Changing values of a list of namedtuples
I have a list of namedtuples named Books
and am trying to increase the price
field by 20% which does change the value of Books
. I tried to do:
from collections import namedtuple
Book = namedtuple('Book', 'author title genre year price instock')
BSI = [
Book('Suzane Collins','The Hunger Games', 'Fiction', 2008, 6.96, 20),
Book('J.K. Rowling', "Harry Potter and the Sorcerer's Stone", 'Fantasy', 1997, 4.78, 12)]
for item in BSI:
item = item.price*1.10
print(item.price)
But I keep getting :
Traceback (most recent call last):
print(item.price)
AttributeError: 'float' object has no attribute 'price'
I understand that I cannot set the fields in a namedtuple. How do I go about updating price
?
I tried to make it into a function:
def restaurant_change_price(rest, newprice):
rest.price = rest._replace(price = rest.price + newprice)
return rest.price
print(restaurant_change_price(Restaurant("Taillevent", "French", "343-3434", "Escargots", 24.50), 25))
but I get an error with replace saying:
rest.price = rest._replace(price = rest.price + newprice)
AttributeError: can't set attribute
Can someone let me know why this is happening?
Named tuples are immutable, so you cannot manipulate them.
Right way of doing it:
If you want something mutable, you can use recordtype
.
from recordtype import recordtype
Book = recordtype('Book', 'author title genre year price instock')
books = [
Book('Suzane Collins','The Hunger Games', 'Fiction', 2008, 6.96, 20),
Book('J.K. Rowling', "Harry Potter and the Sorcerer's Stone", 'Fantasy', 1997, 4.78, 12)]
for book in books:
book.price *= 1.1
print(book.price)
PS: You may need to pip install recordtype
if you don't have it installed.
Bad way of doing it:
You may also keep using namedtuple
with using the _replace()
method.
from collections import namedtuple
Book = namedtuple('Book', 'author title genre year price instock')
books = [
Book('Suzane Collins','The Hunger Games', 'Fiction', 2008, 6.96, 20),
Book('J.K. Rowling', "Harry Potter and the Sorcerer's Stone", 'Fantasy', 1997, 4.78, 12)]
for i in range(len(books)):
books[i] = books[i]._replace(price = books[i].price*1.1)
print(books[i].price)
In Python >= 3.7 you can use dataclass decorator with the new variable annotations feature to produce mutable record types:
from dataclasses import dataclass
@dataclass
class Book:
author: str
title: str
genre: str
year: int
price: float
instock: int
BSI = [
Book("Suzane Collins", "The Hunger Games", "Fiction", 2008, 6.96, 20),
Book(
"J.K. Rowling",
"Harry Potter and the Sorcerer's Stone",
"Fantasy",
1997,
4.78,
12,
),
]
for item in BSI:
item.price *= 1.10
print(f"New price for '{item.title}' book is {item.price:,.2f}")
Output:
New price for 'The Hunger Games' book is 7.66
New price for 'Harry Potter and the Sorcerer's Stone' book is 5.26
This looks like a task for Python's data analysis library, pandas. It's really, really easy to do this sort of thing:
In [6]: import pandas as pd
In [7]: df = pd.DataFrame(BSI, columns=Book._fields)
In [8]: df
Out[8]:
author title genre year \
0 Suzane Collins The Hunger Games Fiction 2008
1 J.K. Rowling Harry Potter and the Sorcerers Stone Fantasy 1997
price instock
0 6.96 20
1 4.78 12
In [9]: df['price'] *= 100
In [10]: df
Out[10]:
author title genre year \
0 Suzane Collins The Hunger Games Fiction 2008
1 J.K. Rowling Harry Potter and the Sorcerer's Stone Fantasy 1997
price instock
0 696 20
1 478 12
Now isn't that just much, much better than labouring with namedtuple
s?