Class 12 Text, Binary and CSV Files: Complete Concepts and Practice

Big picture

Variables lose their values when a program ends. Files store data permanently on disk so it can be used later. Python works with three kinds of files in the syllabus: text files (human-readable characters), binary files (data in the same format as in memory, used here to store Python objects with pickle) and CSV files (tables of comma-separated values that spreadsheets can open).

Every board paper has a file-handling program to write: count words or lines in a text file, search or update records in a binary file, or read and write a CSV file. This lesson gives the methods and the standard programs, all tested.

Learning goals

• Distinguish text, binary and CSV files, and absolute and relative paths.

• Open files in the correct mode and close them, using with.

• Read and write text files using read(), readline(), readlines(), write() and writelines().

• Use seek() and tell().

• Write programs that count characters, words, lines and specific items in text files.

• Store and retrieve records in binary files using pickle, including search and update.

• Read and write CSV files using the csv module.

Core ideas

1. Types of files and paths

• Absolute path: the full path from the root, e.g. C:\Users\Asha\data\marks.txt.

• Relative path: relative to the current working directory, e.g. data\marks.txt or ..\notes.txt.

2. Opening and closing files

file_object = open('filename', 'mode'). After use, file_object.close() saves pending data and frees the file.

Add 'b' for binary files: 'rb', 'wb', 'ab', 'rb+' and so on.

The `with` statement closes the file automatically, even if an error occurs:

with open('poem.txt', 'w') as f:
    f.write('The sun is bright\nThe sky is blue\nWe love to learn\n')

3. Reading text files

Using the file written above (tested):

with open('poem.txt') as f:
    print(repr(f.read(7)))      # 'The sun'
    print(repr(f.readline()))   # ' is bright\n'  (rest of the first line)
    print(f.tell())             # 18

with open('poem.txt') as f:
    lines = f.readlines()
    print(len(lines))           # 3
    print(repr(lines[1]))       # 'The sky is blue\n'

A file object can also be looped over line by line: for line in f:.

4. Writing text files

• write(string) writes a string (you must add \n yourself) and returns the number of characters written.

• writelines(list_of_strings) writes all strings in a list; it doesn't add newlines.

• Numbers must be converted to strings first: f.write(str(25)).

5. seek() and tell()

• tell() returns the current position of the file pointer (in bytes from the start).

• seek(offset) moves the pointer to the given position. seek(0) goes back to the start.

with open('poem.txt') as f:
    f.seek(4)
    print(f.read(3))   # sun

6. Standard text-file programs

Count words, vowels and lines starting with a word (tested on poem.txt):

with open('poem.txt') as f:
    data = f.read()
print(len(data.split()))                                   # 12 words
print(sum(1 for c in data if c.lower() in 'aeiou'))        # 14 vowels

count = 0
with open('poem.txt') as f:
    for line in f:
        if line.startswith('The'):
            count += 1
print(count)                                               # 2

Other common tasks: count a particular word (data.split().count('the')), display lines longer than a given length, copy lines that contain a character into another file, and count uppercase letters (c.isupper()).

Appending: after open('poem.txt', 'a') and writing 'Done\n', the file has 4 lines; opening it with 'w' instead would have erased the original three.

7. Binary files with pickle

The pickle module converts Python objects (lists, dictionaries) to a byte stream (pickling or serialisation) and back (unpickling or deserialisation).

• pickle.dump(obj, file) writes an object to a binary file opened in 'wb' or 'ab'.

• pickle.load(file) reads the next object; it raises `EOFError` at the end of the file, which is used to stop reading.

Write and search records (tested):

import pickle

records = [{'roll': 1, 'name': 'Asha', 'marks': 88},
           {'roll': 2, 'name': 'Ravi', 'marks': 72}]
with open('stu.dat', 'wb') as f:
    for r in records:
        pickle.dump(r, f)

with open('stu.dat', 'rb') as f:
    try:
        while True:
            r = pickle.load(f)
            if r['marks'] > 80:
                print(r['name'])     # Asha
    except EOFError:
        pass

Updating a record: read all records into a list, change the required one, and write the whole list back in 'wb' mode. (Alternatively, open in 'rb+', remember the position with tell() before each load, then seek() back and dump() the modified record.)

8. CSV files with the csv module

• Open a CSV file for writing with newline='', so that blank lines don't appear between rows on some systems.

• csv.writer(f) creates a writer; writerow(list) writes one row; writerows(list_of_lists) writes many.

• csv.reader(f) returns rows as lists of strings; convert numbers with int() or float(). next(reader) skips the header row.

Write and read (tested):

import csv

with open('emp.csv', 'w', newline='') as f:
    w = csv.writer(f)
    w.writerow(['id', 'name', 'salary'])
    w.writerows([[1, 'Neha', 50000], [2, 'Arun', 42000]])

with open('emp.csv') as f:
    r = csv.reader(f)
    next(r)                          # skip header
    for row in r:
        if int(row[2]) > 45000:
            print(row[1])            # Neha

The file contains plain text: id,name,salary, then 1,Neha,50000, then 2,Arun,42000.

9. Text, binary and CSV files compared

A reliable routine for file programs

1. Choose the file type and mode: 'r' to read, 'w' to create or overwrite, 'a' to add; add 'b' for pickle.

2. Use with open(...) as f: so the file closes automatically.

3. For text files, decide whether to read the whole file, line by line, or word by word with split().

4. For binary files, loop on pickle.load() inside try and stop at EOFError.

5. For CSV files, use newline='' when writing, skip the header with next(), and convert strings to numbers.

Connections that matter

• Exception handling handles FileNotFoundError and EOFError.

• Advanced Python revision: string methods like split(), startswith() and isupper() are used in text processing.

• Python–SQL connectivity is another way of storing data permanently.

Common mistakes

• Opening an existing file in `'w'` mode by mistake, which erases it.

• Forgetting `\n` with `write()`, so all lines run together.

• Using `pickle` with a file opened in text mode. Use 'rb' or 'wb'.

• Not handling `EOFError` when reading pickled records in a loop.

• Comparing CSV values as numbers without converting them. csv.reader returns strings.

Revision checklist

• I can distinguish text, binary and CSV files and absolute and relative paths.

• I can choose the right file mode and use with.

• I can use every read and write method and seek()/tell().

• I can write programs to count words, lines, vowels and specific items.

• I can write, search and update records with pickle.

• I can read and write CSV files with the csv module.