AI-Learning

t = ("a", "b", "c")
print("b" in t)

import json
json_data = '{"items": [10, 20, 30]}'
data = json.loads(json_data)
print(data["items"][1])

import sys
args = sys.argv[1:]
if "debug" in args:
print("Debug mode enabled")
else:
print("Normal mode")

実行コマンド：python script.py debug

class MyClass:
class_variable = "shared"

obj = MyClass()
print(obj.class_variable)

x = 1

def first_function():
global x
x += 1

def second_function():
global x
x *= 3

first_function()
second_function()
print(x)

def format_text(text, prefix="*", suffix="*"):
return prefix + text + suffix

print(format_text("Hello"))
print(format_text("Hello", prefix="~"))
print(format_text("Hello", suffix="?"))

set1 = {1, 2, 3}
set2 = {3, 4, 5}
set1.update(set2)
print(set1)

my_set = {1, 2, 3}
my_set.clear()
print(my_set)

from collections import deque
dq = deque(maxlen=5)
dq.extend([1, 2, 3])
dq.extendleft([4, 5])
print(dq)

items = [(2, "b"), (3, "c"), (1, "a")]
sorted_items = sorted(items)
print(sorted_items)

class Parent:
def __init__(self, value):
self.value = value

class Child(Parent):
def __init__(self, value):
super().__init__(value)
self.value *= 2

obj = Child(5)
print(obj.value)

class Parent:
def __init__(self):
self.data = [1, 2, 3]

class Child(Parent):
def __init__(self):
super().__init__()
self.data.append(4)

obj = Child()
print(obj.data)

$ python -m venv testenv
$ source testenv/bin/activate
$ pip list

class Parent:
def greet(self):
return "Hello from Parent!"

class Child(Parent):
def greet(self):
return "Hello from Child!"

obj = Child()
print(obj.greet())

class Parent:
def __init__(self):
self.name = "Parent"

class Child(Parent):
def __init__(self):
super().__init__()
self.age = 10

obj = Child()
print(obj.name, obj.age)

def calculate_area(width, height=2):
return width * height

print(calculate_area(4))
print(calculate_area(4, 3))

import sys
args = sys.argv[1:]
result = sum(int(arg) for arg in args if arg.isdigit())
print(f"Sum of numbers: {result}")

実行コマンド：python script.py 1 2 three 4

t = (1, 2, 3, 4, 5)
print(t[-2])

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("-v", "--verbose", action="store_true", help="Enable verbose mode")
args = parser.parse_args()
print(f"Verbose: {args.verbose}")

実行コマンド：python script.py -v

x = [1, 2, 3

with open('sample.txt', 'w') as f:
f.write("Hello, World!\n")
f.write("Python Programming")

set1 = {1, 2, 3}
set2 = {2, 3, 4}
result = set1.symmetric_difference_update(set2)
print(set1, result)

import sys
print(sys.argv)

実行コマンド：python script.py input.txt output.txt

score = 85
result = "優秀" if score >= 90 else "合格" if score >= 60 else "不合格"
print(result)

lst = [1, 2, 3, 4]
x = lst.pop(2)
print(x, lst)

t = (1, [2, 3], 4)
t[1].append(5)
print(t)

try:
raise NameError("Variable not defined")
except ValueError as e:
print("Caught ValueError:", e)
except NameError as e:
print("Caught NameError:", e)

import json
data = '{"name": "Charlie", "age": 35, "city": "Kyoto"}'
parsed_data = json.loads(data)
print(parsed_data["city"])

def greet_many(times, name="Guest"):
return (f"Hello, {name}!" * times).strip()

print(greet_many(2))
print(greet_many(3, "Alice"))

x = 1

def outer_function():
def inner_function():
global x
x += 1
inner_function()

outer_function()
print(x)

import statistics
data = [1, 2, 3, 4, 5, 6, 7, 8]
variance = statistics.variance(data)
print(round(variance, 2))

stack = [1, 2, 3]
for _ in range(2):
stack.append(stack[-1] + stack[-2])
stack.pop()

import glob
result = glob.glob("file??.txt")

# ファイル名: sample.txt
# 初期内容:
# ---
# Python is great!
# ---
with open('sample.txt', 'r+') as f:
f.seek(10)
f.write("amazing")
f.seek(0)
print(f.read())

a = 3
b = 8
if a < 5 and b > 10:
print("条件1が成立")
elif a < 5 or b > 5:
print("条件2が成立")
else:
print("どちらも成立しません")