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:
You can use pickle
module for that.
This module have two methods,
- Pickling(dump): Convert Python objects into string representation.
- Unpickling(load): Retrieving original objects from stored string representstion.
https://docs.python.org/3.3/library/pickle.html
Code:
>>> import pickle
>>> l = [1,2,3,4]
>>> with open("test.txt", "wb") as fp: #Pickling
... pickle.dump(l, fp)
...
>>> with open("test.txt", "rb") as fp: # Unpickling
... b = pickle.load(fp)
...
>>> b
[1, 2, 3, 4]
Also Json
- dump/dumps: Serialize
- load/loads: Deserialize
https://docs.python.org/3/library/json.html
Code:
>>> import json
>>> with open("test.txt", "w") as fp:
... json.dump(l, fp)
...
>>> with open("test.txt", "r") as fp:
... b = json.load(fp)
...
>>> b
[1, 2, 3, 4]
Answer #2:
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")
score = []
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 #3:
Although the accepted answer works, you should really be using 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 human-readable
json.dump(score, f, indent=2)
with open("file.json", 'r') as f:
score = json.load(f)
print(score)
Advantages:
json
is a widely adopted and standardized data format, so non-python programs can easily read and understand the json filesjson
files are human-readable- Any nested or non-nested list/dictionary structure can be saved to a
json
file (as long as all the contents are serializable).
Disadvantages:
- The data is stored in plain-text (ie it’s uncompressed), which makes it a slow and bloated option for large amounts of data (ie probably a bad option for storing large numpy arrays, that’s what
hdf5
is for). - The contents of a list/dictionary need to be serializable before you can save it as a json, so while you can save things like strings, ints, and floats, you’ll need to write custom serialization and deserialization code to save objects, classes, and functions
When to use json
vs pickle
:
- If you want to store something you know you’re only ever going to use in the context of a python program, use
pickle
- If you need to save data that isn’t serializable by default (ie objects), save yourself the trouble and use
pickle
. - If you need a platform agnostic solution, use
json
- If you need to be able to inspect and edit the data directly, use
json
Common use cases:
- Configuration files (for example,
node.js
uses apackage.json
file to track project details, dependencies, scripts, etc …) - Most
REST
APIs usejson
to transmit and receive data - Data that requires a nested list/dictionary structure, or requires variable length lists/dicts
- Can be an alternative to
csv
,xml
oryaml
files
Answer #4:
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 #5:
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']
Answer #6:
pickle
and other serialization packages work. So does writing it to a .py
file that you can then import.
>>> score = [1,2,3,4,5]
>>>
>>> with open('file.py', 'w') as f:
... f.write('score = %s' % score)
...
>>> from file import score as my_list
>>> print(my_list)
[1, 2, 3, 4, 5]
Answer #7:
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 #8:
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.