chore

tests/metagpt/actions/test_execute_code.py

@@ -4,57 +4,57 @@ from metagpt.actions.execute_code import ExecutePyCode
 from metagpt.schema import Message
 
 
-# @pytest.mark.asyncio
-# async def test_code_running():
-#     pi = ExecutePyCode()
-#     output = await pi.run("print('hello world!')")
-#     assert output[1] is True
-#     output = await pi.run({"code": "print('hello world!')", "language": "python"})
-#     assert output[1] is True
-#     code_msg = Message("print('hello world!')")
-#     output = await pi.run(code_msg)
-#     assert output[1] is True
+@pytest.mark.asyncio
+async def test_code_running():
+    pi = ExecutePyCode()
+    output = await pi.run("print('hello world!')")
+    assert output[1] is True
+    output = await pi.run({"code": "print('hello world!')", "language": "python"})
+    assert output[1] is True
+    code_msg = Message("print('hello world!')")
+    output = await pi.run(code_msg)
+    assert output[1] is True
 
 
-# @pytest.mark.asyncio
-# async def test_split_code_running():
-#     pi = ExecutePyCode()
-#     output = await pi.run("x=1\ny=2")
-#     output = await pi.run("z=x+y")
-#     output = await pi.run("assert z==3")
-#     assert output[1] is True
+@pytest.mark.asyncio
+async def test_split_code_running():
+    pi = ExecutePyCode()
+    output = await pi.run("x=1\ny=2")
+    output = await pi.run("z=x+y")
+    output = await pi.run("assert z==3")
+    assert output[1] is True
 
 
-# @pytest.mark.asyncio
-# async def test_execute_error():
-#     pi = ExecutePyCode()
-#     output = await pi.run("z=1/0")
-#     assert output[1] is False
+@pytest.mark.asyncio
+async def test_execute_error():
+    pi = ExecutePyCode()
+    output = await pi.run("z=1/0")
+    assert output[1] is False
 
 
-# @pytest.mark.asyncio
-# async def test_plotting_code():
-#     pi = ExecutePyCode()
-#     code = """
-#     import numpy as np
-#     import matplotlib.pyplot as plt
+@pytest.mark.asyncio
+async def test_plotting_code():
+    pi = ExecutePyCode()
+    code = """
+    import numpy as np
+    import matplotlib.pyplot as plt
 
-#     # 生成随机数据
-#     random_data = np.random.randn(1000)  # 生成1000个符合标准正态分布的随机数
+    # 生成随机数据
+    random_data = np.random.randn(1000)  # 生成1000个符合标准正态分布的随机数
 
-#     # 绘制直方图
-#     plt.hist(random_data, bins=30, density=True, alpha=0.7, color='blue', edgecolor='black')
+    # 绘制直方图
+    plt.hist(random_data, bins=30, density=True, alpha=0.7, color='blue', edgecolor='black')
 
-#     # 添加标题和标签
-#     plt.title('Histogram of Random Data')
-#     plt.xlabel('Value')
-#     plt.ylabel('Frequency')
+    # 添加标题和标签
+    plt.title('Histogram of Random Data')
+    plt.xlabel('Value')
+    plt.ylabel('Frequency')
 
-#     # 显示图形
-#     plt.show()
-#     """
-#     output = await pi.run(code)
-#     assert output[1] is True
+    # 显示图形
+    plt.show()
+    """
+    output = await pi.run(code)
+    assert output[1] is True
 
 
 @pytest.mark.asyncio