Generaattoreiden Käytännön Sovellukset: Tosielämän Käyttötapaukset

              
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from contextlib import contextmanager

@contextmanager
def database_connection():
    print("Opening database connection")
    connection = "Database Connection"  # Simulated connection
    try:
        yield connection
    finally:
        print("Closing database connection")

# Using the generator as a context manager
with database_connection() as conn:
    print(f"Using {conn}")

              
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import re

# Stage 1: Read lines lazily
def read_lines(text):
    for line in text.split("\n"):
        yield line

# Stage 2: Filter non-empty lines
def filter_lines(lines):
    for line in lines:
        if line.strip():
            yield line

# Stage 3: Extract words lazily
def extract_words(lines):
    for line in lines:
        for word in re.findall(r'\w+', line):
            yield word

# Stage 4: Transform words to lowercase
def lowercase_words(words):
    for word in words:
        yield word.lower()

# Input text
text = """Generators are powerful tools
They allow efficient data processing
This pipeline demonstrates their usage"""

# Build the pipeline
lines = read_lines(text)
filtered = filter_lines(lines)
words = extract_words(filtered)
lowercased = lowercase_words(words)

# Process the data
print("Processed words:")
for word in lowercased:
    print(word)