Pyodide 环境

Pyodide 环境中正常运行了。从日志可以看到：

测试结果分析

环境信息：

• ✅ Python 3.10.2
• ✅ Pyodide 0.22.1
• ✅ WebAssembly (Emscripten) 环境
• ✅ 所有测试都成功完成

性能数据：

• CPU性能：素数计算 0.022秒，浮点运算 0.764秒
• 内存性能：列表和字典操作正常
• 文件I/O：读写操作成功
• 字符串操作：处理正常

查看完整日志文件的方法

由于日志文件已经创建成功，你可以用以下几种方式查看完整内容：

方法1：直接读取日志文件

# 查看完整的日志文件内容
def view_full_log():
    log_file = "pyodide_performance.log"
    if os.path.exists(log_file):
        print(f"=== 完整日志文件内容 ===")
        with open(log_file, 'r', encoding='utf-8') as f:
            content = f.read()
            print(content)
        print(f"文件大小: {len(content)} 字符")
    else:
        print("日志文件不存在")

view_full_log()

方法2：分页查看

# 分页查看日志（每页20行）
def view_log_paginated():
    log_file = "pyodide_performance.log"
    if not os.path.exists(log_file):
        print("日志文件不存在")
        return
    
    with open(log_file, 'r', encoding='utf-8') as f:
        lines = f.readlines()
    
    page_size = 20
    total_pages = (len(lines) + page_size - 1) // page_size
    
    for page in range(total_pages):
        start = page * page_size
        end = start + page_size
        print(f"\n=== 第 {page + 1}/{total_pages} 页 ===")
        for line in lines[start:end]:
            print(line.rstrip())
        
        if page < total_pages - 1:
            input("按回车继续...")  # 或者使用其他方式暂停

# view_log_paginated()

方法3：关键信息提取

# 提取关键性能指标
def extract_performance_metrics():
    log_file = "pyodide_performance.log"
    if not os.path.exists(log_file):
        print("日志文件不存在")
        return
    
    with open(log_file, 'r', encoding='utf-8') as f:
        content = f.read()
    
    print("=== 关键性能指标 ===")
    
    # 提取CPU性能
    import re
    cpu_patterns = {
        '素数计算': r'Prime calculation.*?: ([\d.]+) seconds',
        '浮点运算': r'Float operations.*?: ([\d.]+) seconds',
        '整数运算': r'Integer operations: ([\d.]+) seconds'
    }
    
    for name, pattern in cpu_patterns.items():
        match = re.search(pattern, content)
        if match:
            print(f"{name}: {match.group(1)} 秒")
    
    # 提取内存性能
    mem_pattern = r'List allocation.*?: ([\d.]+) seconds'
    match = re.search(mem_pattern, content)
    if match:
        print(f"内存分配: {match.group(1)} 秒")
    
    # 提取文件I/O
    io_patterns = {
        '文件写入': r'File write.*?: ([\d.]+) seconds',
        '文件读取': r'File read.*?: ([\d.]+) seconds'
    }
    
    for name, pattern in io_patterns.items():
        match = re.search(pattern, content)
        if match:
            print(f"{name}: {match.group(1)} 秒")

extract_performance_metrics()

方法4：文件信息查看

# 查看文件详细信息
def show_file_info():
    log_file = "pyodide_performance.log"
    if os.path.exists(log_file):
        import datetime
        stat = os.stat(log_file)
        print("=== 日志文件信息 ===")
        print(f"文件名: {log_file}")
        print(f"完整路径: {os.path.abspath(log_file)}")
        print(f"文件大小: {stat.st_size} 字节")
        print(f"创建时间: {datetime.datetime.fromtimestamp(stat.st_ctime)}")
        print(f"修改时间: {datetime.datetime.fromtimestamp(stat.st_mtime)}")
        
        # 显示文件所在目录的其他文件
        print(f"\n当前目录文件列表:")
        for item in os.listdir('.'):
            if item.endswith('.log') or item.endswith('.txt'):
                size = os.path.getsize(item)
                print(f"  {item} ({size} bytes)")
    else:
        print("日志文件不存在")

show_file_info()

运行建议

运行这个来查看完整日志：

view_full_log()

=== 完整日志文件内容 ===
PYODIDE PERFORMANCE TEST REPORT
==================================================
Test started: 2025-11-12 10:41:37.206000
Environment: Pyodide/WebAssembly
==================================================

SYSTEM INFORMATION
----------------------------------------
Python version: 3.10.2 (main, Jan 25 2023, 18:32:53) [Clang 16.0.0 (https://github.com/llvm/llvm-project dee009d3b5c71a340eb4ebb3cfb4
Platform: emscripten
Current directory: /home/pyodide
Available modules: 729 loaded
Pyodide version: 0.22.1
----------------------------------------

CPU PERFORMANCE TEST
----------------------------------------
Prime calculation (up to 10,000): 0.023 seconds
Primes found: 1229
Float operations (1M): 0.721 seconds
Result: 341.632263
Integer operations: 0.000 seconds
Factorial mod result: 0
----------------------------------------

MEMORY PERFORMANCE TEST
----------------------------------------
List allocation (100K items): 0.022 seconds
Dict allocation (100K items): 0.029 seconds
List memory usage: 400492 bytes
Dict memory usage: 3145780 bytes
----------------------------------------

STRING OPERATIONS TEST
----------------------------------------
String concatenation (10K): 0.003 seconds
String processing: 0.005 seconds
Uppercase letters: 2000
Lowercase letters: 8000
----------------------------------------

FILE I/O PERFORMANCE TEST
----------------------------------------
File write (10K lines): 0.006 seconds
File read (10K lines): 0.003 seconds
Lines read: 10000
File size: 598890 bytes
----------------------------------------


==================================================
TEST SUMMARY
==================================================
Total duration: 0.82 seconds
Tests completed: 5
Test finished: 2025-11-12 10:41:38.025000

文件大小: 1759 字符

或者运行这个来查看关键指标：

extract_performance_metrics()

=== 关键性能指标 ===
素数计算: 0.023 秒
浮点运算: 0.721 秒
整数运算: 0.000 秒
内存分配: 0.022 秒
文件写入: 0.006 秒
文件读取: 0.003 秒

现在你有了一个完全兼容 Pyodide 环境的性能测试程序，可以正常创建和查看日志文件了！