Question

如何对numpy数组进行序列化/反序列化？

A           = np.random.randint(0, 10, 40).reshape(8, 5)
print(A)
print (A.dtype)
snapshot   = A
serialized = snapshot.tobytes()

    [[9 5 5 7 4]
     [3 8 8 1 0]
     [5 7 1 0 2]
     [2 2 7 1 2]
     [2 6 3 5 4]
     [7 5 4 8 3]
     [2 4 2 4 7]
     [3 4 2 6 2]]
    int64

返回

 deserialized = np.frombuffer(serialized).astype(np.int64)
 print (deserialized)

 [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
     0 0 0]

Answer 1

用于生成dtype的默认A与np.frombuffer中的默认# Python 3.6 64-bits with numpy 1.12.1 64-bits A = np.random.randint(0, 10, 40).reshape(8, 5) print(A) >>> array([[3, 3, 5, 3, 9], [1, 4, 7, 1, 8], [1, 7, 4, 3, 0], [9, 2, 9, 1, 2], [2, 8, 9, 1, 1], [3, 3, 5, 2, 6], [5, 0, 2, 7, 6], [2, 8, 8, 0, 7]]) A.dtype >>> dtype('int32') deserialized = np.frombuffer(A.tobytes(), dtype=np.int32).reshape(A.shape) print(deserialized) >>> array([[3, 3, 5, 3, 9], [1, 4, 7, 1, 8], [1, 7, 4, 3, 0], [9, 2, 9, 1, 2], [2, 8, 9, 1, 1], [3, 3, 5, 2, 6], [5, 0, 2, 7, 6], [2, 8, 8, 0, 7]])之间不匹配。使用正确的dtype时可以按预期工作（可能取决于计算机/ Python / numpy版本）：

//const fetch = require("node-fetch")
const axios = require("axios")
const DisplayFunctions = require('./app/display');
let i = 0;
var requestLoop = setInterval(() => {
    try {
        i++;
        DisplayFunctions.showError("called " + i + " times")
        axios.get("https://jsonplaceholder.typicode.com/todos/1")
        //fetch("https://jsonplaceholder.typicode.com/todos/1")
        .then(() => {
            DisplayFunctions.showError("worked " + i + " times")
        })
        .catch((err) => {
            DisplayFunctions.showError(err.message)
        })
        } catch (err) {
            DisplayFunctions.showError(err.message)
    }
},1000);

如何使用Numpy .tobytes（）序列化对象

1 个答案: