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Python 使用Python远程连接并操作InfluxDB数据库

2019年02月17日  | 移动技术网IT编程  | 我要评论

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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:

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

 

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))

        }

   }

]

 

 

 

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