使用Python远程连接并操作InfluxDB数据库

by:授客 QQ：1033553122

实践环境

Python 3.4.0

CentOS 6 64位（内核版本2.6.32-642.el6.x86_64）

influxdb-1.5.2.x86_64.rpm

网盘下载地址：

https://pan.baidu.com/s/1jAbY4xz5gvzoXxLHesQ-PA

influxdb-5.0.0-py2.py3-none-any.whl

下载地址：

https://pypi.org/project/influxdb/#files

下载地址：https://pan.baidu.com/s/1DQ0HGYNg2a2-VnRSBdPHmg

几个重要的名词介绍

database：数据库；

measurement：数据库中的表；

point：表里面的一行数据。

每个行记录由time(纳秒时间戳)、字段（fields）和tags组成。

time：每条数据记录的时间，也是数据库自动生成的主索引；

fields：记录各个字段的值；

tags：各种有索引的属性，一般用于where查询条件。

实践代码

#encoding:utf-8

__author__ = ‘shouke’

import random

from influxdb import InfluxDBClient

client = InfluxDBClient(‘10.203.25.106’, 8086, timeout=10) # timeout 超时时间 10秒

print(‘获取数据库列表：’)

database_list = client.get_list_database()

print(database_list)

print(‘\n创建数据库’)

client.create_database(‘mytestdb’)

print(client.get_list_database())

print(‘\n切换至数据库（切换至对应数据库才可以操作数据库对象)\n’)

client.switch_database(‘mytestdb’)

print(‘插入表数据\n’)

for i in range(0, 10):

    json_body = [

        {

            “measurement”: “table1”,

            “tags”: {

                “stuid”: “stuid1”

            },

            # “time”: “2018-05-16T21:58:00Z”,

            “fields”: {

                “value”: float(random.randint(0, 1000))

            }

        }

    ]

    client.write_points(json_body)

print(‘查看数据库所有表\n’)

tables = client.query(‘show measurements;’)

print(‘查询表记录’)

rows = client.query(‘select value from table1;’)

print(rows)

print(‘\n删除表\n’)

client.drop_measurement(‘table1’)

print(‘删除数据库\n’)

client.drop_database(‘mytestdb’)

输出结果：

获取数据库列表：

[{‘name’: ‘_internal’}]

创建数据库

[{‘name’: ‘_internal’}, {‘name’: ‘mytestdb’}]

切换至数据库（切换至对应数据库才可以操作数据库对象)

插入表数据

查看数据库所有表

查询表记录

ResultSet({‘(‘table1′, None)’: [{‘time’: ‘2018-05-23T11:55:55.341839963Z’, ‘value’: 165}, {‘time’: ‘2018-05-23T11:55:55.3588771Z’, ‘value’: 215}, {‘time’: ‘2018-05-23T11:55:55.367430575Z’, ‘value’: 912}, {‘time’: ‘2018-05-23T11:55:55.37528554Z’, ‘value’: 34}, {‘time’: ‘2018-05-23T11:55:55.383530082Z’, ‘value’: 680}, {‘time’: ‘2018-05-23T11:55:55.391322174Z’, ‘value’: 247}, {‘time’: ‘2018-05-23T11:55:55.399173622Z’, ‘value’: 116}, {‘time’: ‘2018-05-23T11:55:55.407073805Z’, ‘value’: 224}, {‘time’: ‘2018-05-23T11:55:55.414792607Z’, ‘value’: 415}, {‘time’: ‘2018-05-23T11:55:55.422871017Z’, ‘value’: 644}]})

删除表

删除数据库

说明：

class influxdb.InfluxDBClient(host=u’localhost’, port=8086, username=u’root’, password=u’root’, database=None, ssl=False, verify_ssl=False, timeout=None, retries=3, use_udp=False, udp_port=4444, proxies=None)

参数

host (str) – 用于连接的InfluxDB主机名称，默认‘localhost’

port (int) – 用于连接的Influxport端口，默认8086

username (str) – 用于连接的用户名，默认‘root’

password (str) – 用户密码，默认‘root’

database (str) – 需要连接的数据库，默认None

ssl (bool) – 使用https连接，默认False

verify_ssl (bool) – 验证https请求的SSL证书，默认False

timeout (int) – 连接超时时间(单位：秒)，默认None,

retries (int) – 终止前尝试次数（number of retries your client will try before aborting, defaults to 3. 0 indicates try until success）

use_udp (bool) – 使用UDP连接到InfluxDB默认False

udp_port (int) – 使用UDP端口连接，默认4444

proxies (dict) – 为请求使用http（s）代理，默认 {}

query(query, params=None, epoch=None, expected_response_code=200, database=None, raise_errors=True, chunked=False, chunk_size=0)

参数:

query (str) – 真正执行查询的字符串

params (dict) – 查询请求的额外参数，默认{}

epoch (str) – response timestamps to be in epoch format either ‘h’, ‘m’, ‘s’, ‘ms’, ‘u’, or ‘ns’,defaults to None which is RFC3339 UTC format with nanosecond precision

expected_response_code (int) – 期望的响应状态码，默认 200

database (str) – 要查询的数据库，默认数据库

raise_errors (bool) – 查询返回错误时，是否抛出异常，默认

chunked (bool) – Enable to use chunked responses from InfluxDB. With chunked enabled, one ResultSet is returned per chunk containing all results within that chunk

chunk_size (int) – Size of each chunk to tell InfluxDB to use.

返回数据查询结果集

write_points(points, time_precision=None, database=None, retention_policy=None, tags=None, batch_size=None, protocol=u’json’)

参数

points  由字典项组成的list，每个字典成员代表了一个

time_precision (str) – Either ‘s’, ‘m’, ‘ms’ or ‘u’, defaults to None

database (str) – points需要写入的数据库，默认为当前数据库

tags (dict) – 同每个point关联的键值对，key和value都要是字符串.

retention_policy (str) – the retention policy for the points. Defaults to None

batch_size (int) – value to write the points in batches instead of all at one time. Useful for when doing data dumps from one database to another or when doing a massive write operation, defaults to None

protocol (str) – Protocol for writing data. Either ‘line’ or ‘json’.

如果操作成功，返回True

就query，write_points操作来说，如果操作执行未调用switch_database函数，切换到目标数据库，可以在调用query，write_points函数时，可以指定要操作的数据库，如下

client.query(‘show measurements;’, database=’mytestdb’)

client.write_points(json_body, database=’mytestdb’)

points参数值，可以不指定 time，这样采用influxdb自动生成的时间

    json_body = [

        {

            “measurement”: “table1”,

            “tags”: {

                “stuid”: “stuid1”

            },

            # “time”: “2018-05-16T21:58:00Z”,

            “fields”: {

                “value”: float(random.randint(0, 1000))

            }

        }

    ]

另外，需要注意的是，influxDB使用UTC时间，所以，如果显示指定时间，需要做如下处理：

timetuple = time.strptime(time.localtime(), ‘%Y-%m-%d %H:%M:%S’)

second_for_localtime_utc = int(time.mktime(timetuple)) + 1 – 8 * 3600 # UTC时间（秒）

timetuple = time.localtime(second_for_localtime_utc)

date_for_data = time.strftime(‘%Y-%m-%d’, timetuple)

time_for_data = time.strftime(‘%H:%M:%S’, timetuple)

datetime_for_data = date_for_data + ‘T’ + time_for_data + ‘Z’

json_body = [

{

        “measurement”: “table1”,

        “tags”: {

            “stuid”: “stuid1”

        },

        “time”: datetime_for_data,

        “fields”: {

            “value”: float(random.randint(0, 1000))

        }

   }

]

https://influxdb-python.readthedocs.io/en/latest/api-documentation.html#influxdbclient