### Basic yfinance-cache Usage

Source: https://github.com/valueraider/yfinance-cache/blob/main/README.md

Demonstrates the basic interaction with the yfinance-cache library, showing how to import, create a Ticker object, and access historical data and calendar information. This is the primary way to use the library for fetching financial data.

```python
import yfinance_cache as yfc
dat = yfc.Ticker("MSFT")
dat.history(period="1wk")
dat.calendar
# etc
```

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

### View and Set Persistent Cache Options

Source: https://github.com/valueraider/yfinance-cache/blob/main/README.md

Demonstrates how to view and modify persistent caching options, such as the max age for calendar data.

```python
import yfinance_cache as yfc
print(yfc.options)
{
    "max_ages": {
        "calendar": "7d",
        ...
    }
}
yfc.options.max_ages.calendar = '30d'
print(yfc.options)
{
    "max_ages": {
        "calendar": "30d",
        ...
    }
}
```

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

### Price Data Adjustment in yfinance-cache

Source: https://github.com/valueraider/yfinance-cache/blob/main/README.md

Shows how to enable adjustments for stock splits and dividends when fetching historical price data. This ensures the cached data remains accurate by accounting for corporate actions.

```python
dat.history(..., adjust_splits=True, adjust_divs=True)
```

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

### Verify Prices of Entire Cache

Source: https://github.com/valueraider/yfinance-cache/blob/main/README.md

This function verifies prices for all cached ticker symbols, processing them alphabetically. It's recommended to use a `requests_cache` session for debugging. Options include setting tolerances, correcting data, halting on failure, and resuming from a specific ticker.

```python
# Verify prices of entire cache, ticker symbols processed alphabetically. Recommend using `requests_cache` session.
yfc.verify_cached_tickers_prices(
	session=None,  # recommend you provide a requests_cache here if debugging
	rtol=0.0001,
	vol_rtol=0.005,
	correct=[False|'one'|'all'],
	halt_on_fail=True,  # stop verifying on first fail
	resume_from_tkr=None,  # in case you aborted verification, can jump ahead to this ticker symbol. Append '+1' to start AFTER the ticker
	debug_tkr=None,  # only verify this ticker symbol
	debug_interval=None)

```

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

### Set Max Age for Price Data

Source: https://github.com/valueraider/yfinance-cache/blob/main/README.md

Controls when price data cache is updated based on a specified time duration. Defaults to half of the interval.

```python
df = dat.history(interval="1d", max_age="1h", trigger_at_market_close=False, ...)
```

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

### Fix All Data Issues

Source: https://github.com/valueraider/yfinance-cache/blob/main/README.md

To automatically correct all identified data issues across the entire cache, use `verify_cached_tickers_prices` with `correct='all'` and `halt_on_fail=False`.

```python
yfc.verify_cached_tickers_prices(correct='all', halt_on_fail=False)
```

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

### Enable Offline Mode

Source: https://github.com/valueraider/yfinance-cache/blob/main/README.md

Disables all web fetches by setting the session to offline mode. These options reset when Python closes.

```python
import yfinance_cache as yfc
yfc.options.session.offline = True
...
```

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

### Verify Prices of a Single Ticker

Source: https://github.com/valueraider/yfinance-cache/blob/main/README.md

Use this function to check the cached prices for a specific ticker symbol. You can configure relative tolerances for price and volume, and choose how to handle incorrect data (none, first, or all).

```python
# Verify prices of one ticker symbol
dat.verify_cached_prices(
	rtol=0.0001,  # relative tolerance for differences
	vol_rtol=0.005,  # relative tolerance specifically for Volume
	correct=[False|'one'|'all'],  # delete incorrect cached data? 'one' = stop after correcting first incorrect prices table ; 'all' = correct all tickers & intervals
	discard_old=False,  # if cached data too old to check (e.g. 30m), assume incorrect and delete?
	quiet=True,  # enable to print nothing, disable to print summary detail of why cached data wrong
	debug=False,  # enable even more detail for debugging 
	debug_interval=None)

```

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

### Scan for Data Mismatch Without Correction

Source: https://github.com/valueraider/yfinance-cache/blob/main/README.md

To simply scan for the first data mismatch without attempting to correct it, call `verify_cached_tickers_prices()` with default parameters.

```python
yfc.verify_cached_tickers_prices()
```

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

### Set Max Age for Shares Data

Source: https://github.com/valueraider/yfinance-cache/blob/main/README.md

Specifies the maximum age for cached shares data before it is considered stale and needs updating.

```python
df = dat.shares(..., max_age='60d')
```

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