# Create a Function to get the High and Low of the Stock​

The significance of a stock’s price high lies in the following aspects:

1. It serves as the stoploss level for a sell trade when the sell order is activated.
2. It acts as the trigger point for initiating a buy trade.

Similarly, the low price of a stock holds importance for the following reasons:

1. It functions as the stoploss level for a buy trade once the buy order is executed.
2. It serves as the trigger point for initiating a sell trade.

In summary:

• High of the stock = Buy Trigger = Sell Stoploss
• Low of the stock = Sell Trigger = Buy Stoploss

Now, let’s consider the scenario where we want to determine if yesterday’s NIFTY had an inside bar. How about creating a function that provides us with the high and low prices of the stock on that particular day? This information can be used to assess whether a trade has been triggered or if it has hit its stop loss, among other things.

```				```
def get_stock_data(symbol, time):
try:
datetime_string = str(row['date']) + " 9:20:00+05:30"
parsed_datetime = datetime.datetime.strptime(datetime_string, '%d-%m-%Y %H:%M:%S%z')
previous_day = parsed_datetime - datetime.timedelta(days=1)
from_date = previous_day

data = kite.historical_data(instrument_token=get_insToken(symbol,"NSE"),
from_date=from_date,
to_date=from_date+ datetime.timedelta(days=2),
interval='day')

return data[0]['high'],data[0]['low'],data[1]['open']

except IndexError:
return 0,0,0
```
```

Now let’s explain the entire code step by step –

The `get_stock_data` function takes two parameters: `symbol` (like the stock symbol, e.g., ‘RELIANCE’) and `time` .

```				```
datetime_string = str(row['date']) + " 9:20:00+05:30"
parsed_datetime = datetime.datetime.strptime(datetime_string, '%d-%m-%Y %H:%M:%S%z')

```
```
This line subtracts one day from the `parsed_datetime` to calculate the date for the previous trading day. The result is stored in the `previous_day` variable.
```				```
data = kite.historical_data(instrument_token=get_insToken(symbol,"NSE"),
from_date=from_date,
to_date=from_date+ datetime.timedelta(days=2),
interval='day')
return data[0]['high'], data[0]['low'], data[1]['open']

```
```
This section utilizes an external API or library called `kite` to fetch historical stock data. It specifies the instrument token, date range, and data interval. The retrieved data is stored in the `data` variable. Sometimes there can be trading holidays. So we are taking 2 days of data and checking for the last value using `data[0]`.
×Close