前言:
该项目环境为Ubuntu16.04,python3.5
python库为pymysql,安装直接在终端输入pip3 install pymysql
使用参考:https://blog.csdn.net/qq_37176126/article/details/72824106
数据库采用mysql,附上安装链接:https://blog.csdn.net/nancy50/article/details/81080693
mysql的可视化操作软件是navicat,附上安装链接:https://blog.csdn.net/superit401/article/details/78110079/
import numpy as np
import pymysql as ml
def insertData(numpy_bytes,shape_str):
db = ml.connect(host="localhost", user="root", password="123456", db="test", port=3306)
#连接数据库对象
cur = db.cursor()
#游标对象
sql = "insert into face_data(numpy_data,shape) values(%s,%s)"
#定义好sql语句,%s是字符串的占位符
try:
cur.execute(sql,(numpy_bytes,shape_str))
#执行sql语句
db.commit()
#提交到数据库中
except Exception as e:
#捕获异常
raise e
finally:
db.close() # 关闭连接
def readData():
db = ml.connect(host="localhost", user="root", password="123456", db="test", port=3306)
#连接数据库对象
cur = db.cursor()
#游标对象
sql = "select * from face_data"
#定义好sql语句,%s是字符串的占位符
try:
cur.execute(sql)
#执行sql语句
results = cur.fetchall()
#获取所有结果集
for row in results:
numArr = np.fromstring(string=row[1], dtype=int)
#将读取到的字节流转化为ndarray数组
shape = tuple(eval(row[2]))
#将读取到的shape转换为元组的格式,这里的eval(),由于我们元组里面的数据是int的所以,这里eval()的作用就是把本该是数字的转化回来
numArr.shape = shape
#设置维度,设置的数值为元组
print(numArr)
db.commit()
#提交到数据库中
except Exception as e:
#捕获异常
raise e
finally:
db.close() # 关闭连接
if __name__ == '__main__':
arr =np.arange(0, 45).reshape(3,5,3)
#生产0-45数字的维度=(3,5,3)的三维数组
shape_ = arr.shape
#获取数组的维度
numpy_bytes = arr.tostring()
#将数组转化为二进制流
shape_str = "".join(str(shape_))
#将shape元组转化为字符串
insertData(numpy_bytes, shape_str)
#插入数据库
readData()
#读取数据库