Fortgeschrittene Sortiertechniken
Nachdem wir die Grundlagen verstanden haben, wollen wir uns mit fortgeschritteneren Sortiertechniken unter Verwendung von Lambda-Funktionen befassen.
Sortieren von Dictionaries
Dictionaries sind eine gängige Datenstruktur in Python, und wir müssen oft Listen von Dictionaries sortieren. Erstellen Sie eine Datei namens sorting_dictionaries.py:
## Sorting lists of dictionaries
products = [
{"name": "Laptop", "price": 999.99, "stock": 25},
{"name": "Phone", "price": 499.50, "stock": 42},
{"name": "Tablet", "price": 299.75, "stock": 15},
{"name": "Headphones", "price": 149.99, "stock": 34},
{"name": "Mouse", "price": 24.99, "stock": 55}
]
## Print original products
print("Original product list:")
for product in products:
print(f" {product['name']}: ${product['price']}, Stock: {product['stock']}")
## Sort by price (lowest to highest)
by_price = sorted(products, key=lambda product: product["price"])
print("\nSorted by price (lowest to highest):")
for product in by_price:
print(f" {product['name']}: ${product['price']}, Stock: {product['stock']}")
## Sort by stock (highest to lowest)
by_stock = sorted(products, key=lambda product: product["stock"], reverse=True)
print("\nSorted by stock (highest to lowest):")
for product in by_stock:
print(f" {product['name']}: ${product['price']}, Stock: {product['stock']}")
## Sort by name (alphabetically)
by_name = sorted(products, key=lambda product: product["name"])
print("\nSorted by name:")
for product in by_name:
print(f" {product['name']}: ${product['price']}, Stock: {product['stock']}")
Führen Sie diese Datei aus:
python3 sorting_dictionaries.py
Sie sollten die Produkte auf verschiedene Arten sortiert sehen:
Original product list:
Laptop: $999.99, Stock: 25
Phone: $499.5, Stock: 42
Tablet: $299.75, Stock: 15
Headphones: $149.99, Stock: 34
Mouse: $24.99, Stock: 55
Sorted by price (lowest to highest):
Mouse: $24.99, Stock: 55
Headphones: $149.99, Stock: 34
Tablet: $299.75, Stock: 15
Phone: $499.5, Stock: 42
Laptop: $999.99, Stock: 25
Sorted by stock (highest to lowest):
Mouse: $24.99, Stock: 55
Phone: $499.5, Stock: 42
Headphones: $149.99, Stock: 34
Laptop: $999.99, Stock: 25
Tablet: $299.75, Stock: 15
Sorted by name:
Headphones: $149.99, Stock: 34
Laptop: $999.99, Stock: 25
Mouse: $24.99, Stock: 55
Phone: $499.5, Stock: 42
Tablet: $299.75, Stock: 15
Multi-Level-Sortierung
Manchmal müssen wir Elemente anhand mehrerer Kriterien sortieren. Zum Beispiel möchten wir Studenten zuerst nach Note und dann nach Alter für diejenigen mit derselben Note sortieren.
Erstellen Sie eine Datei namens multi_level_sorting.py:
## Multi-level sorting example
students = [
{"name": "Alice", "grade": "A", "age": 21},
{"name": "Bob", "grade": "B", "age": 19},
{"name": "Charlie", "grade": "A", "age": 22},
{"name": "David", "grade": "C", "age": 20},
{"name": "Eve", "grade": "B", "age": 18},
{"name": "Frank", "grade": "A", "age": 19}
]
print("Original student list:")
for student in students:
print(f" {student['name']}: Grade {student['grade']}, Age {student['age']}")
## Sort by grade (A to C), then by age (youngest to oldest)
## To sort by grade, we create a dictionary for grade priorities
grade_priority = {"A": 1, "B": 2, "C": 3} ## A is highest priority (lowest number)
by_grade_then_age = sorted(students,
key=lambda student: (grade_priority[student["grade"]], student["age"]))
print("\nSorted by grade (A first), then by age (youngest first):")
for student in by_grade_then_age:
print(f" {student['name']}: Grade {student['grade']}, Age {student['age']}")
## Sort by age (oldest to youngest), then by name (alphabetically)
by_age_then_name = sorted(students,
key=lambda student: (-student["age"], student["name"]))
print("\nSorted by age (oldest first), then by name:")
for student in by_age_then_name:
print(f" {student['name']}: Grade {student['grade']}, Age {student['age']}")
Führen Sie diese Datei aus:
python3 multi_level_sorting.py
Sie sollten Folgendes sehen:
Original student list:
Alice: Grade A, Age 21
Bob: Grade B, Age 19
Charlie: Grade A, Age 22
David: Grade C, Age 20
Eve: Grade B, Age 18
Frank: Grade A, Age 19
Sorted by grade (A first), then by age (youngest first):
Frank: Grade A, Age 19
Alice: Grade A, Age 21
Charlie: Grade A, Age 22
Eve: Grade B, Age 18
Bob: Grade B, Age 19
David: Grade C, Age 20
Sorted by age (oldest first), then by name:
Charlie: Grade A, Age 22
Alice: Grade A, Age 21
David: Grade C, Age 20
Bob: Grade B, Age 19
Frank: Grade A, Age 19
Eve: Grade B, Age 18
Beachten Sie, wie wir Tupel innerhalb der Lambda-Funktion verwendet haben, um mehrere Sortierkriterien zu definieren. Das erste Element im Tupel ist der primäre Sortierschlüssel, und nachfolgende Elemente werden für die Auflösung von Gleichständen verwendet.
Wir haben ein Minuszeichen -student["age"] verwendet, um nach Alter in absteigender Reihenfolge zu sortieren. Diese Technik ist nützlich, wenn Sie numerisch in umgekehrter Reihenfolge sortieren möchten.
Sortieren von benutzerdefinierten Objekten
Lassen Sie uns ein letztes Beispiel erstellen, um zu zeigen, wie man benutzerdefinierte Klassenobjekte sortiert. Erstellen Sie eine Datei namens sorting_objects.py:
## Sorting objects of a custom class
class Person:
def __init__(self, name, age, height):
self.name = name
self.age = age
self.height = height ## in cm
def __repr__(self):
return f"Person(name='{self.name}', age={self.age}, height={self.height}cm)"
## Create a list of Person objects
people = [
Person("Alice", 25, 165),
Person("Bob", 30, 180),
Person("Charlie", 22, 175),
Person("David", 35, 170),
Person("Eve", 28, 160)
]
print("Original list of people:")
for person in people:
print(f" {person}")
## Sort by age
by_age = sorted(people, key=lambda person: person.age)
print("\nSorted by age:")
for person in by_age:
print(f" {person}")
## Sort by height
by_height = sorted(people, key=lambda person: person.height)
print("\nSorted by height:")
for person in by_height:
print(f" {person}")
## Sort by name length, then by age
by_name_length_then_age = sorted(people, key=lambda person: (len(person.name), person.age))
print("\nSorted by name length, then by age:")
for person in by_name_length_then_age:
print(f" {person}")
Führen Sie diese Datei aus:
python3 sorting_objects.py
Sie sollten Folgendes sehen:
Original list of people:
Person(name='Alice', age=25, height=165cm)
Person(name='Bob', age=30, height=180cm)
Person(name='Charlie', age=22, height=175cm)
Person(name='David', age=35, height=170cm)
Person(name='Eve', age=28, height=160cm)
Sorted by age:
Person(name='Charlie', age=22, height=175cm)
Person(name='Alice', age=25, height=165cm)
Person(name='Eve', age=28, height=160cm)
Person(name='Bob', age=30, height=180cm)
Person(name='David', age=35, height=170cm)
Sorted by height:
Person(name='Eve', age=28, height=160cm)
Person(name='Alice', age=25, height=165cm)
Person(name='David', age=35, height=170cm)
Person(name='Charlie', age=22, height=175cm)
Person(name='Bob', age=30, height=180cm)
Sorted by name length, then by age:
Person(name='Bob', age=30, height=180cm)
Person(name='Eve', age=28, height=160cm)
Person(name='Alice', age=25, height=165cm)
Person(name='David', age=35, height=170cm)
Person(name='Charlie', age=22, height=175cm)
Dieses Beispiel zeigt, wie Lambda-Funktionen verwendet werden können, um benutzerdefinierte Objekte zu sortieren, indem direkt auf ihre Attribute zugegriffen wird.
