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The core providence library contains classes that should handle and enable the generated code, except for some special cases. It handles the descriptors, base classes for the models and model builder themselves and common utilities for working with the model classes. There are interfaces for using the services, but not the implementations for working with them, see providence-core-client and providence-core-server modules for more on using the services.

PS: Note that for the most part, the user should not need to worry about these libraries, with some exceptions.

Base Classes And Utilities

As described in providence models, there are generated methods for getting each field from the structures, and how to build it. But as providence is built to be self-reflective / self-describing, these same classes need more generic methods to be able to build and read the model content without relying on java reflection. Notable features are following.

PMessage and PMessageBuilder

All structures implements a base interface called the PMessage. It has utility methods to dynamically check and get the content of the message. Both classes have a descriptor() method that returns the descriptor for the message. See below for details. Also the message implementation class will always have a kDescriptor constant containing the same.

The functionality of the PMessage is basically only the get(i), has(i) methods, and the more notable:

  • mutate(): Returns a builder that further builds upon / mutates the content from the instance.
  • mergeWith(Message other): Essentially just mutate().merge(other).build(), but handy to have in order to quickly make messages by merging two of the same type.

The PMessageBuilder has a bit more features to be noted. These are added mainly in order to facilitate “smarter” ways or handling updates and changes.

  • valid() and validate() checks if, and fails if not (respectively) the current content of the message builder constitutes a valid message when comparing it to the field requirements of the type.
  • isSet(field) and presentFields() are respectively returning true if the specified field has a value, and the list of fields that has a value at time of calling.
  • isModified(field) and modifiedFields() are respectively returning true if the specified field has been modified since the builder was created, and the list of fields that has been modified since the builder was created at time of calling.
  • mutator(field) returns a contained PMessageBuilder for the specified field. The returned builder is “contained” in the outer builder so that any modifications to this builder will affect the contained message. Corresponds to the mutableMyField() (if field named ‘my_field’) method.


As noted above, providence is self-describing. This is done via a set of PDeclaredDescriptor implementations, one for each generated base class. As a user, you should usually only need to know that all the generated classes have a kDescriptor constant, which is passed into serializers and other utilities to represent the type.

The descriptors also have some niceties that can be used to represent the generated class.


Serialization and deserialization of providence models are done through the Serializer interface. It’s main interface are the serialize and deserialize methods. Both methods will to it’s job and return if and only if the read or write operations succeeded.

  • int serialize(OutputStream os, PMessage m): Serialize message with the serializer onto the output stream. Since the message is self-describing no descriptor is needed. It should return the number of bytes written.
  • T deserialize(InputStream is, PDescriptor<T> t): Read an object of type T with the descriptor t from the input stream. The object does not have to be a Message, any serializable type should work.

The available serializers are as follows:

  • BinarySerializer: A native providence version of thrift’s TBinaryProtocol binary format. It should generate the same serialized data as TBinaryProtocol, and be able to parse data back from the same. It is the default serializer in the pvdrpc tool. See binary serializer spec for details.
  • FastBinarySerializer: A compact and efficient serialization format. The serializer is designed to have a balance of computational and data efficiency. See fast binary serializer spec for details.
  • JsonSerializer: A general purpose JSON serializer. This should be able to read most generic JSON formats into providence structs that match with name to field type mapping. See json serializer spec for details.
  • PrettySerializer: A serializer format for making and reading a pure human readable format. The format is also used in the providence config, but with some extra features. See providence-config for details on the pretty config format.

Serializer Providers

Often when using serializers a system may need to be able to select a fitting serializer for the current task. This is done with the SerializerProvider interface, which simply lets a service get a serializer based on a media type string.

A Note on Strictness

All of the base serializers have a strict option. And this controls how strict the parser or generator can be when reading and writing the messages. In essence:

  • If strict is true, only data accepted by the generated code made by apache thrift will be accepted. Meaning:
    • If a required field in a message is missing, reading it will fail. E.g. validation failure.
    • If a map key or set value cannot be resolved, it will be ‘null’ and fail reading. This is mostly only applicable to enums reading an unknown value.
  • Otherwise the failures above will be handled as:
    • required fields are handled as if they were optional_in_required_out, a.k.a. default requirement.
    • Unresolved enum values for map keys and set values are just ignored.
  • If strict is false, the examples above will be accepted, but a number of other issues will still fail reading a message:
    • If any value does not have a compatible wire format to it’s described type, the read will fail. This may happen if fields change type, or if two separate services have added a field with the same ID (or name for some serializers).
    • If any value fails to be parsed (for the requested type), e.g. bad string utf-8 entities, too large (or small) number for parsed i* types, etc.

Writing a message should only fail if writing to the stream fails. A message usually cannot contain an invalid value, since fields are validated on construction by the builder.

Example use of Serialization.

In the simplest form, serializers are used plainly on input and output streams.

class Example {
    void write(MyMessage message) {
        BinarySerializer serializer = new BinarySerializer();
        FileOutputStream out = new FileOutputStream(new File(""));
        serializer.serialize(out, message);

    MyMessage read() {
        BinarySerializer serializer = new BinarySerializer();
        FileInputStream in = new FileInputStream(new File(""));
        return serializer.deserialize(in, MyMessage.kDescriptor);

Message I/O

Since using the Serializers require knowing more about the source of and how to handle multiple message in one etc, there is a MessageIO library that simplifies some common tasks. The interface is mostly a simplification of use of the Serializers, making specialized MessageReader and MessageWriter classes.

  • IOMessageReader and IOMessageWriter are simply wrappers around input stream and output stream that handles streaming multiple messages, with optional internal separators (e.g. for JSON).
  • FileMessageReader and FileMessageWriter writes to and reads from a single file that is appended to and read from as a stream of messages, also with optional internal separators.


Convenience methods for creating java 8 streams from an input stream containing providence data. These are mostly for convenience, but with added handling of a stream of content, meaning multiple messages in a row in the same stream. It is mostly just wrappers around the two MessageReader & MessageWriter implementations.

  • MessageStreams.file(File f, PSerializer s, PDescriptor d): Consume messages from the file using the given serializer one at a time onto the stream.
  • MessageStreams.resource(String r, PSerializer, s, PDescriptor d): Consume messages from the java resource using the given serializer one at a time onto the stream.
  • in, PSerializer, s, PDescriptor d): Consume messages from the input stream using the given serializer one at a time onto the stream.
  • MessageCollectors.toFile(File f, PSerializer s): Collect messages and write them to file with the given serializer.
  • MessageCollectors.toStream(OutputStream os, PSerializer s): Collect messages and write them to the given output stream with the given serializer.


If you need a simple data storage layer for providence messages, take a look at the storage module, or for use with DBI see JDBI v2 or v3 modules.