|
| 1 | +# Customization |
| 2 | + |
| 3 | +Papercast is designed to be extensible. |
| 4 | + |
| 5 | +## Creating a Pipeline Component |
| 6 | + |
| 7 | +The most straightforward customization is to create a new pipeline component. Pipeline Components are the building blocks of Papercast pipelines. There are three base classes that Pipeline Components can inherit from: `BaseProcessor`, `BaseSubscriber`, and `BasePublisher`. |
| 8 | + |
| 9 | +### BaseProcessor |
| 10 | + |
| 11 | +`BaseProcessor` is a base class for Pipeline Components that process a document or document identifier and return an updated document. `BaseProcessor` has two class attributes, `input_types` and `output_types`, which define the expected input and output of the Pipeline Component. |
| 12 | + |
| 13 | +Subclasses of `BaseProcessor` must implement the abstract `process` method, which takes an instance of `Production` as input and returns an instance of `Production`. The `process` method should contain the logic for processing the input document and returning an updated document. |
| 14 | + |
| 15 | +```python |
| 16 | +@abstractmethod |
| 17 | +def process(self, input: Production, *args, **kwargs) -> Production: |
| 18 | +``` |
| 19 | + |
| 20 | +### BaseSubscriber |
| 21 | + |
| 22 | +`BaseSubscriber` is a base class for Pipeline Components that initiate document processing based on external events, like a webhook. Subclasses of `BaseSubscriber` must implement the abstract `subscribe` method, which should contain the logic for subscribing to the external event and triggering document processing. |
| 23 | + |
| 24 | +```python |
| 25 | +@abstractmethod |
| 26 | +async def subscribe(self) -> Production: |
| 27 | +``` |
| 28 | + |
| 29 | +### BasePublisher |
| 30 | + |
| 31 | +`BasePublisher` is a base class for Pipeline Components that publish documents to an external system. `BasePublisher` has one class attribute, `input_types`, which defines the expected input of the Pipeline Component. |
| 32 | + |
| 33 | +Subclasses of `BasePublisher` must implement the abstract `process` method, which takes an instance of `Production` as input and publishes it to an external system. The `process` method should contain the logic for publishing the input document. |
| 34 | + |
| 35 | +```python |
| 36 | +@abstractmethod |
| 37 | +def process(self, input: Production, *args, **kwargs) -> None: |
| 38 | +``` |
| 39 | + |
| 40 | +## Step 1: Choose a Base Class |
| 41 | + |
| 42 | +**Processor:** Choose this if you want to process a document or document identifier and return an updated document. |
| 43 | + |
| 44 | +**Subscriber:** Choose this if you want to initiate document processing based on external events, like a webhook. |
| 45 | + |
| 46 | +**Publisher:** Choose this if you want to publish documents to an external system. |
| 47 | + |
| 48 | + |
| 49 | +## Step 2: Create the Component |
| 50 | + |
| 51 | +To create a new Pipeline Component, you will need to create a new Python class that inherits from one of the base classes: `BaseProcessor`, `BaseSubscriber`, or `BasePublisher`. |
| 52 | + |
| 53 | +For example, to create a new Processor, you can create a class that inherits from `BaseProcessor`: |
| 54 | + |
| 55 | +```python |
| 56 | +class MyProcessor(BaseProcessor): |
| 57 | + input_types = {"my_input": str} |
| 58 | + output_types = {"my_output": str} |
| 59 | + |
| 60 | + def process(self, input: Production, *args, **kwargs) -> Production: |
| 61 | + """ |
| 62 | + Processes a document by returning the input string with "processed" appended. |
| 63 | +
|
| 64 | + Args: |
| 65 | + input (Production): The input document containing a "my_input" attribute. |
| 66 | +
|
| 67 | + Returns: |
| 68 | + Production: The processed document containing a "my_output" attribute. |
| 69 | + """ |
| 70 | + input_string = getattr(input, "my_input") |
| 71 | + processed_string = f"{input_string} processed" |
| 72 | + output = Production(my_output=processed_string) |
| 73 | + return output |
| 74 | +``` |
| 75 | + |
| 76 | +In this example, `MyProcessor` inherits from `BaseProcessor` and defines the expected input and output types using the `input_types` and `output_types` class attributes. It also implements the `process` method to perform the processing logic and return the processed document. |
| 77 | + |
| 78 | +You can customize the implementation of the `process` method to suit your specific use case. Once your new Pipeline Component is defined, you can instantiate it and use it as part of a Pipeline to perform your desired document processing. |
| 79 | + |
| 80 | +## Step 3: Define Input and Output Types |
| 81 | + |
| 82 | +When defining a new Pipeline Component, you will need to specify the expected input and output types of the component. This is done using the `input_types` and `output_types` class attributes, which are dictionaries that map attribute names to their expected data types. |
| 83 | + |
| 84 | +For example, to define the input and output types for a custom Processor that takes a string as input and returns an integer as output, you can define the class like this: |
| 85 | + |
| 86 | +```python |
| 87 | +class MyProcessor(BaseProcessor): |
| 88 | + input_types = {"input_string": str} |
| 89 | + output_types = {"output_int": int} |
| 90 | + |
| 91 | + def process(self, input: Production, *args, **kwargs) -> Production: |
| 92 | + """ |
| 93 | + Processes a document by converting the input string to an integer and returning it. |
| 94 | +
|
| 95 | + Args: |
| 96 | + input (Production): The input document containing an "input_string" attribute. |
| 97 | +
|
| 98 | + Returns: |
| 99 | + Production: The processed document containing an "output_int" attribute. |
| 100 | + """ |
| 101 | + input_string = getattr(input, "input_string") |
| 102 | + output_int = int(input_string) |
| 103 | + output = Production(output_int=output_int) |
| 104 | + return output |
| 105 | +``` |
| 106 | + |
| 107 | +In this example, `MyProcessor` defines the expected input and output types using the `input_types` and `output_types` class attributes. The `input_types` attribute specifies that the input document should have an attribute named "input_string" that is of type `str`. The `output_types` attribute specifies that the processed document should have an attribute named "output_int" that is of type `int`. |
| 108 | + |
| 109 | +You can customize the input and output types of your Pipeline Component to match your specific use case. |
| 110 | + |
| 111 | + |
| 112 | +## Step 4: Share your Pipeline Component (Optional) |
| 113 | + |
| 114 | +If you would like to share your Pipeline Component with the Papercast community, you can follow the steps at the [contributing guide](./contributing.md). |
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