# \u5b9a\u4e49\u53d8\u91cf<\/p>\na = 10 # \u6574\u6570<\/p>\n
b = 3.14 # \u6d6e\u70b9\u6570<\/p>\n
c = "Hello" # \u5b57\u7b26\u4e32<\/p>\n
d = [1, 2, 3] # \u5217\u8868<\/p>\n
e = (4, 5, 6) # \u5143\u7ec4<\/p>\n
f = {'key': 'value'} # \u5b57\u5178<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u63a7\u5236\u7ed3\u6784<\/h4>\n<\/p>\n
\u63a7\u5236\u7ed3\u6784\u5305\u62ec\u6761\u4ef6\u8bed\u53e5\u548c\u5faa\u73af\u8bed\u53e5\u3002\u5728Python\u4e2d\uff0c\u5e38\u7528\u7684\u63a7\u5236\u7ed3\u6784\u6709if\u8bed\u53e5\u3001for\u5faa\u73af\u548cwhile\u5faa\u73af\u3002<\/p>\n<\/p>\n
# \u6761\u4ef6\u8bed\u53e5<\/p>\nif a > b:<\/p>\n
print("a is greater than b")<\/p>\n
elif a == b:<\/p>\n
print("a is equal to b")<\/p>\n
else:<\/p>\n
print("a is less than b")<\/p>\n
for\u5faa\u73af<\/strong><\/h2>\nfor i in range(5):<\/p>\n
print(i)<\/p>\n
while\u5faa\u73af<\/strong><\/h2>\ncount = 0<\/p>\n
while count < 5:<\/p>\n
print(count)<\/p>\n
count += 1<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u51fd\u6570\u548c\u6a21\u5757<\/h4>\n<\/p>\n
\u51fd\u6570\u662f\u7ec4\u7ec7\u4ee3\u7801\u7684\u57fa\u672c\u5355\u5143\uff0c\u901a\u8fc7\u5b9a\u4e49\u51fd\u6570\u53ef\u4ee5\u63d0\u9ad8\u4ee3\u7801\u7684\u590d\u7528\u6027\u548c\u53ef\u8bfb\u6027\u3002Python\u8fd8\u652f\u6301\u5c06\u4ee3\u7801\u7ec4\u7ec7\u5230\u6a21\u5757\u4e2d\uff0c\u4ee5\u4fbf\u8fdb\u884c\u66f4\u597d\u7684\u7ba1\u7406\u548c\u7ef4\u62a4\u3002<\/p>\n<\/p>\n
# \u5b9a\u4e49\u51fd\u6570<\/p>\ndef add(x, y):<\/p>\n
return x + y<\/p>\n
\u8c03\u7528\u51fd\u6570<\/strong><\/h2>\nresult = add(3, 5)<\/p>\n
print(result)<\/p>\n
\u5bfc\u5165\u6a21\u5757<\/strong><\/h2>\nimport math<\/p>\n
print(math.sqrt(16))<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u5b66\u4e60\u9762\u5411\u5bf9\u8c61\u7f16\u7a0b<\/h3>\n<\/p>\n
\u9762\u5411\u5bf9\u8c61\u7f16\u7a0b\uff08OOP\uff09\u662fPython\u7f16\u7a0b\u7684\u4e00\u4e2a\u91cd\u8981\u6982\u5ff5\uff0c\u901a\u8fc7\u5b66\u4e60OOP\u53ef\u4ee5\u66f4\u597d\u5730\u7ec4\u7ec7\u548c\u7ba1\u7406\u4ee3\u7801\u3002<\/p>\n<\/p>\n
\u7c7b\u548c\u5bf9\u8c61<\/h4>\n<\/p>\n
\u5728Python\u4e2d\uff0c\u7c7b\u662f\u521b\u5efa\u5bf9\u8c61\u7684\u84dd\u56fe\uff0c\u901a\u8fc7\u5b9a\u4e49\u7c7b\u53ef\u4ee5\u521b\u5efa\u591a\u4e2a\u5b9e\u4f8b\u5bf9\u8c61\u3002<\/p>\n<\/p>\n
# \u5b9a\u4e49\u7c7b<\/p>\nclass Dog:<\/p>\n
def __init__(self, name, age):<\/p>\n
self.name = name<\/p>\n
self.age = age<\/p>\n
def bark(self):<\/p>\n
print(f"{self.name} is barking")<\/p>\n
\u521b\u5efa\u5bf9\u8c61<\/strong><\/h2>\ndog1 = Dog("Buddy", 3)<\/p>\n
dog2 = Dog("Lucy", 2)<\/p>\n
\u8c03\u7528\u65b9\u6cd5<\/strong><\/h2>\ndog1.bark()<\/p>\n
dog2.bark()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7ee7\u627f\u548c\u591a\u6001<\/h4>\n<\/p>\n
\u7ee7\u627f\u662fOOP\u7684\u91cd\u8981\u7279\u6027\uff0c\u901a\u8fc7\u7ee7\u627f\u53ef\u4ee5\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u7c7b\uff0c\u8be5\u7c7b\u7ee7\u627f\u4e86\u7236\u7c7b\u7684\u5c5e\u6027\u548c\u65b9\u6cd5\u3002\u591a\u6001\u662f\u6307\u4e0d\u540c\u5bf9\u8c61\u53ef\u4ee5\u8c03\u7528\u76f8\u540c\u7684\u65b9\u6cd5\uff0c\u5177\u4f53\u6267\u884c\u7684\u64cd\u4f5c\u53ef\u80fd\u4e0d\u540c\u3002<\/p>\n<\/p>\n
# \u5b9a\u4e49\u7236\u7c7b<\/p>\nclass Animal:<\/p>\n
def __init__(self, name):<\/p>\n
self.name = name<\/p>\n
def speak(self):<\/p>\n
raise NotImplementedError("Subclasses must implement this method")<\/p>\n
\u5b9a\u4e49\u5b50\u7c7b<\/strong><\/h2>\nclass Cat(Animal):<\/p>\n
def speak(self):<\/p>\n
return f"{self.name} says Meow"<\/p>\n
class Dog(Animal):<\/p>\n
def speak(self):<\/p>\n
return f"{self.name} says Woof"<\/p>\n
\u521b\u5efa\u5bf9\u8c61<\/strong><\/h2>\ncat = Cat("Whiskers")<\/p>\n
dog = Dog("Buddy")<\/p>\n
\u8c03\u7528\u65b9\u6cd5<\/strong><\/h2>\nprint(cat.speak())<\/p>\n
print(dog.speak())<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u4e86\u89e3\u5e38\u7528\u7684Python\u5e93<\/h3>\n<\/p>\n
Python\u62e5\u6709\u4e30\u5bcc\u7684\u7b2c\u4e09\u65b9\u5e93\uff0c\u53ef\u4ee5\u5e2e\u52a9\u7a0b\u5e8f\u5458\u5feb\u901f\u5b9e\u73b0\u5404\u79cd\u529f\u80fd\u3002\u4e86\u89e3\u548c\u638c\u63e1\u4e00\u4e9b\u5e38\u7528\u7684Python\u5e93\u662f\u975e\u5e38\u91cd\u8981\u7684\u3002<\/p>\n<\/p>\n
NumPy<\/h4>\n<\/p>\n
NumPy\u662f\u4e00\u4e2a\u7528\u4e8e\u79d1\u5b66\u8ba1\u7b97\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86\u591a\u7ef4\u6570\u7ec4\u5bf9\u8c61\u548c\u5404\u79cd\u6570\u5b66\u51fd\u6570\u3002\u5b83\u662f\u8bb8\u591a\u6570\u636e\u79d1\u5b66\u548c\u673a\u5668\u5b66\u4e60\u5e93\u7684\u57fa\u7840\u3002<\/p>\n<\/p>\n
import numpy as np<\/p>\n\u521b\u5efa\u6570\u7ec4<\/strong><\/h2>\narray = np.array([1, 2, 3, 4, 5])<\/p>\n
print(array)<\/p>\n
\u6570\u7ec4\u8fd0\u7b97<\/strong><\/h2>\nprint(array + 10)<\/p>\n
print(np.mean(array))<\/p>\n
print(np.sum(array))<\/p>\n
<\/code><\/pre>\n<\/p>\n
Pandas<\/h4>\n<\/p>\n
Pandas\u662f\u4e00\u4e2a\u7528\u4e8e\u6570\u636e\u64cd\u4f5c\u548c\u5206\u6790\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u636e\u7ed3\u6784\u548c\u6570\u636e\u5206\u6790\u5de5\u5177\u3002\u901a\u8fc7Pandas\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u6570\u636e\u6e05\u6d17\u3001\u5904\u7406\u548c\u5206\u6790\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n\u521b\u5efa\u6570\u636e\u6846<\/strong><\/h2>\ndata = {'Name': ['Tom', 'Jerry', 'Mickey'],<\/p>\n
'Age': [25, 30, 22]}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
print(df)<\/p>\n
\u6570\u636e\u64cd\u4f5c<\/strong><\/h2>\nprint(df['Age'].mean())<\/p>\n
print(df[df['Age'] > 25])<\/p>\n
<\/code><\/pre>\n<\/p>\n
Matplotlib<\/h4>\n<\/p>\n
Matplotlib\u662f\u4e00\u4e2a\u7528\u4e8e\u6570\u636e\u53ef\u89c6\u5316\u7684\u5e93\uff0c\u53ef\u4ee5\u751f\u6210\u5404\u79cd\u7c7b\u578b\u7684\u56fe\u8868\uff0c\u5982\u6298\u7ebf\u56fe\u3001\u67f1\u72b6\u56fe\u3001\u6563\u70b9\u56fe\u7b49\u3002\u901a\u8fc7Matplotlib\u53ef\u4ee5\u5c06\u6570\u636e\u4ee5\u76f4\u89c2\u7684\u65b9\u5f0f\u5c55\u793a\u51fa\u6765\u3002<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n\u521b\u5efa\u6570\u636e<\/strong><\/h2>\nx = [1, 2, 3, 4, 5]<\/p>\n
y = [2, 3, 5, 7, 11]<\/p>\n
\u7ed8\u5236\u6298\u7ebf\u56fe<\/strong><\/h2>\nplt.plot(x, y)<\/p>\n
plt.xlabel('X-axis')<\/p>\n
plt.ylabel('Y-axis')<\/p>\n
plt.title('Line Plot')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
Scikit-learn<\/h4>\n<\/p>\n
Scikit-learn\u662f\u4e00\u4e2a\u7528\u4e8e\u673a\u5668\u5b66\u4e60\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86\u5404\u79cd\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\u548c\u5de5\u5177\u3002\u901a\u8fc7Scikit-learn\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u6570\u636e\u9884\u5904\u7406\u3001\u6a21\u578b\u8bad\u7ec3\u548c\u8bc4\u4f30\u3002<\/p>\n<\/p>\n
from sklearn.datasets import load_iris<\/p>\nfrom sklearn.model_selection import train_test_split<\/p>\n
from sklearn.ensemble import RandomForestClassifier<\/p>\n
from sklearn.metrics import accuracy_score<\/p>\n
\u52a0\u8f7d\u6570\u636e\u96c6<\/strong><\/h2>\ndata = load_iris()<\/p>\n
X = data.data<\/p>\n
y = data.target<\/p>\n
\u62c6\u5206\u6570\u636e\u96c6<\/strong><\/h2>\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)<\/p>\n
\u8bad\u7ec3\u6a21\u578b<\/strong><\/h2>\nmodel = RandomForestClassifier()<\/p>\n
model.fit(X_train, y_train)<\/p>\n
\u9884\u6d4b<\/strong><\/h2>\ny_pred = model.predict(X_test)<\/p>\n
\u8bc4\u4f30\u6a21\u578b<\/strong><\/h2>\naccuracy = accuracy_score(y_test, y_pred)<\/p>\n
print(f"Accuracy: {accuracy}")<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u638c\u63e1\u8c03\u8bd5\u6280\u5de7<\/h3>\n<\/p>\n
\u8c03\u8bd5\u662f\u7f16\u7a0b\u8fc7\u7a0b\u4e2d\u4e0d\u53ef\u907f\u514d\u7684\u4e00\u90e8\u5206\uff0c\u638c\u63e1\u8c03\u8bd5\u6280\u5de7\u53ef\u4ee5\u5e2e\u52a9\u7a0b\u5e8f\u5458\u5feb\u901f\u5b9a\u4f4d\u548c\u4fee\u590d\u4ee3\u7801\u4e2d\u7684\u95ee\u9898\u3002<\/p>\n<\/p>\n
\u4f7f\u7528print()\u8c03\u8bd5<\/h4>\n<\/p>\n
\u5728Python\u4e2d\uff0c\u6700\u7b80\u5355\u7684\u8c03\u8bd5\u65b9\u6cd5\u662f\u4f7f\u7528print()\u51fd\u6570\u6253\u5370\u53d8\u91cf\u7684\u503c\u548c\u7a0b\u5e8f\u7684\u6267\u884c\u72b6\u6001\u3002\u8fd9\u79cd\u65b9\u6cd5\u867d\u7136\u7b80\u5355\uff0c\u4f46\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\u975e\u5e38\u6709\u6548\u3002<\/p>\n<\/p>\n
def add(x, y):<\/p>\n result = x + y<\/p>\n
print(f"Adding {x} and {y} gives {result}")<\/p>\n
return result<\/p>\n
add(3, 5)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4f7f\u7528\u65ad\u70b9\u8c03\u8bd5<\/h4>\n<\/p>\n
\u5927\u591a\u6570IDE\u90fd\u63d0\u4f9b\u4e86\u65ad\u70b9\u8c03\u8bd5\u529f\u80fd\uff0c\u7a0b\u5e8f\u5458\u53ef\u4ee5\u5728\u4ee3\u7801\u4e2d\u8bbe\u7f6e\u65ad\u70b9\uff0c\u7a0b\u5e8f\u6267\u884c\u5230\u65ad\u70b9\u65f6\u4f1a\u6682\u505c\uff0c\u5141\u8bb8\u7a0b\u5e8f\u5458\u68c0\u67e5\u53d8\u91cf\u7684\u503c\u548c\u7a0b\u5e8f\u7684\u6267\u884c\u72b6\u6001\u3002\u901a\u8fc7\u8fd9\u79cd\u65b9\u6cd5\uff0c\u53ef\u4ee5\u66f4\u7ec6\u81f4\u5730\u8c03\u8bd5\u4ee3\u7801\u3002<\/p>\n<\/p>\n
\u4f7f\u7528\u8c03\u8bd5\u5668<\/h4>\n<\/p>\n
Python\u5185\u7f6e\u4e86\u4e00\u4e2a\u8c03\u8bd5\u5668\uff0c\u79f0\u4e3apdb\u3002\u901a\u8fc7\u5728\u4ee3\u7801\u4e2d\u63d2\u5165import pdb; pdb.set_trace()<\/code>\uff0c\u7a0b\u5e8f\u6267\u884c\u5230\u8be5\u884c\u65f6\u4f1a\u8fdb\u5165\u8c03\u8bd5\u6a21\u5f0f\uff0c\u7a0b\u5e8f\u5458\u53ef\u4ee5\u901a\u8fc7\u8c03\u8bd5\u5668\u547d\u4ee4\u9010\u6b65\u6267\u884c\u4ee3\u7801\u3002<\/p>\n<\/p>\ndef add(x, y):<\/p>\n import pdb; pdb.set_trace()<\/p>\n
result = x + y<\/p>\n
return result<\/p>\n
add(3, 5)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u53c2\u4e0e\u5f00\u6e90\u9879\u76ee<\/h3>\n<\/p>\n
\u53c2\u4e0e\u5f00\u6e90\u9879\u76ee\u662f\u63d0\u9ad8\u7f16\u7a0b\u6280\u80fd\u548c\u79ef\u7d2f\u5b9e\u9645\u7ecf\u9a8c\u7684\u4e00\u4e2a\u91cd\u8981\u9014\u5f84\u3002\u901a\u8fc7\u53c2\u4e0e\u5f00\u6e90\u9879\u76ee\uff0c\u53ef\u4ee5\u63a5\u89e6\u5230\u66f4\u591a\u7684\u5b9e\u9645\u95ee\u9898\u548c\u89e3\u51b3\u65b9\u6848\uff0c\u540c\u65f6\u4e5f\u53ef\u4ee5\u4e0e\u5176\u4ed6\u5f00\u53d1\u8005\u4ea4\u6d41\u548c\u5408\u4f5c\u3002<\/p>\n<\/p>\n
\u5bfb\u627e\u5f00\u6e90\u9879\u76ee<\/h4>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7GitHub\u3001GitLab\u7b49\u5e73\u53f0\u5bfb\u627e\u611f\u5174\u8da3\u7684\u5f00\u6e90\u9879\u76ee\uff0c\u4e86\u89e3\u9879\u76ee\u7684\u80cc\u666f\u548c\u9700\u6c42\uff0c\u9009\u62e9\u9002\u5408\u81ea\u5df1\u7684\u4efb\u52a1\u3002<\/p>\n<\/p>\n
\u63d0\u4ea4\u4ee3\u7801<\/h4>\n<\/p>\n
\u5728\u53c2\u4e0e\u5f00\u6e90\u9879\u76ee\u7684\u8fc7\u7a0b\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u63d0\u4ea4\u4ee3\u7801\u8d21\u732e\u81ea\u5df1\u7684\u529b\u91cf\u3002\u5728\u63d0\u4ea4\u4ee3\u7801\u4e4b\u524d\uff0c\u9700\u8981\u4ed4\u7ec6\u9605\u8bfb\u9879\u76ee\u7684\u8d21\u732e\u6307\u5357\uff0c\u6309\u7167\u89c4\u8303\u8fdb\u884c\u4ee3\u7801\u7f16\u5199\u548c\u63d0\u4ea4\u3002<\/p>\n<\/p>\n
\u53c2\u4e0e\u8ba8\u8bba<\/h4>\n<\/p>\n
\u901a\u8fc7\u53c2\u4e0e\u9879\u76ee\u7684\u8ba8\u8bba\uff0c\u53ef\u4ee5\u4e86\u89e3\u9879\u76ee\u7684\u8fdb\u5c55\u548c\u95ee\u9898\uff0c\u63d0\u51fa\u81ea\u5df1\u7684\u610f\u89c1\u548c\u5efa\u8bae\u3002\u901a\u8fc7\u4e0e\u5176\u4ed6\u5f00\u53d1\u8005\u7684\u4ea4\u6d41\uff0c\u53ef\u4ee5\u5b66\u4e60\u5230\u66f4\u591a\u7684\u7f16\u7a0b\u6280\u5de7\u548c\u7ecf\u9a8c\u3002<\/p>\n<\/p>\n
\u4e03\u3001\u4e0d\u65ad\u7f16\u5199\u548c\u4f18\u5316\u4ee3\u7801<\/h3>\n<\/p>\n
\u7f16\u5199\u4ee3\u7801\u662f\u63d0\u9ad8\u7f16\u7a0b\u6280\u80fd\u7684\u6700\u6709\u6548\u65b9\u6cd5\uff0c\u901a\u8fc7\u4e0d\u65ad\u7f16\u5199\u548c\u4f18\u5316\u4ee3\u7801\uff0c\u53ef\u4ee5\u79ef\u7d2f\u66f4\u591a\u7684\u7ecf\u9a8c\u548c\u6280\u5de7\u3002<\/p>\n<\/p>\n
\u7f16\u5199\u5c0f\u9879\u76ee<\/h4>\n<\/p>\n
\u901a\u8fc7\u7f16\u5199\u5c0f\u9879\u76ee\uff0c\u53ef\u4ee5\u5b9e\u8df5\u6240\u5b66\u7684\u77e5\u8bc6\uff0c\u5e76\u9010\u6b65\u63d0\u9ad8\u7f16\u7a0b\u6280\u80fd\u3002\u53ef\u4ee5\u9009\u62e9\u4e00\u4e9b\u611f\u5174\u8da3\u7684\u4e3b\u9898\uff0c\u5982\u6570\u636e\u5206\u6790\u3001\u7f51\u9875\u5f00\u53d1\u3001\u81ea\u52a8\u5316\u811a\u672c\u7b49\uff0c\u7f16\u5199\u5c0f\u9879\u76ee\u8fdb\u884c\u7ec3\u4e60\u3002<\/p>\n<\/p>\n
\u4ee3\u7801\u8bc4\u5ba1<\/h4>\n<\/p>\n
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