Chapter 8: File Operations and JSON

1. Why files matter

Programs live in RAM, but real-world data lives on disk. Reading and writing files lets your code remember things after it stops running.

2. Opening a file safely

What you write	What it means	Typical use
`open("example.txt", "r")`	read-only	When you only want to look
`open("example.txt", "w")`	write (erase & start fresh)	When you’re replacing everything
`open("example.txt", "a")`	append	When you want to add to the end

Pro tip: Use a context manager so Python closes the file for you—even if something goes wrong.

with open("example.txt", "r") as file:
    content = file.read()

3. Reading from a file

Method	Result	Good for
`read()`	The whole file as one big string	Small files
`readline()`	One line each time you call it	Stepping through line by line
`readlines()`	A list where each item is a line	Quick “grab-all” into memory

Example:

with open("poem.txt") as f:
    first_line = f.readline()
    all_lines  = f.readlines()

4. Writing to a file

Anything you write() must be a string.

with open("log.txt", "w") as f:
    f.write("Hello\n")
    f.write("World\n")

Need multiple lines? End each one with \n.

Writing structured data yourself

info = {"name": "Ana", "age": 25}
with open("person.txt", "w") as f:
    for key, val in info.items():
        f.write(f"{key}: {val}\n")

Reading it back means splitting each line at ": ".

5. JSON—the universal data suitcase

JSON (JavaScript Object Notation) stores dictionaries, lists, strings, numbers, booleans, and null. Almost every language understands it.

Main functions from the `json` module

Function	Direction	Memory vs. Disk
`json.dumps(py_obj)`	Python ➜ string	Memory
`json.loads(json_str)`	string ➜ Python	Memory
`json.dump(py_obj, file)`	Python ➜ file	Disk
`json.load(file)`	file ➜ Python	Disk

Example round-trip:

import json
data = {"city": "Toronto", "temp": 18}

json_string = json.dumps(data)   # to text
parsed = json.loads(json_string) # back to dict

with open("weather.json", "w") as f:
    json.dump(data, f)

with open("weather.json") as f:
    from_disk = json.load(f)

6. Guarding against errors (Exception Handling)

try:
    n = int(input("Number: "))
    print(10 / n)
except ValueError:
    print("Not a number.")
except ZeroDivisionError:
    print("Can't divide by zero.")
except Exception as e:          # catches anything else
    print("Something went wrong →", e)

Flow:

Try something risky.
If Python raises a matching except block, run that block.
Program keeps going instead of crashing.

7. Cleaning text with `strip()` & `rstrip()`

Method	Removes	From where
`strip()`	blanks or given chars	both ends
`rstrip()`	blanks or given chars	right end only

s = "   Hi!  "
s.strip()   # 'Hi!'

dots = "...hello..."
dots.strip(".")   # 'hello'

Common use: trim line endings from files:

for raw in open("names.txt"):
    name = raw.strip()

8. Quick recap

Files need a mode: "r", "w", or "a".
Read with read(), readline(), or readlines().
Always close files—or simpler—use with.
JSON is the go-to for saving dictionaries/lists.
Handle mistakes gracefully with try / except.
strip() and friends tidy up messy strings.

9. Practice prompts

Write a program that appends today’s date to journal.txt each time it runs.
Convert a list of Python dictionaries (contacts) into contacts.json, then read it back and print each name.
Ask the user for a filename, open it safely, and count how many non-empty lines it contains, handling “file not found” errors politely.

Data Structures and Object-Oriented Programming