How to save a list to a file and read it as a list

Question

Say I have the list score=[1,2,3,4,5] and it gets changed whilst my program is running. How could I save it to a file so that next time the program is run I can access the changed list as a list type?

I have tried:

score=[1,2,3,4,5]

with open("file.txt", 'w') as f:
    for s in score:
        f.write(str(s) + '\n')

with open("file.txt", 'r') as f:
    score = [line.rstrip('\n') for line in f]


print(score)

But this results in the elements in the list being strings not integers.

Answer 1

I am using pandas.

import pandas as pd
x = pd.Series([1,2,3,4,5])
x.to_excel('temp.xlsx')
y = list(pd.read_excel('temp.xlsx')[0])
print(y)

Use this if you are anyway importing pandas for other computations.

Answer 2

What I did not like with many answers is that it makes way too many system calls by writing to the file line per line. Imho it is best to join list with '\n' (line return) and then write it only once to the file:

mylist = ["abc", "def", "ghi"]
myfile = "file.txt"
with open(myfile, 'w') as f:
    f.write("\n".join(mylist))

and then to open it and get your list again:

with open(myfile, 'r') as f:
    mystring = f.read()
my_list = mystring.split("\n")

Answer 3

You can also use python's json module:

import json

score=[1,2,3,4,5]

with open("file.json", 'w') as f:
    # indent=2 is not needed but makes the file more 
    # human-readable for more complicated data
    json.dump(score, f, indent=2) 

with open("file.json", 'r') as f:
    score = json.load(f)

print(score)

The advantage of using a json is that:

1. The file is human readable
2. Non-python programs can read and understand the json file
3. You can literally save any list/dictionary in python to a json (as long as none of the values are objects/functions)

Typically, you'll see jsons used for more complicated nested lists/dictionaries (like an array of records). The main disadvantage of storing your data as a json is that the data is stored in plain-text, and as such is completely uncompressed, making it a slow and bloated option for large amounts of data.

Answer 4

I decided I didn't want to use a pickle because I wanted to be able to open the text file and change its contents easily during testing. Therefore, I did this:

score = [1,2,3,4,5]

with open("file.txt", "w") as f:
    for s in score:
        f.write(str(s) +"\n")

with open("file.txt", "r") as f:
  for line in f:
    score.append(int(line.strip()))

So the items in the file are read as integers, despite being stored to the file as strings.

Answer 5

If you don't want to use pickle, you can store the list as text and then evaluate it:

data = [0,1,2,3,4,5]
with open("test.txt", "w") as file:
    file.write(str(data))

with open("test.txt", "r") as file:
    data2 = eval(file.readline())

# Let's see if data and types are same.
print(data, type(data), type(data[0]))
print(data2, type(data2), type(data2[0]))

[0, 1, 2, 3, 4, 5] class 'list' class 'int'

[0, 1, 2, 3, 4, 5] class 'list' class 'int'

Answer 6

If you want you can use numpy's save function to save the list as file. Say you have two lists

sampleList1=['z','x','a','b']
sampleList2=[[1,2],[4,5]]

here's the function to save the list as file, remember you need to keep the extension .npy

def saveList(myList,filename):
    # the filename should mention the extension 'npy'
    np.save(filename,myList)
    print("Saved successfully!")

and here's the function to load the file into a list

def loadList(filename):
    # the filename should mention the extension 'npy'
    tempNumpyArray=np.load(filename)
    return tempNumpyArray.tolist()

a working example

>>> saveList(sampleList1,'sampleList1.npy')
>>> Saved successfully!
>>> saveList(sampleList2,'sampleList2.npy')
>>> Saved successfully!

# loading the list now 
>>> loadedList1=loadList('sampleList1.npy')
>>> loadedList2=loadList('sampleList2.npy')

>>> loadedList1==sampleList1
>>> True

>>> print(loadedList1,sampleList1)

>>> ['z', 'x', 'a', 'b'] ['z', 'x', 'a', 'b']