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.