Skip to content
An embeddable, language agnostic Push language interpreter
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
.circleci
deploy
doc
docs
resources
src/plushi
test/plushi
.gitignore
CHANGELOG.md
LICENSE
README.md
project.clj

README.md

plushi

CircleCI

Plushi is an embadable language agnostic push interpreter capable of running push programs via JSON interface.

Push is a programming language designed for AI systems to write software in. It has virtually no syntax and supports all common data types and can express a variety of control structures and data structures.

To read more about the push language, see the Push Redux.

Installation

Download the standalone jar from https://github.com/erp12/plushi/releases.

To build your own standalone jar, clone the repository and run the following leiningen commands.

lein deps
lein uberjar

For easy integration with Clojure projects, a public clojars release coming soon!

Usage

The Plushi interpreter is wrapped in an HTTP server written using ring. Any environment capable of making POST requests can use Plushi. JVM languages can also attempt to use plushi via inerop, although this is not the primary design goal.

Starting the Plushi Server

To start the plushi HTTP server, simply run the jar with the --start flag.

java -jar plushi-0.1.0-standalone.jar --start
# or
$ java -jar plushi-0.1.0-standalone.jar -s

The default port is 8075. To specify the port number, supply the --port flag followed by a valid port number.

java -jar plushi-0.1.0-standalone.jar --start --port 8076
# or
$ java -jar plushi-0.1.0-standalone.jar -s -p 8076

Request Actions

All of the actions required to synthesis plushi programs are available via POST requests to the plushi HTTP server. Other applications can send JSON blobs that describe what action the plushi server should take.

Getting the Supported Instructions

The Plushi interpreter supports a set of instructions which can appear in programs along side literals (ints, floats, strings, booleans). These instructions and literals in a linear sequence is a "plush program" which can be executed by the plushi interpreter.

To request the Plushi instruction set, the JSON blob in the request body must have 2 keys: "action" and "arity". The value of the "action" key must be "instructions" and the value of the "arity" key should be an integer denoting how many inputs the programs you would like to generate will accept.

Below is an example of this in python.

import json, requests
instr_set = requests.post("http://localhost:8075/", json=json.dumps({
  'action': 'instructions',
  'arity': arity
})).json()

Getting the Supported Types

Depending on what kinds of programs you intend on synthesizing, it maybe be helful to know what kinds of data types the Plushi interpreter is capable of manipulating. The "types" action returns this information on requst.

Below is an example of this in python.

import json, requests
plushi_types = requests.post("http://localhost:8075/",
                             json=json.dumps({'action': 'types'})).json()

Running a Plushi Program

If the value associated with the "action" key is "run" then Plushi will expect to be running a given plush program.

Below is an example of request made through python. All of the required and optional values are described in detail in the paragraphs below.

import json, requests
X = json.load("data.json")
request_body = {
  'action': 'run',
  'code': [1, 2, "plushi:integer_add"],
  'arity': 1,
  'output-types': ['integer'],
  'dataset': X
}
outputs = requests.post("http://localhost:8075/",
                        json=json.dumps(request_body)).json()

"code"

The value for the "code" key should be a flat list containing valid plushi atoms. A valid plushi atom can be any of the following:

  • an integer
  • a float
  • a boolean
  • a string

If a string atom is equal to a name of any instruction (ie "plushi:float_mult") Plushi will assume that the atom at that position should be the instruction. Otherwise the string (or any other atom) will be assumed to be a literal.

Unlike other implemenations of the the Push language, Plushi programs are always linear. Certain instructions (ie. exec_if) assume that the subsequent atom is a nested Push expression (or "code block"). Plushi has a dedicated instruction called close which denotes the closing of a code block. Using these instructions a linear Plushi program can be translated into a traditional, executable Push program. If no code blocks are open, the close instructions are a noop.

"arity"

An integer denoting how many inputs the program specified by "code" will expect. This is also the number of features in the dataset.

"output-types"

A list of plushi types to return after program execution. If more than one value of a certain type should be output, that type name should appear in the list multiple times.

For example a program which returns two integer and a string should set the "output-types" value to ["integer", "integer", "string"].

"dataset"

Plushi is designed to be used inside of inductive machine learning frameworks. Thus, it is expected that each program will need to be run on an entire dataset of inputs for evaluation.

The value of the "dataset" key is expected to be a list of JSON objects. Each JSON object is one record in the dataset with the keys being feature names and values being feature values.

[
  {"name" : "Alice", "age": 31},
  {"name" : "Bob", "age": 45},
  {"name" : "Cathy", "age": 24},
]

The dataset should not contain the training label you are trying to predict. Currently Plushi only requires you specify the arity of the program, not the names of which feature to use, and thus Plushi may use your label as an input by mistake.

Examples

Below is a list of other projects which use Plushi:

  • plushi-annealing - A simple simulated annealing algorithm for synthesizing Plushi programs.

Contributing

All contributions and ideas are strongly encouraged!

To see the list of proposed new features and changes, check the issues on the project's issues. Feel free to open new issues with any ideas or suggestions.

If you would like to contribute to either the source code or the documentation, please follow the "GitHub Flow" which is simply summarized here.

TLDR:

  1. Fork the official repository.
  2. Create a branch for your contribution.
  3. Make commits (Including tests).
  4. Open a pull request and await review and merge.

License

Copyright © 2018 Edward Pantridge

Distributed under the Eclipse Public License either version 1.0 or (at your option) any later version.

You can’t perform that action at this time.