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  • Pipy Documentation
  • Introduction
    • Overview
    • Concepts
  • Getting Started
    • Build and Install
    • Quick Start
    • Getting help
  • Release
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      • 0.10.0-1
      • 0.22.0-31
      • 0.30.0
      • 0.50.0
  • Tutorial
    • Part 1: Hello
    • Part 2: Echo
    • Part 3: Proxy
    • Part 4: Routing
    • Part 5: Loading Balancing
    • Part 6: Configuration
    • Part 7: Plugins
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    • PipyJS
      • Language
      • Builtin Objects
      • NMI

    NMI

    Pipy is able to dynamically load and run an external module written in C via NMI (Native Module Interface). Since it's pure C interface, it also allows other languages that have a native C interface to interoperate with Pipy.

    A native module hooked up into Pipy can do the following things:

    • Define custom native pipelines
    • Receive input events coming to a native pipeline
    • Output events from a native pipeline
    • Define/access/export (but not import) context variables related to a native pipeline's current context

    Define a native module

    For a native module to be utilized by Pipy, it needs to be a dynamically-loadable shared library that exports one single entrance function under the name pipy_module_init. Inside the function, you call pipy_define_variable and pipy_define_pipeline to tell Pipy what variables and pipelines your native module has.

    All types and functions that NMI provides for native modules can be found in header file include/pipy/nmi.h.

    Variable definition

    Call pipy_define_variable to define a context variable being used by the native module. You can call this function multiple times to define multiple variables.

    Each variable definition needs the following information:

    • id - An integer for referring the variable in C code directly and efficiently. Module developers should make sure this ID is unique among all variables within a module. Better have consecutive increasing numbers starting from 0.
    • name - Name of the variable seen by PipyJS.
    • ns - When given, the namespace this variable is exported to. The variable won't be visible to other modules if ns is NULL.
    • value - The initial value.

    For how to create an initial value for a variable definition, see Operating pjs_value.

    Pipeline definition

    Call pipy_define_pipeline to define a pipeline the native module provides. You can call this function multiple times to define multiple pipelines under different names.

    Each pipeline definition needs the following information:

    • name - Name under which the pipeline can be referred to from PipyJS. It can be an empty string for the entrance pipeline, which is the pipeline that can be referred to by only the module name and without a pipeline name.
    • init - Function to be called when a pipeline instance is created.
    • free - Function to be called when a pipeline instance is destroyed.
    • process - Function to be called when an event arrives to a pipeline instance.

    Pipeline implementation

    The implementation of a native pipeline sits in the 3 callback functions provided in the definition.

    Lifecycle management

    2 of the 3 callbacks, fn_pipeline_init and fn_pipeline_free namely, are for lifecycle management. When a native pipeline is created, fn_pipeline_init will be called. When a native pipeline is destroyed, fn_pipeline_free will be called. Both functions have the pipeline instance ID as their first argument.

    When a pipeline is being created, you can optionally provide a user pointer of any type via the 2nd parameter to fn_pipeline_init. The pointer you give will be bound to the pipeline instance and will be presented to the other 2 callback functions each time they are called for this specific pipeline instance. That way, you can attach any types of user data you need to a pipeline instance.

    The allocation of user data is not under control of Pipy. It relies completely on user code. So make sure to free the allocated data in callback fn_pipeline_free when the pipeline using it is destroyed.

    Event handling

    A native pipeline handles its input events in callback fn_pipeline_process. It receives 3 arguments:

    • Pipeline ID
    • Pointer to the user data (provided by fn_pipeline_init)
    • An event object

    The event object is given as a pjs_value. It can be an object of one of the 4 event types:

    See Operating pjs_value for how to use pjs_value.

    NMI provides the following functions for deciding what type the event really is:

    int pipy_is_Data(pjs_value obj);
    int pipy_is_MessageStart(pjs_value obj);
    int pipy_is_MessageEnd(pjs_value obj);
    int pipy_is_StreamEnd(pjs_value obj);

    The following functions are provided for accessing these event objects:

    pjs_value pipy_Data_push(pjs_value obj, pjs_value data);
    pjs_value pipy_Data_pop(pjs_value obj, int len);
    pjs_value pipy_Data_shift(pjs_value obj, int len);
    int pipy_Data_get_size(pjs_value obj);
    int pipy_Data_get_data(pjs_value obj, char *buf, int len);
    pjs_value pipy_MessageStart_get_head(pjs_value obj);
    pjs_value pipy_MessageEnd_get_tail(pjs_value obj);
    pjs_value pipy_MessageEnd_get_payload(pjs_value obj);
    pjs_value pipy_StreamEnd_get_error(pjs_value obj);

    While you process an input event in fn_pipeline_process, you can generate new events as the pipeline's output. This is done through a call to function pipy_output_event. The function requires 2 arguments: the ID of the pipeline you want to output from, and an event object as a pjs_value. You can pass in any existing event objects, or create a new event object with one of the following functions:

    pjs_value pipy_Data_new(const char *buf, int len);
    pjs_value pipy_MessageStart_new(pjs_value head);
    pjs_value pipy_MessageEnd_new(pjs_value tail, pjs_value payload);
    pjs_value pipy_StreamEnd_new(pjs_value error);

    You can also access any variables related to the pipeline's current context by using the following 2 functions:

    void pipy_get_variable(pipy_pipeline ppl, int id, pjs_value value);
    void pipy_set_variable(pipy_pipeline ppl, int id, pjs_value value);

    Both of the above functions receive 3 arguments:

    • ID of the pipeline instance
    • ID of the variable to access (as defined in pipy_module_init when module starts)
    • A pjs_value giving or receiving the value

    Operating pjs_value

    From the view point of NMI, every piece of information you get from or give to Pipy is pjs_value. It's crucial to understand how pjs_value works to interoperate with Pipy.

    Types of pjs_value

    A pjs_value represents a value in PipyJS, so its type system also resembles the same type system being used by PipyJS, which includes the following basic types:

    • Undefined
    • Boolean (true or false)
    • Number (64-bit floating numbers)
    • String (A sequence of Unicode characters)
    • Object (A generic key-value container with optional methods to operate its internal state)

    An array object is also an object. Therefore, array in itself is not a distinct basic type. Compared to other types of objects, an array only has array-specific methods to operate the elements it contains.

    Scope of pjs_value

    By default, a pjs_value, either created within a function or received as a function argument, is in local scope. That means, the value will only be valid inside the current function. When execution exits from the current function, Pipy will make sure all local scope values are freed promptly.

    If a pjs_value needs to stay alive outside of its local scope, for instance, when it is assigned to a C struct allocated in the heap, you need to pjs_hold it to let Pipy know that it's still in use. Also, when the value is no longer needed, don't forget to pjs_free it so that no memory leaks could happen.

    That being said, when a value is assigned to a PipyJS container object such as an object or an array instead of a C struct, don't worry about pjs_hold since reference counting is done automatically by those PipyJS objects internally.

    Operations on pjs_value

    Creation

    Use the following functions to create various types of pjs_value:

    pjs_value pjs_undefined();
    pjs_value pjs_boolean(int b);
    pjs_value pjs_number(double n);
    pjs_value pjs_string(const char *s, int len);
    pjs_value pjs_object();
    pjs_value pjs_array(int len);

    Type checking

    Use the following functions to obtain type information of a pjs_value:

    pjs_type pjs_type_of(pjs_value v);
    int pjs_class_of(pjs_value v);
    int pjs_class_id(const char *name);
    int pjs_is_undefined(pjs_value v);
    int pjs_is_null(pjs_value v);
    int pjs_is_nullish(pjs_value v);
    int pjs_is_empty_string(pjs_value v);
    int pjs_is_instance_of(pjs_value v, int class_id);
    int pjs_is_array(pjs_value v);
    int pjs_is_function(pjs_value v);

    Generic value operations

    You can clone or check equality of values of any type with these functions:

    pjs_value pjs_copy(pjs_value v, pjs_value src);
    int pjs_is_equal(pjs_value a, pjs_value b);
    int pjs_is_identical(pjs_value a, pjs_value b);

    String operations

    If a pjs_value is a string, the following functions can be used on it:

    int pjs_string_get_length(pjs_value str);
    int pjs_string_get_char_code(pjs_value str, int pos);
    int pjs_string_get_utf8_size(pjs_value str);
    int pjs_string_get_utf8_data(pjs_value str, char *buf, int len);

    Object operations

    If a pjs_value is an object, the following functions can be used on it:

    int pjs_object_get_property(pjs_value obj, pjs_value k, pjs_value v);
    int pjs_object_set_property(pjs_value obj, pjs_value k, pjs_value v);
    int pjs_object_delete(pjs_value obj, pjs_value k);
    void pjs_object_iterate(pjs_value obj, int (*cb)(pjs_value k, pjs_value v));

    Array operations

    If a pjs_value is an array object, the following functions can be used on it:

    int pjs_array_get_length(pjs_value arr);
    int pjs_array_set_length(pjs_value arr, int len);
    int pjs_array_get_element(pjs_value arr, int i, pjs_value v);
    int pjs_array_set_element(pjs_value arr, int i, pjs_value v);
    int pjs_array_delete(pjs_value arr, int i);
    int pjs_array_push(pjs_value arr, pjs_value v);
    pjs_value pjs_array_pop(pjs_value arr);
    pjs_value pjs_array_shift(pjs_value arr);
    int pjs_array_unshift(pjs_value arr, pjs_value v);
    pjs_value pjs_array_splice(pjs_value arr, int pos, int del_cnt, int ins_cnt, pjs_value v[]);

    Calling from PipyJS

    Native modules are loaded and dynamically linked to the Pipy main executable via a use() filter. It's similar to loading a PipyJS module, where all you have to provide to the filter as parameters are a filename and an optional pipeline name.


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