What s different about Factor?
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- Wilfred Higgins
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1 Harshal Lehri
2 What s different about Factor? Factor is a concatenative programming language - A program can be viewed as a series of functions applied on data Factor is a stack oriented program - Data in Factor is stored on a stack - functions pop data from the stack and the output data is pushed on the same stack Factor uses an Image-based persistence model - the program code and data are saved in an image file, similar to core dumps Built in Foreign Function Interface that allows it to talk to declarative programs like C, Objective-C and Fortran
3 A Practical stack oriented language Factor supports popular functional programming concepts like currying and higher order functions( like map, reduce, filter) Factor supports object-oriented programming - via tuples and generic words Factor is dynamically typed and has a type system Factor supports powerful meta programming capabilities using parsing words Garbage collection, optimizing compiler, nice REPL, large standard library and more...
4 Concatenative Programming A program can be written as a chain of functions applied one after another, each modifying data before passing it to the next one Unix pipes are a good example of concatenative programming Unix pipes use a Queue to store intermediate results while Factor uses a Stack
5 Concatenative Programming- An Example Consider a Unix command like cat file1.txt grep filter-text awk {print $1} The program reads contents of file, filters lines containing the word filter-text and prints the word before the first whitespace in the line cat file1.txt File data grep filter-text Filtered Lines awk {print $1}
6 Words and Vocabularies Functions in Factor are encouraged to be small and read from left to right. They are known as words A set of words form a module and are called vocabularies Factor programs are a sequence of words (including ones that generate data into the stack) Words are usually 1-3 lines in length and larger ones can be factored out into smaller words applied after one another Words are separated only by spaces - this makes tokenization simple
7 A simple Factor program - Finding Factorial of 10 Suppose we want to calculate the factorial of 10 in Factor. We can do that as follows push 10 on the data stack push 1 on the stack 10 [1,b] 1 [ * ] reduce Generate a lazy sequence from 1 to number on top of the stack A quotation or a lambda function, here multiplication Apply reduce on the sequence on top of the stack The reduce function that takes a sequence, base number and a function, all present on the stack
8 Factorial of 10 - View from the REPL
9 Factorial of 10 - Key Takeaways Literals like 10, hello, 0.19 are treated as words themselves, they have the effect of adding the data to the stack Words use the postfix notation i.e data is pushed to the stack before the operator. Hence there is no notion of precedence required Words in factor can use any character, number or punctuation - only whitespace is used for tokenization. Hence we can have words like [a,b] [ * ] is an anonymous function or quotation. Note the whitespace in between [ and *. [ is a special word called parsing word
10 Writing a more general Program in Factor The previous program did not look much like a function - it worked for only one input The aim of the next program will be to create a general function as well as introduce the notions of parsing-word, stack-effects and combinators
11 Parsing-Words A parsing word is a special word that is part of the meta-programming of Factor Unlike regular words, parsing-words do not have an immediate effect on the stack - rather they interact with Factors parser to influence how successive words are to be parsed A Parsing-Word is defined using the SYNTAX: ; word (note SYNTAX: itself can be considered a parsing word)
12 Some common Parsing Words [... ] : These parser words are used to define quotations or anonymous functions. For example [ * ] {... } : These are parser words used to define arrays. For example { } H{... } : These are parser words used to define hash maps. For example H{ { A B } { C D } } : ; : These are parser words used to define functions USE: ; : Parser word to import packages TUPLE: ; : Parser word to define a class
13 Defining Functions in Factor A function definition in Factor is as follows Function Name Body of the function Parsing word begin : name ( x1 x2. xn -- y1 y2.ym ) body ; Parsing word end The stack effect of the function
14 Stack Effects Stack effects is an important feature in Factor. They behave like a pre-condition and post-condition for that function The notation ( x1 x2 xn -- y1 y2 ym ) means that the function processes x1 x2 xn items on the stack and output y1 y2.. ym on the stack The variable names themselves don t mean anything, the names are chosen to allow the user to quickly identify the behaviour of the function To use the names x1,x2 xn in the body, the :: parsing-word is used when declaring functions instead of :
15 Stack Effects - Examples dup ( x -- x x ) : Duplicate the top element of the stack drop ( x -- ) : Drop the top element of the stack swap ( x y -- y x ) : Swap the top two elements of the stack nip ( x y -- y ) : Remove second element from top on the stack rot ( x y z -- y z x ) : Rotate left top three elements of the stack -rot ( x y z -- z x y ) : Rotate right top three elements of the stack product ( {x1,...,xn} -- x1*...*xn ) : Product of an array
16 Dataflow Combinators Stack based programs require the user to run a mental stack machine, which becomes trickier when applications shuffle the stack (like swap) Dataflow Combinators simplify this by encapsulating common, easy to understand dataflows cleave combinators like bi, tri that apply multiple functions on a data value, for example the program 10 { [ 3 + ] [ 2 - ] } cleave results in the top of the stack having value 13 8 spread combinators like bi*, tri* takes a series of objects and a equal number of quotations and apply the quotation on the appropriate object napply combinators like bi@, tri@ take a quotation and an integer n and apply the quotation on the top n objects on the stack
17 Dataflow Combinators - Examples 10 [ 3 + ] [ 2 - ] bi results in the data stack having 13 and 8 as its top elements. Equivalent to 10 { [ 3 + ] [ 2 - ] } cleave [3 + ] [ 2 - ] bi* results in the data stack having 13 and 10 as its top elements. Equivalent to { [ 3 + ] [ 2 - ] } spread [ 2 + ] bi@ results in the data stack having 12 and 14 as its top elements. Equivalent to [ 2 + ] 2 napply
18 Currying in Factor Factor allows function currying using the curry word The curry word accepts a 10 [ + ] curry generates a new word on [ 10 + ] by absorbing the top element of the stack into the quotation The curry word requires two arguments an argument and a quotation, and absorbs the argument into the quotation For example if the top of the data stack looks like [ 2 + ] [ 3 + ] [ bi ]. Using the curry word, the new stack looks like [ 2 + ] [ ~quotation~ bi ]. Note that it only absorbed one argument at a time
19 Primality testing program in Factor Quotation of generating numbers from 2 to n A cleave combinator : prime? ( n --? ) [ sqrt [2,b] ] [ [ multiple? ] curry ] bi any? not ; Word name Stack effect for the word, this states that the word takes the top element of the stack and returns a boolean (The symbols themselves don t mean anything) Checks if one number is a multiple of another Negate the final result Checks if there is a number in a sequence that satisfies a given condition
20 Recursion in Factor : fib ( n -- fib(n) ) dup 1 > [ [ 1 - fib ] [ 2 - fib ] bi + ] when ; Factor performs tail-call optimization
21 Object System in Factor Factor is purely object-oriented programming language - every value is an object and basic operations are method calls Unlike traditional object-oriented programs, methods do not belong to a particular object or class, rather a method is defined as a generic word with its implementation being different for different classes
22 Defining new Classes - The Tuple: parsing word A class can be defined using the Tuple: parsing word as TUPLE : class-name field1 field2. ;. For example : TUPLE: circle radius ; TUPLE: rectangle length width ; Each instance variable has an associated getter and setter. For example the circle class has a radius>> getter and >>radius setter. Fields can be made read-only and by defining them like { radius read-only }
23 Creating Objects of a Class An object of the class can be created using the new word like rectangle new 10 >>length 10 >>width. or using the boa(by-order-of-arguments) constructor rectangle boa The boa constructor is common enough to have its own parsing defined as C: <rectangle> rectangle, which can be used as <rectangle>
24 Methods for classes - Generic words The GENERIC: parsing word allows a user to define methods common to different classes. For example an area method for the two defined shapes can be written as GENERIC: area ( shape -- area ) M: circle area radius>> dup * pi * ; M: rectangle area [ length>> ] [ width>> ] bi * ;
25 Derived Classes Primitive classes like Strings, Numbers and words cannot be subclassed Tuple classes offer single inheritance - rooted at a class called tuple More classes can be defined using set operations on Tuple classes like UNION: and INTERSECTION: Mixins are special Union class where some class can be added to a mixin that share a method Protocols consist of a set of generic words used by a Mixin. This is equivalent to an interface in other object oriented languages
26 Unit Tests and Documentation Unit Tests can be written using tools.test vocabulary. For example, [ t ] [ 2 prime? ] unit-test Similar to unit-tests, there are different words like must-fail, must-infer etc The help.markup and help.syntax vocabularies help in documentation
27 Documentation in Factor HELP: prime? { $values { "n" fixnum } { "?" boolean } } { $description "Tests if n is prime. n is assumed to be a positive integer." } ;
28 I/O in Factor Factor uses asynchronous input/output facilities, similar to NIO on the JVM or Node.js I/O system I/O is represented as lazy streams around which words are designed to read or write to a stream : read-lines ( path -- ) utf8 file-lines [ 1 safe-head write nl ] each ; Encoding of file Reads lines of a file as a lazy sequence read 1 element from the sequence and print it Apply quotation on each file line
29 Multithreading Factor is single threaded - so it emulates multithreading using coroutines - cooperative threads that periodically yield the core they are running on Factor allows for spawning of processes on multiple cores that communicate through channels Threads are created using spawn, with stop, suspend, sleep and resume words Channels use to and from similar to Akka s send and receive ( send and receive in Factor is used for marking quotations to be called when receiving or sending a messsage)
30 Other Features Factor allows using local variables using the :: parsing word by binding stack parameters to variables Factor allows using dynamic variables using the SYMBOL: parsing word along with get and set words to manipulate it. These variables can be bound to a particular scope using [ ]with-scope parsing words Factor has a built in HTTP server library Factor provides nice metaprogramming features in terms of macros, parsing words and functors Excellent REPL
31 Current Limitations Factors community is small. It is tricky to find information about Factor on the internet It s not always simple to think in terms of a single stack - many stack manipulating operations are tricky to understand and traditional programs have different implementation Factor is single threaded - so programs must be designed in an event driven manner
32 Some good resources on Factor Factor REPL can be downloaded from Slav Pestov s paper on Factor Andrea Ferreti s excellent tutorial about basics of Factor Concatenative programming websites Wiki on Factor Some good examples on and Slav s Google talk on
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