Python在移动开发中的应用：自动化、AI与ML

# 自动调整应用截图的脚本
import os
from PIL import Image

def resize_screenshots(input_dir: str, output_dir: str, size: tuple) -> None:
    """将所有PNG截图调整为所需的商店尺寸。"""
    for filename in os.listdir(input_dir):
        if not filename.lower().endswith(".png"):
            continue
        path = os.path.join(input_dir, filename)
        img = Image.open(path)
        resized = img.resize(size, Image.LANCZOS)
        out_path = os.path.join(output_dir, filename)
        resized.save(out_path, "PNG")
        print(f"Resized {filename} -> {out_path}")

resize_screenshots("screenshots_raw", "screenshots_resized", (1242, 2208))

# 从CSV翻译文件生成strings.xml
import csv
from xml.etree import ElementTree as ET
from xml.dom import minidom

def csv_to_strings(csv_path: str, lang: str) -> str:
    root = ET.Element("resources")
    with open(csv_path, "r") as f:
        reader = csv.DictReader(f)
        for row in reader:
            el = ET.SubElement(root, "string")
            el.set("name", row["key"])
            el.text = row[lang]
    rough = ET.tostring(root, encoding="unicode")
    parsed = minidom.parseString(rough.encode())
    return parsed.toprettyxml(indent="  ")

print(csv_to_strings("translations.csv", "ru"))

# 训练一个简单的手势分类模型
import tensorflow as tf
from tensorflow import keras

model = keras.Sequential([
    keras.layers.Input(shape=(64, 64, 3)),
    keras.layers.Conv2D(32, (3, 3), activation="relu"),
    keras.layers.MaxPooling2D(2, 2),
    keras.layers.Conv2D(64, (3, 3), activation="relu"),
    keras.layers.Flatten(),
    keras.layers.Dense(128, activation="relu"),
    keras.layers.Dropout(0.2),
    keras.layers.Dense(4, activation="softmax")
])

model.compile(optimizer="adam",
              loss="sparse_categorical_crossentropy",
              metrics=["accuracy"])

# 训练后转换为TFLite
converter = tf.lite.TFLiteConverter.from_keras_model(model)
tflite_model = converter.convert()
with open("gesture_model.tflite", "wb") as f:
    f.write(tflite_model)

print(f"Model size: {len(tflite_model)} bytes")

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from typing import List
import sqlite3

app = FastAPI(title="Mobile App API")

class UserCreate(BaseModel):
    username: str
    email: str
    avatar_url: str | None = None

@app.post("/users", status_code=201)
async def create_user(payload: UserCreate):
    conn = sqlite3.connect("app.db")
    cur = conn.execute(
        "INSERT INTO users (username, email) VALUES (?, ?)",
        (payload.username, payload.email)
    )
    conn.commit()
    user_id = cur.lastrowid
    conn.close()
    return {"id": user_id, "username": payload.username}

@app.get("/users/{user_id}")
async def get_user(user_id: int):
    conn = sqlite3.connect("app.db")
    row = conn.execute(
        "SELECT id, username, email FROM users WHERE id = ?",
        (user_id,)
    ).fetchone()
    conn.close()
    if not row:
        raise HTTPException(status_code=404, detail="User not found")
    return {"id": row[0], "username": row[1], "email": row[2]}

from locust import HttpUser, task, between

class MobileApiUser(HttpUser):
    wait_time = between(1, 5)

    @task(2)
    def get_posts(self):
        self.client.get("/api/v1/posts?page=1")

    @task(1)
    def create_post(self):
        self.client.post("/api/v1/posts", json={
            "title": "Test",
            "body": "Content"
        })

# 最佳实践：自动化脚本中的错误处理
import sys
import logging
from pathlib import Path

logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s")
log = logging.getLogger(__name__)

def build_apk(project_dir: str) -> bool:
    path = Path(project_dir)
    if not path.exists():
        log.error(f"Directory {project_dir} not found")
        return False
    try:
        # 这里是构建命令
        log.info("Build started")
        return True
    except Exception as e:
        log.exception(f"Build failed: {e}")
        return False

if __name__ == "__main__":
    success = build_apk("android/app")
    sys.exit(0 if success else 1)