标签：启动 发布订阅 string 订阅 can 长度 number 认证 运行
# 是一种非关系数据库 no only SQL 缓存 操作原子性 数据保存在内存 定期写到磁盘 安装 sudo apt-get update sudo apt install redis-server 启动 redis-server 连接： 本机连接： redis-cli 127.0.0.1:6379 远程连接： 修改虚拟机上redis的配置文件 /etc/redis/redis.conf """ 如果要从外部计算机连接到Redis，可以采用以下解决方案之一： 1）通过从运行服务器的同一主机连接到Redis，只需禁用保护模式，从环回接口发送命令“CONFIG SET protected mode no”， 但是，如果要从internet公开访问Redis，请确保这样做。使用配置重写将此更改永久化。 2） 或者，您可以通过编辑Redis配置文件，将protected mode选项设置为“no”，然后重新启动服务器来禁用保护模式。 3） 如果您只是为了测试而手动启动服务器，请使用“--protected mode no”选项重新启动它。 4） 设置绑定地址或身份验证密码。 """ bind 0.0.0.0 允许IP所有连接 requirepass password 设置用户认证密码 重启redis /etc/init.d/redis-server restart 之后远程redis需要认证 redis-cli 连接 AUTH password 认证 使用： 操作字符串： key -value set name "" EX 超时时间秒 FX 超时时间毫秒 NX 当set时如果name存在就忽略，不存在才创建 XX 当set时name存在则修改，不存在不执行 # 存入字符串 get name # 取出字符串 keys * # 查看所有键 mset # 批量设置 MSET key value key value mget # 批量获取 MGET key key getset # 获取旧值并设置新值 **************************************************************************** setbit # 将字符串转换为二进制，对二进制的某一位设置0或1 ord("a") 获取ASCII码 bin(ASCII码) 获得二进制 "w":119 01110111 -> "h":104 01101000 -> "y":121 01111001 -> "g":103 01100111 19 0 20 0 21 1 22 1 getbit # 获取这个字符串二进制位上的值 bitcount # 获取为1的个数 127.0.0.1:6379> set age 18 ex 3 OK 127.0.0.1:6379> get age (nil) 127.0.0.1:6379> GETRANGE name 1 2 # 对字符串切片 "hy" 127.0.0.1:6379> SETRANGE name 0 "rtuiijn" # 从0位置向后覆盖 (integer) 7 127.0.0.1:6379> get name "rtuiijn" strlen 获取字节长度 incr 对数字自增1 incrbyfloat key num 浮点增 decr 自减 append 拼接 Hash操作 如同结构体 小明 -> {"age":18,"hobby":"gril"} 小红 -> {"age":18,"sex":"women"} HSET key filed value hmset key filed value [filed value...] HGETALL key 获取key中的所有filed HLEN key 获取key中filed的个数 HEXISTS key 判断key是否存在 hscan key cursor [match *] [count count] cursor 光标 127.0.0.1:6379> HSCAN xiaoming 0 match a* 1) "0" 2) 1) "age" 2) "18" 操作列表 LPUSH KEY VALUE 从左到右存 RPUSH KEY VALUE LRANGE KEY START STOP LLEN key LINSERT key befor|after 位置 value 位置是列表中具体的value LSET key index value 重新设置某位置上的值 LREM key count value 删掉count个value LPOP LINDEX KEY INDEX LTRIM key start stop RPOPLPUSH keyA keyB 从A的右边拿出一个值给B RPOPLPUSH keyA keyB timeout 从A的右边拿出一个值给B，A中无值后等待超时，期间有加入则立即放到B BLPOP key [key....] timeout 将key中的所有值依次取出，取完所有key之后等待超时时间，此时如果有新加入的值则立刻取出 操作集合 关系测试 SADD key value SMEMBER key SCARD key 元素个数 有序集合 管道 python操作redis每次操作都要请求一次redis，消耗比较大，这时就可以使用管道， 所有的操作变为一个事务，最终一起提交到redis执行 import redis # r = redis.Redis(host="192.168.193.129",port=6379,password="w000000") # print(r.get("age")) pool = redis.ConnectionPool(host="192.168.193.129",port=6379,password="w000000") # 建立一个连接池 r = redis.Redis(connection_pool=pool) pipe = r.pipeline(transaction=True) # 开启事务 transaction：业务 r.set("year","2020") r.set("month","5") pipe.execute() # 执行事务 发布订阅： # 发布订阅类 import redis class Helper(): def __init__(self): self.pool = redis.ConnectionPool(host="192.168.193.129",port=6379,password="w000000") self.__conn = redis.Redis(connection_pool=self.pool) self.pub = "fm105.8" self.sub = "fm105.8" def public(self,msg): self.__conn.publish(self.pub,msg) return True def subscribe(self): pub = self.__conn.pubsub() pub.subscribe(self.sub) pub.parse_response() return pub # 发布者 from redis_helper import Helper obj = Helper() obj.public("www") # 订阅者 多个订阅同时接收 from redis_helper import Helper obj = Helper() sub = obj.subscribe() while True: msg = sub.parse_response() print(msg) Celery： Celery 是一个 基于python开发的分布式异步消息任务队列 报错AttributeError: ‘float‘ object has no attribute ‘items‘:解决redis==2.10.6 报错kombu.exceptions.VersionMismatch: Redis transport requires redis-py versions 3.2.0 or later. You have 2.10.6：解决kombu==4.1.0 celery==4.1.0 celery_test.py from clery import Celery app = Celery("tasts", broker="redis://:w000000@192.168.193.129:6379/0", # 中间件 backend="redis://:w000000@192.168.193.129") # 最后的任务结果需要指定地点写入 @app.tast def add(x,y): return x+y celery -A celery_test worker --loglevel=info 启动 另起会话 进入python from celery_test import add add.delay(4,4) <AsyncResult: 4a710433-ae4b-4f05-ae4c-7385f2968f5a> >>> result.get() 13 在django中使用celery 一、创建django项目 二、创建celery.py、tasks.py，修改__init__.py位置如下 celery_django -celery_django -__init__.py -celery.py -app01 -tasks.py celery.py from __future__ import absolute_import, unicode_literals import os from celery import Celery # set the default Django settings module for the ‘celery‘ program. os.environ.setdefault(‘DJANGO_SETTINGS_MODULE‘, ‘django_celery.settings‘) # 项目名 app = Celery(‘django_celery‘) # app名 # Using a string here means the worker don‘t have to serialize # the configuration object to child processes. # - namespace=‘CELERY‘ means all celery-related configuration keys # should have a `CELERY_` prefix. app.config_from_object(‘django.conf:settings‘, namespace=‘CELERY‘) # Load task modules from all registered Django app configs. app.autodiscover_tasks() @app.task(bind=True) def debug_task(self): print(‘Request: {0!r}‘.format(self.request)) __init__.py from __future__ import absolute_import, unicode_literals # This will make sure the app is always imported when # Django starts so that shared_task will use this app. from .celery import app as celery_app __all__ = [‘celery_app‘] tasks.py from __future__ import absolute_import, unicode_literals from celery import shared_task @shared_task def add(x, y): return x + y @shared_task def mul(x, y): return x * y @shared_task def xsum(numbers): return sum(numbers) 三、修改settings.py CELERY_BROKER_URL=‘redis://:w000000@192.168.193.129:6379/0‘ CELERY_RESULT_BACKEND=‘redis://:w000000@192.168.193.129‘ 四、在项目目录中启动celery celery -A django_celery worker -l info 返回： /usr/lib/python3/dist-packages/celery/platforms.py:795: RuntimeWarning: You‘re running the worker with superuser privileges: this is absolutely not recommended! Please specify a different user using the -u option. User information: uid=0 euid=0 gid=0 egid=0 uid=uid, euid=euid, gid=gid, egid=egid, -------------- celery@why-virtual-machine v4.1.0 (latentcall) ---- **** ----- --- * *** * -- Linux-5.3.0-51-generic-x86_64-with-Ubuntu-18.04-bionic 2020-05-21 11:54:13 -- * - **** --- - ** ---------- [config] - ** ---------- .> app: celery_test:0x7f655863c5f8 - ** ---------- .> transport: redis://:**@192.168.193.129:6379/0 - ** ---------- .> results: redis://:**@192.168.193.129/ - *** --- * --- .> concurrency: 1 (prefork) -- ******* ---- .> task events: OFF (enable -E to monitor tasks in this worker) --- ***** ----- -------------- [queues] .> celery exchange=celery(direct) key=celery [tasks] . celery_test.tasks.add . celery_test.tasks.mul . celery_test.tasks.xsum . django_celery.celery.debug_task [2020-05-21 11:54:13,966: INFO/MainProcess] Connected to redis://:**@192.168.193.129:6379/0 [2020-05-21 11:54:13,992: INFO/MainProcess] mingle: searching for neighbors [2020-05-21 11:54:15,039: INFO/MainProcess] mingle: all alone [2020-05-21 11:54:15,058: WARNING/MainProcess] /usr/lib/python3/dist-packages/celery/fixups/django.py:202: UserWarning: Using settings.DEBUG leads to a memory leak, never use this setting in production environments! warnings.warn(‘Using settings.DEBUG leads to a memory leak, never ‘ [2020-05-21 11:54:15,058: INFO/MainProcess] celery@why-virtual-machine ready. [2020-05-21 11:54:16,126: INFO/MainProcess] Received task: celery_test.tasks.add[44d461c0-5fea-4690-93e7-696d3439553c] [2020-05-21 11:54:16,128: INFO/MainProcess] Received task: celery_test.tasks.add[5c2e933f-a926-4c5b-90a9-cbad1f1c050b] [2020-05-21 11:54:16,129: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,130: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,134: INFO/MainProcess] Received task: celery_test.tasks.add[38bedc71-a5df-4ec6-8788-5a03fee379d0] [2020-05-21 11:54:16,136: INFO/ForkPoolWorker-1] Task celery_test.tasks.add[44d461c0-5fea-4690-93e7-696d3439553c] succeeded in 0.007576367999718059s: 111 [2020-05-21 11:54:16,138: INFO/MainProcess] Received task: celery_test.tasks.add[c27419ab-0615-48ba-8778-4ccd5fe5e5fb] [2020-05-21 11:54:16,140: INFO/MainProcess] Received task: celery_test.tasks.add[2edd2899-85fb-4548-b84a-2a83fe26b0da] [2020-05-21 11:54:16,140: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,141: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,142: INFO/ForkPoolWorker-1] Task celery_test.tasks.add[5c2e933f-a926-4c5b-90a9-cbad1f1c050b] succeeded in 0.0015097089999471791s: 111 [2020-05-21 11:54:16,144: INFO/MainProcess] Received task: celery_test.tasks.add[572f86f7-a852-4c2d-99c2-344f48703e7b] [2020-05-21 11:54:16,144: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,144: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,145: INFO/ForkPoolWorker-1] Task celery_test.tasks.add[38bedc71-a5df-4ec6-8788-5a03fee379d0] succeeded in 0.0008416309992753668s: 111 [2020-05-21 11:54:16,147: INFO/MainProcess] Received task: celery_test.tasks.add[5bf2f552-cb77-419b-bea5-276cdec41b27] [2020-05-21 11:54:16,148: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,148: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,149: INFO/ForkPoolWorker-1] Task celery_test.tasks.add[c27419ab-0615-48ba-8778-4ccd5fe5e5fb] succeeded in 0.0016753949985286454s: 111 [2020-05-21 11:54:16,151: INFO/MainProcess] Received task: celery_test.tasks.add[a3d9893a-9203-48eb-afeb-98c89b0d2f8e] [2020-05-21 11:54:16,153: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,153: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,154: INFO/ForkPoolWorker-1] Task celery_test.tasks.add[2edd2899-85fb-4548-b84a-2a83fe26b0da] succeeded in 0.001095354000426596s: 111 [2020-05-21 11:54:16,156: INFO/MainProcess] Received task: celery_test.tasks.add[992ad66f-3572-4442-b6ba-001b344327f4] [2020-05-21 11:54:16,157: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,157: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,158: INFO/ForkPoolWorker-1] Task celery_test.tasks.add[572f86f7-a852-4c2d-99c2-344f48703e7b] succeeded in 0.0011435019987402484s: 111 [2020-05-21 11:54:16,160: INFO/MainProcess] Received task: celery_test.tasks.add[248c52a6-2792-4a0f-b34e-abdfe0ce7c45] [2020-05-21 11:54:16,160: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,161: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,161: INFO/ForkPoolWorker-1] Task celery_test.tasks.add[5bf2f552-cb77-419b-bea5-276cdec41b27] succeeded in 0.0011216180009796517s: 111 [2020-05-21 11:54:16,163: INFO/MainProcess] Received task: celery_test.tasks.add[4c4c28cc-d8e9-4466-a963-f6e5f71ccbad] [2020-05-21 11:54:16,164: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,165: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,166: INFO/ForkPoolWorker-1] Task celery_test.tasks.add[a3d9893a-9203-48eb-afeb-98c89b0d2f8e] succeeded in 0.001705070999378222s: 111 [2020-05-21 11:54:16,168: INFO/MainProcess] Received task: celery_test.tasks.add[d0f56426-2254-486a-8ab3-a88da51c9019] [2020-05-21 11:54:16,169: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,170: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,170: INFO/ForkPoolWorker-1] Task celery_test.tasks.add[992ad66f-3572-4442-b6ba-001b344327f4] succeeded in 0.001145517000622931s: 111 [2020-05-21 11:54:16,172: INFO/MainProcess] Received task: celery_test.tasks.add[5b885602-d37e-4f07-b1fb-e708097c8ac0] [2020-05-21 11:54:16,173: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,173: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,173: INFO/ForkPoolWorker-1] Task celery_test.tasks.add[248c52a6-2792-4a0f-b34e-abdfe0ce7c45] succeeded in 0.0006293960013863398s: 111 [2020-05-21 11:54:16,175: INFO/MainProcess] Received task: celery_test.tasks.add[3de908e5-186c-41c2-bdf0-6ed67cb05084] [2020-05-21 11:54:16,176: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,176: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,177: INFO/ForkPoolWorker-1] Task celery_test.tasks.add[4c4c28cc-d8e9-4466-a963-f6e5f71ccbad] succeeded in 0.0010510339998290874s: 111 [2020-05-21 11:54:16,178: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,179: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,179: INFO/ForkPoolWorker-1] Task celery_test.tasks.add[d0f56426-2254-486a-8ab3-a88da51c9019] succeeded in 0.000996217000647448s: 111 [2020-05-21 11:54:16,180: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,181: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,181: INFO/ForkPoolWorker-1] Task celery_test.tasks.add[5b885602-d37e-4f07-b1fb-e708097c8ac0] succeeded in 0.0008322609992319485s: 111 [2020-05-21 11:54:16,182: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,182: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:54:16,183: INFO/ForkPoolWorker-1] Task celery_test.tasks.add[3de908e5-186c-41c2-bdf0-6ed67cb05084] succeeded in 0.0007275499992829282s: 111 [2020-05-21 11:55:36,283: INFO/MainProcess] Received task: celery_test.tasks.add[7252baec-66ca-41e6-8c4b-de6d5083f3b5] [2020-05-21 11:55:36,284: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:55:36,284: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:55:36,286: INFO/ForkPoolWorker-1] Task celery_test.tasks.add[7252baec-66ca-41e6-8c4b-de6d5083f3b5] succeeded in 0.0020388960001582745s: 111 [2020-05-21 11:55:52,701: INFO/MainProcess] Received task: celery_test.tasks.add[0edcf8a0-48f7-40b2-800c-c66acd983921] [2020-05-21 11:55:52,702: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:55:52,702: WARNING/ForkPoolWorker-1] 4 [2020-05-21 11:55:52,703: INFO/ForkPoolWorker-1] Task celery_test.tasks.add[0edcf8a0-48f7-40b2-800c-c66acd983921] succeeded in 0.0011271639996266458s: 111 五、启动项目 六、获取任务id tasks.id 七、根据任务id获取任务结果 from celery.result import AsyncResult task_id = "" res_task = AsyncResult(id=task_id) res = res.get() celery定时任务 目录结构如下： s3proj/ ├── celery.py ├── __init__.py ├── __pycache__ │ ├── celery.cpython-36.pyc │ ├── __init__.cpython-36.pyc │ └── tasks.cpython-36.pyc └── tasks.py celery.py: from celery import Celery #创建一个Celery对象 broker = ‘redis://:w000000@127.0.0.1:6379/0‘ #任务放在用redis://ip:端口/第几个数据库 backend = ‘redis://:w000000@127.0.0.1‘ #任务结果放在 include = [‘s3proj.tasks‘,] #任务所在目录 app = Celery(broker=broker, backend=backend, include=include) app.conf.timezone = ‘Asia/Shanghai‘ #配置时区 app.conf.enable_utc = False # 是否使用UTC from datetime import timedelta from celery.schedules import crontab app.conf.beat_schedule = { #任务名称自定义可随意 ‘get_banner-task‘: { ‘task‘: ‘s3proj.tasks.get_baidu_info‘,#任务所在路径且指定哪个任务 ‘schedule‘: 10.0, #定时任务相关 }, } tasks.py: from .celery import app @app.task #一定要加装饰器 def get_baidu_info(): return "success" 启动worker celery -A s3proj worker -l info 启动beat celery -A s3proj beat Celery与Django结合实现定时任务 1.pip3 install django-celery-beat 2.INSTALLED_APPS = ( ..., ‘django_celery_beat‘, ) 3.python3 manage.py makemigrations 4.python3 manage.py migrate 5.进入admin Clocked Crontabs # 具体日期时间执行 Intervals # 间隔执行 Periodic tasks # 任务定义，任务在task.py中，会被自动发现 Solar events celery -A celery_time beat -l info -S django # 启动beat celery -A celery_time worker -l info # 启动worker
标签：启动 发布订阅 string 订阅 can 长度 number 认证 运行
原文地址：https://www.cnblogs.com/123why/p/13121244.html
