import numpy as np def np_add(a: np.ndarray, b: np.ndarray): return a + b np_add(1, 2) 上述代码调用 np_add 时,传入了类型不符的变量,使用 mypy 对其进行类型检查: mypy learn_type_hint.py learn_type_hint.py:8: error: Argument 1 to "np_add" has incompatible type "int"; exp...
Has anyone implemented type hinting for the specific numpy.ndarray class? Right now, I'm using typing.Any, but it would be nice to have something more specific. For instance if the numpy people added a type alias for their array_like object class. Better yet, implement support at the dtyp...
import numpy as np def np_add(a: np.ndarray, b: np.ndarray): return a + b np_add(1, 2) 上述代码调用 np_add 时,传入了类型不符的变量,使用 mypy 对其进行类型检查: 复制 mypy learn_type_hint.py learn_type_hint.py:8: error: Argument 1 to "np_add" has incompatible type "int"; ...
The type stub fornp.rec.fromrecordshas a bug and does not hint that an optional keyword-only argumentformatshas a default value. This has no runtime effect but results inmypycomplaining unless a redundantformats=Noneis specified in the code. Reproduce the code example: importnumpyasnprecarray=...
src_kwargs(dict) – Parameters for the source type (e.g.{'dtype'=float}fornumpy_array). dest_kwargs(dict) – Parameters for the destination type (e.g.{'index'=True}fordataframe). Returns: Function to convert from src_type to dest_type. ...
importnumpyasnp arr=np.array([1,2,3]) dict={arr:'value'} In this example, we attempt to use a NumPy array as a key to a dictionary. This results in the error as shown below: We can convert the data type to a hashable object to fix this. In our case, converting the array int...
基础数据类型像是int,float,str,bytes 可以在type hints中直接使用,其他已经封装好的类,也可以直接在type hint中使用。当然抽象类(Abstract Base Classes)在type hint中也很有用。 Optional and Union types 上面2个类型还是比较常见的,我们先来看个例子: ...
Note that being explicit about a function not returning anything is different from not adding a type hint about the return value:# play.py def play(player_name: str): print(f"{player_name} plays") ret_val = play("Henrik") In this latter case Mypy has no information about the return ...
默认情况下,Field只接受使用type函数定义的类型,而无法直接接受使用Type的子类。 然而,我们可以通过自定义Field子类来实现让Pydantic的Field接受使用Type的子类。以下是实现的步骤: 步骤一:创建自定义的Field子类 代码语言:txt 复制 from pydantic import Field, typing class TypeField(Field): def __init__(self,...
label = [CHAR_TO_IDX[char] for char in self.info[file_name]] label = np.array(label, dtype="int64") # 确保 label 是 int64 类型 label_length = len(label) input_length = np.array([IMAGE_SHAPE_W], dtype="int64") # 确保 input_length 是 int64 类型 ...