【Python】npy/pkl/csv读写效率测试

import os
import pickle
import numpy as np
import pandas as pd
import time


def read_pkl(path):
    f = open(path, 'rb')
    test = pickle.load(f)
    f.close()
    return test


def read_csv(path):
    test = pd.read_csv(path)
    return test


def read_npy(path):
    test = np.load(path)
    return test


if __name__ == '__main__':
    s_t = time.time()
    root_path = "ceshi"
    # 写入
    for i in range(200):
        a = np.ones([1000, 1000])
        # 写入npy
        np.save('ceshi/%s.npy' % i, a)
        # 写入pkl
        # f = open('ceshi/%s.pkl' % i, 'wb')
        # pickle.dump(a, f)
        # f.close()
        # 写入csv
        # pd.DataFrame(a).to_csv('ceshi/%s.csv' % i)
    # 读取
    # for i in os.listdir(root_path):
    #     test = read_pkl(os.path.join(root_path, i))

    e_t = time.time()
    print(e_t - s_t)