Simple python workflow engine based on asyncio and a DAG structure.
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README.md

Travis

Pyperator

Pyperator is a simple python workflow library based on asyncio. Freely inspired by other flow-based programming tools such as noflo scipipe and many others. A network of components communicating through named ports is build; the execution happens asynchronously by scheduling all processes and sending/receving on the input/output ports.

Simple example

A simple example workflow summing two numbers and printing the result can be built as follows:

        from pyperator.DAG import  Multigraph
        from pyperator.components import GeneratorSource, ShowInputs, BroadcastApplyFunction, ConstantSource, Filter, OneOffProcess
        from pyperator import components
        from pyperator.nodes import Component
        from pyperator.utils import InputPort, OutputPort, FilePort, Wildcards
        #Sum function
        def adder(**kwargs):
                out = sum([item for k, item in kwargs.items() if item])
                return out
        #Create two source generating data from generator compherensions
        source1 = GeneratorSource('s1',  (i for i in range(100)))
        source2 = GeneratorSource('s2',  (i for i in range(100)))
        #Add a printer to display the result
        shower = ShowInputs('printer')
        #add input port
        shower.inputs.add(InputPort('in1'))
        #Function that applies a function of all input packets and sends it to all output ports
        summer = BroadcastApplyFunction('summer', adder )
        #Add ports
        summer.inputs.add(InputPort('g1'))
        summer.inputs.add(InputPort('g2'))
        summer.outputs.add(OutputPort('sum'))
        #Initialize DAG
        graph = Multigraph()
        #Connect ports
        graph.connect(source1.outputs.OUT, summer.inputs.g1)
        graph.connect(source2.outputs.OUT, summer.inputs.g2)
        graph.connect(summer.outputs.sum, shower.inputs.in1)
        #Execute dag
        graph()

How to use Pyperator

Creating a pyperator workflow requires three steps:

  1. Define/import components
  2. Define input/output ports
  3. create a graph by connecting ports

Define components

Each pyperator component should be built subclassing pyperator.nodes.Component, which is in turn subclassed from the AbstractComponent, which has __call__ as a abstract method. Your component should implement the __call__ coroutine. An example of a simple component summing the content of the packets received in "IN1" and "IN2":

from pyperator import components
from pyperator.nodes import Component
from pyperator.utils import InputPort, OutputPort, FilePort, Wildcards
from pyperator.IP import InformationPacket
from pyperator.DAG import  Multigraph
import asyncio
import random

class Summer(Component):
    """
    This is a component that sums the value of the recieved packets
    """

    def __init__(self, name):
        super(Summer, self).__init__(name)
        self.inputs.add(InputPort("IN1"))
        self.inputs.add(InputPort("IN2"))
        self.outputs.add(OutputPort("OUT"))

    @log_schedule
    async def __call__(self):
        while True:
                in_packets_1 = await sefl.inputs.IN1.receive()
                in_packets_2 = await sefl.inputs.IN1.receive()
                #InformationPackets have the attribute "value" that contains the data
                summed = InformatioPacket(in_packets_1.value() + in_packets_2.value())
                await self.outputs.OUT.send_packet(summed)

To receive packets from a channel named "IN", you should use packet = await self.inputs.IN.receive_packet(). The input and output PortRegister support two forms of indexing:

  • Selecting ports using dict-style keys, i.e self.inputs["IN"]

  • Selecting them as attributes of the PortRegister, i.e self.inputs.IN

Likewise, sending packets is accomplished by issuing await self.outputs.OUT.send(packet).

Now, we define a second components that creates some interesting packets. This component will be a source component, it will not have any input ports and will generate packtes consisting of random numbers:

class RandomSource(Component):
        """
        This component generates random packets
        """
        def __init__(self, name):
                super(RandomSource, self).__init__(name)
                self.name = name
                self.outputs.add(OutputPort("OUT"))
                
        async def __call__(self):
                while True:
                        #generate IP containing random number
                        a = InformationPacket(random.random())
                        #send to the output port
                        await self.outputs.OUT.send_packet(a)
                        await asyncio.sleep(0)

Define Input/Output Ports

There are two main ways to add ports to a component:

  • Adding them when defining the component, using its init method:
class CustomComponent(Component):
    """
    This is my useless component
    """

    def __init__(self, name):
        super(CustomComponent, self).__init__(name)
        self._gen = generator
        self.outputs.add(OutputPort("OUT"))
        self.inputs.add(OutputPort("IN"))

this is what we have done before to define the Summer and the RandomSourcecomponents.

  • Adding ports to an existing compononent instance using the method add of the input and output PortRegister:
c1 = CustomComponent("test")
#This component already has one input and output ports.
c1.inputs.add.InputPort("IN1")
c1.outputs.add.OutputPort("OUT1")

Now, c1 will have two InputPorts, "IN" and "IN1" and two OutputPorts"OUT" and "OUT1".

Create a graph

Finally, several components can be tied together using a MultiGraph. In this case, we want to compute the sum of two random packets and print the result. To print the result we import the ShowInputs component from pyperator.components that will print the packet it receives from each port.

#Define a graph
g = Multigraph()

#Instantiate components

s1 = RandomSource("s1")
s2 = RandomSource("s2")
adder = Summer("sum_them")
printer = ShowInputs("show_it")
#The printer needs an input port
printer.inputs.add(InputPort("IN"))

#Now we connect the components

s1.outputs.OUT.connect(adder.inputs.IN1)
s2.outputs.OUT.connect(adder.inputs.IN2)
adder.outputs.OUT.connect(printer.inputs.IN)

#Now we need to add them to a Graph instance to be able to run them.

g.add_node(s1)
g.add_node(s2)
g.add_node(adder)
g.add_node(printer)

#We can vrun the computation by calling the graph
g()

Create a graph using magic methods

Pyperator also supports a nicer syntax to express graphs and connect ports. The same graph of the previous example can be expressed in a more suggestive way using:

#all nodes defined within this context manager will be automatically be added to the graph `g`
with Multigraph() as g:
        s1 = RandomSource("s1")
        s2 = RandomSource("s2")
        adder = Summer("sum_them")
        printer = ShowInputs("show_it")
        #The printer needs an input port
        printer.inputs.add(InputPort("IN"))
        #Connect 
        s1.outputs.OUT >> adder.inputs.IN1
        s2.outputs.OUT >> adder.inputs.IN2
        adder.outputs.OUT >> printer.inputs.IN
        
g()
        
        

Advanced example

In this example we will see how pyperator supports shell commands and files, including wildcards and the generation of dynamic filenames. Many of these features are inspired by scipipe.

        from pyperator.DAG import  Multigraph
        from pyperator.components import GeneratorSource, ShowInputs, BroadcastApplyFunction, ConstantSource, Filter, OneOffProcess
        from pyperator import components
        from pyperator.nodes import Component
        from pyperator.utils import InputPort, OutputPort, FilePort, Wildcards
        #Source
        source1 = GeneratorSource('s1', (i for i in range(5)))
        source2 = GeneratorSource('s2', (i for i in range(5)))
        toucher = components.Shell('shell', "echo '{inputs.i.value}, {inputs.j.value}' > {outputs.f1.path}")
        toucher.outputs.add(FilePort('f1'))
        toucher.inputs.add(InputPort('i'))
        toucher.inputs.add(InputPort('j'))
        toucher.DynamicFormatter('f1', "{inputs.j.value}_{inputs.i.value}.txt1")
        printer = ShowInputs('show_path')
        printer.inputs.add(FilePort('f2'))
        graph = Multigraph()
        graph.connect(source1.outputs.OUT, toucher.inputs.i)
        graph.connect(source2.outputs.OUT, toucher.inputs.j)
        graph.connect(toucher.outputs.f1, printer.inputs.f2)
        graph()