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README
Apache-2.0

PyWorkflow(PyWF) - A Python Binding of C++ Workflow

License Language PyPI - Python Version PyPI

概览

C++ Workflow是一个高性能的异步引擎,本项目着力于实现一个Python版的Workflow,让Python用户也能享受Workflow带来的绝佳体验。

快速上手

在用户深入了解Workflow相关概念之前,先来看几个简单的示例,可以对使用方法有一个初步印象。pywf是本项目Python包的名称,在文档中有时会直接使用wf作为其简称。

发起一个Http请求

import pywf as wf

def http_callback(http_task):
    resp = http_task.get_resp()
    print("Http status:{}\n{}".format(
        resp.get_status_code(), resp.get_body())) # body is bytes

http_task = wf.create_http_task("http://www.sogou.com/", redirect_max=4, retry_max=2, callback=http_callback)
http_task.start()
wf.wait_finish()

依次发起多个Http请求

import pywf as wf

def series_callback(s):
    print("All task in this series is done")

def http_callback(http_task):
    req = http_task.get_req()
    resp = http_task.get_resp()
    print("uri:{} status:{}".format(
        req.get_request_uri(),
        resp.get_status_code()))

def create_http_task(url):
    return wf.create_http_task(url, 4, 2, http_callback)

first_task = create_http_task("http://www.sogou.com")
series = wf.create_series_work(first_task, series_callback)
series.push_back(create_http_task("https://www.zhihu.com/people/kedixa"))
series.push_back(create_http_task("https://fanyi.sogou.com/document"))
series.start()
wf.wait_finish()

同时发起多个Http请求

import pywf as wf

def parallel_callback(p):
    print("All series in this parallel is done")

def http_callback(http_task):
    req = http_task.get_req()
    resp = http_task.get_resp()
    print("uri:{} status:{}".format(
        req.get_request_uri(),
        resp.get_status_code()))

url = [
    "http://www.sogou.com",
    "https://www.zhihu.com/people/kedixa",
    "https://fanyi.sogou.com/document"
]
parallel = wf.create_parallel_work(parallel_callback)
for u in url:
    task = wf.create_http_task(u, 4, 2, http_callback)
    series = wf.create_series_work(task, None) # without callback
    parallel.add_series(series)
parallel.start()

wf.wait_finish()

基本概念

任务

通过create_xxx_task等工厂函数创建的对象称作任务(task),例如create_http_task。一个任务被创建后,必须被启动或取消,通过执行http_task.start(),会自动以http_taskfirst_task创建一个串行并立即启动任务。如果用户指定了回调函数,当任务完成时回调函数会被调用,但在任务启动后且回调函数前,用户不能再操作该任务。当回调函数结束后,该任务被立即释放,用户也不能再操作该任务。

串行

通过create_series_work创建的对象称作串行(series),用户在创建时需要指定一个first_task来作为启动该series启动时应当执行的任务,用户可选地指定一个回调函数,当所有任务执行完成后,回调函数会被调用。

series的回调函数用于通知用户该串行中的任务均已完成,不能再继续添加新的任务,且回调函数结束后,该串行会立即被销毁。

并行

通过create_parallel_work创建的对象称作并行(parallel),用户可以创建一个空的并行,然后通过add_series接口向并行中添加串行,也可以在创建时指定一组串行。并行本身也是一种任务,所以并行也可以放到串行中。parallel.start()就会自动创建一个串行,并将parallel作为first_task立即开始执行。

parallel的回调函数用于通知用户该并行中的串行均已完成,不能再继续添加新的串行,且回调函数结束后,该并行会立即被销毁。

有了上述三个概念,就可以构建出各种复杂的任务结构,并在Workflow的管理下高效执行。

详细说明

设计理念

Workflow认为,一个典型的后端程序由三个部分组成,并且完全独立开发。即:程序=协议+算法+任务流。

  • 协议
    • 大多数情况下,用户使用的是内置的通用网络协议,例如http,redis或各种rpc。
    • PyWF未支持用户自定义协议。
  • 算法
    • 算法是与协议对称的概念。
    • 如果说协议的调用是rpc,算法的调用就是一次apc(Async Procedure Call)。
    • 任何一次边界清晰的复杂计算,都应该包装成算法。
  • 任务流
    • 任务流就是实际的业务逻辑,就是把开发好的协议与算法放在流程图里使用起来。
    • 典型的任务流是一个闭合的串并联图。复杂的业务逻辑,可能是一个非闭合的DAG。
    • 任务流图可以直接构建,也可以根据每一步的结果动态生成。所有任务都是异步执行的。

Python Workflow将会逐步支持Workflow的六种基础任务:通讯,文件IO,CPU,GPU,定时器,计数器。

注意事项

  • 框架本身不抛出异常,也未处理任何异常,所以用户需要保证回调函数不会抛出异常,context的构造和析构不抛出异常。
  • 所有通过工厂函数创建出的task,必须start、dismiss或添加至一个series中。
  • 所有创建出的series必须start、dismiss或添加至一个parallel中。
  • 所有创建出的parallel必须start、dismiss或添加至一个series中。
  • 由PyWF工厂函数创建的对象的生命周期均由内部管理,在Python层面仅是一个引用,用户不能使用超出生命周期的对象。
  • 用户使用大部分get接口获取的对象可以自由使用,例如Http中的get_body

构建和安装

通过pip安装

本项目仅支持Python3.6以上,正在准备发布一组manylinux2014版本,用户即将可以通过较高版本的pip直接安装。

# We are working on it
pip3 install pywf

编译安装

用户可以下载本项目源码进行编译安装。

# CentOS 7
yum install cmake3 ninja-build python36 python36-devel python36-pip
yum install gcc-c++ # if needed
git clone https://github.com/sogou/pyworkflow --recursive
cd pyworkflow
pip3 install wheel
python3 setup.py bdist_wheel
pip3 install dist/*.whl --user
# CentOS 8
yum install cmake ninja-build python36 python36-devel python3-pip
git clone https://github.com/sogou/pyworkflow --recursive
cd pyworkflow
pip3 install wheel
python3 setup.py bdist_wheel
pip3 install dist/*.whl --user
# Mac
# Build Requirement
brew install ninja cmake openssl
pip3 install wheel

# OpenSSL Env, see 'brew info openssl' for more infomation
echo 'export PATH="/usr/local/opt/openssl@1.1/bin:$PATH"' >> ~/.bash_profile
echo 'export LDFLAGS="-L/usr/local/opt/openssl@1.1/lib"' >> ~/.bash_profile
echo 'export CPPFLAGS="-I/usr/local/opt/openssl@1.1/include"' >> ~/.bash_profile
echo 'export PKG_CONFIG_PATH="/usr/local/opt/openssl@1.1/lib/pkgconfig"' >> ~/.bash_profile
echo 'export OPENSSL_ROOT_DIR="/usr/local/opt/openssl@1.1/"' >> ~/.bash_profile

# zsh Env, if needed
echo 'test -f ~/.bash_profile  && source ~/.bash_profile' >> ~/.zshrc
source ~/.zshrc

# Build
git clone https://github.com/sogou/pyworkflow --recursive
cd pyworkflow
python3 setup.py bdist_wheel
pip3 install dist/*.whl --user
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简介

Python异步任务编排框架。支持http,redis和MySQL异步任务,异步文件IO。Python下最快的http server之一。 展开 收起
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