python – How to save a list to a file and read it as a list type?

python – How to save a list to a file and read it as a list type?

You can use the pickle module for that.
This module has two methods,

1. Pickling(dump): Convert Python objects into a string representation.
2. Unpickling(load): Retrieving original objects from a stored string representation.

https://docs.python.org/3.3/library/pickle.html

Code:

>>> import pickle
>>> l = [1,2,3,4]
>>> with open(test, wb) as fp:   #Pickling
...   pickle.dump(l, fp)
... 
>>> with open(test, rb) as fp:   # Unpickling
...   b = pickle.load(fp)
... 
>>> b
[1, 2, 3, 4]

---

Also Json

1. dump/dumps: Serialize
2. load/loads: Deserialize

https://docs.python.org/3/library/json.html

Code:

>>> import json
>>> with open(test, w) as fp:
...     json.dump(l, fp)
...
>>> with open(test, r) as fp:
...     b = json.load(fp)
...
>>> b
[1, 2, 3, 4]

I decided I didnt 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.

python – How to save a list to a file and read it as a list type?

Although the accepted answer works, you should really be using pythons 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:

1. json is a widely adopted and standardized data format, so non-python programs can easily read and understand the json files
2. json files are human-readable
3. Any nested or non-nested list/dictionary structure can be saved to a json file (as long as all the contents are serializable).

Disadvantages:

1. The data is stored in plain-text (ie its uncompressed), which makes it a slow and bloated option for large amounts of data (ie probably a bad option for storing large numpy arrays, thats what hdf5 is for).
2. 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, youll need to write custom serialization and deserialization code to save objects, classes, and functions

Which one should I use?:

• If you want to store something you know youre only ever going to use in the context of a python program, use pickle
• If you need to save data that isnt 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 of json:

• Configuration files (for example, node.js uses a package.json file to track project details, dependencies, scripts, etc …)
• Most REST APIs use json 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 or yaml files