File Handling — Part 2: Binary Files and CSV Files: visual lesson, CBSE Class 12 Computer Science

Lesson

Binary Files and CSV Files

Part 2 — storing Python objects with pickle, and tables in CSV files.

In this lesson you will

Store and read Python objects in binary files with pickle.dump() and pickle.load()
Read a binary file to the end by handling EOFError, and search and update its records
Write and read CSV files with csv.writer and csv.reader

Part 2 at a glance

Concept

Binary files and pickle

A record such as [101, "Desert Sky", 240] can be stored as it is in a binary file.

Table of pickle terms: pickling or serialisation turns an object into bytes with dump, unpickling or deserialisation turns bytes back into an object with load, and binary modes such as wb, rb and ab are used
Term	Meaning	Function
Pickling (serialisation)	Python object → byte stream	`pickle.dump(obj, f)`
Unpickling (deserialisation)	byte stream → Python object	`obj = pickle.load(f)`
Binary modes	bytes, not characters	`"wb"`, `"rb"`, `"ab"`, `"rb+"`

Diagram

From object to bytes and back

Each dump() writes one object; each load() reads the next one.

import pickle
with open("books.dat", "wb") as f:
    pickle.dump([101, "Desert Sky", 240], f)
    pickle.dump([102, "Paper Boats", 180], f)
with open("books.dat", "rb") as f:
    print(pickle.load(f))
    print(pickle.load(f)[1])

Output:

[101, 'Desert Sky', 240]
Paper Boats

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