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  • Best way to connect a desktop computer to a 3g network

    - by dbyrne
    A friend of mine is moving to a building with no Internet connectivity. Ethernet and wifi are out of the question. What is the best way for him to get his desktop connected? The most obvious solution is for him to get an unlimited 3G data plan. What is the best way for him to set this up? I am assuming he should get something like Verizon's MiFi 3G access point, but does this have an ethernet jack?

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  • Best way to connect a desktop computer to a 3g network

    - by dbyrne
    A friend of mine is moving to a building with no Internet connectivity. Ethernet and wifi are out of the question. What is the best way for him to get his desktop connected? The most obvious solution is for him to get an unlimited 3G data plan. What is the best way for him to set this up? I am assuming he should get something like Verizon's MiFi 3G access point, but does this have an ethernet jack?

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  • Subversion LDAP Configuration

    - by dbyrne
    I am configuring a subversion repository to use basic LDAP authentication. I have an entry in my http.conf file that looks like this: <Location /company/some/location> DAV svn SVNPath /repository/some/location AuthType Basic AuthName LDAP AuthBasicProvider ldap Require valid-user AuthLDAPBindDN "cn=SubversionAdmin,ou=admins,o=company.com" AuthLDAPBindPassword "XXXXXXX" AuthLDAPURL "ldap://company.com/ou=people,o=company.com?personid" </Location> This works fine for living, breathing people who need to log in. However, I also need to provide application accounts access to the repository. These accounts are in a different OU. Do I need to add a whole new <location> element, or can I add a second AuthLDAPURLto the existing entry?

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  • Polymorphism, Autoboxing, and Implicit Conversions

    - by dbyrne
    Would you consider autoboxing in Java to be a form of polymorphism? Put another way, do you think autoboxing extends the polymorphic capabilities of Java? What about implicit conversions in Scala? My opinion is that they are both examples of polymorphism. Both features allow values of different data types to be handled in a uniform manner. My colleague disagrees with me. Who is right?

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  • Whats the point of lazy-seq in clojure?

    - by dbyrne
    I am looking through some example Fibonacci sequence clojure code: (def fibs (lazy-cat [1 2] (map + fibs (rest fibs)))) I generally understand what is going on, but don't quite understand the point of lazy-cat. I know that lazy-cat is a macro that is translating to something like this: (def fibs (concat (lazy-seq [1 2]) (lazy-seq (map + fibs (rest fibs))))) What exactly is lazy-seq accomplishing? It would still be evaluated lazily even without lazy-seq? Is this strictly for caching purposes?

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  • Clojure: seq (cons) vs. list (conj)

    - by dbyrne
    I know that cons returns a seq and conj returns a collection. I also know that conj "adds" the item to the optimal end of the collection, and cons always "adds" the item to the front. This example illustrates both of these points: user=> (conj [1 2 3] 4) //returns a collection [1 2 3 4] user=> (cons 4 [1 2 3]) //returns a seq (4 1 2 3) For vectors, maps, and sets these differences make sense to me. However, for lists they seem identical. user=> (conj '(3 2 1) 4) (4 3 2 1) user=> (cons 4 '(3 2 1)) (4 3 2 1) Are there any examples using lists where conj vs. cons exhibit different behaviors, or are they truly interchangeable? Phrased differently, is there an example where a list and a seq cannot be used equivalently?

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  • Subversion LDAP Configuration

    - by dbyrne
    I am configuring a subversion repository to use basic LDAP authentication. I have an entry in my http.conf file that looks like this: <Location /company/some/location> DAV svn SVNPath /repository/some/location AuthType Basic AuthName LDAP AuthBasicProvider ldap Require valid-user AuthLDAPBindDN "cn=SubversionAdmin,ou=admins,o=company.com" AuthLDAPBindPassword "XXXXXXX" AuthLDAPURL "ldap://company.com/ou=people,o=company.com?personid" </Location> This works fine for living, breathing people who need to log in. However, I also need to provide application accounts access to the repository. These accounts are in a different OU. Do I need to add a whole new <location> element, or can I add a second AuthLDAPURLto the existing entry?

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  • Recursive function causing a stack overflow

    - by dbyrne
    I am trying to write a simple sieve function to calculate prime numbers in clojure. I've seen this question about writing an efficient sieve function, but I am not to that point yet. Right now I am just trying to write a very simple (and slow) sieve. Here is what I have come up with: (defn sieve [potentials primes] (if-let [p (first potentials)] (recur (filter #(not= (mod % p) 0) potentials) (conj primes p)) primes)) For small ranges it works fine, but causes a stack overflow for large ranges: user=> (sieve (range 2 30) []) [2 3 5 7 11 13 17 19 23 29] user=> (sieve (range 2 15000) []) java.lang.StackOverflowError (NO_SOURCE_FILE:0) I thought that by using recur this would be a non-stack-consuming looping construct? What am I missing?

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  • JDBC call not executing

    - by dbyrne
    I am working on one of the DAOs for a medium sized web application. Unfortunately, it contains very convoluted logic, and makes hundreds of JDBC stored proc calls in loops. This is out of my control. I am working on a method inside the DAO which makes a single JDBC call. The simplified version of what this method looks like is this: DriverManager.registerDriver(new com.sybase.jdbc2.jdbc.SybDriver()); Connection con = DriverManager.getConnection((String)connectionDetails.get("DATABASE_URL") (String)connectionDetails.get("USERID"), (String)connectionDetails.get("PASSWORD")); String sqlToExecute = "{call " + STORED_PROC + "(?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)}"; CallableStatement stmt = con.prepareCall(sqlToExecute); //Maybe I should try calling clearParameters here? stmt.setString(1,someData); //....Set of parameters.... if (!stmt.execute()) { //execute method never returns false } stmt.close(); Its pretty much a textbook JDBC call. All this stored proc does is insert a single row. Here is where things get crazy: This code works when you run it through a debugger line by line, but fails when you run it "full speed". Not only does it fail, but it doesn't throw any exception! The execute method always returns true. It just breezes right through the JDBC call without inserting a row to the database. If you go through the log files, copy the stored proc call and run it manually, it works (just like it does in debug mode). Whats strange is that the rest of the DAO, with all its hundreds of looped stored proc calls, works fine. My thinking is that Connection or CallableStatement is caching some value behind the scenes that is screwing things up. Has anyone ever seen anything like this before? A JDBC call failing with no exceptions? I know it will be impossible to provide a complete solution to this without seeing the whole application, I am just looking for suggestions on possible issues to investigate.

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  • What is the most useful programming language that no one is using?

    - by dbyrne
    What language do you find incredibly useful that no one else seems to care about? I am not looking for the language with the coolest features, but the language that makes you the most productive. I realize that a productive language that no one uses is a bit of an oxymoron. My personal choice would probably be ruby without rails, but I am sure others can come up with some better answers.

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  • Accessing a Class Member from a First-Class Function

    - by dbyrne
    I have a case class which takes a list of functions: case class A(q:Double, r:Double, s:Double, l:List[(Double)=>Double]) I have over 20 functions defined. Some of these functions have their own parameters, and some of them also use the q, r, and s values from the case class. Two examples are: def f1(w:Double) = (d:Double) => math.sin(d) * w def f2(w:Double, q:Double) = (d:Double) => d * q * w The problem is that I then need to reference q, r, and s twice when instantiating the case class: A(0.5, 1.0, 2.0, List(f1(3.0), f2(4.0, 0.5))) //0.5 is referenced twice I would like to be able to instantiate the class like this: A(0.5, 1.0, 2.0, List(f1(3.0), f2(4.0))) //f2 already knows about q! What is the best technique to accomplish this? Can I define my functions in a trait that the case class extends? EDIT: The real world application has 7 members, not 3. Only a small number of the functions need access to the members. Most of the functions don't care about them.

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  • Working with images in Scala

    - by dbyrne
    I am generating large PNG files from a Scala program. Currently, I am doing it the same way I would do it in java. I am creating a new BufferedImage and setting each pixel to the correct color. This works fine, but I am wondering if there are any good libraries for working with images in Scala? I am looking for something like Ruby's RMagick library.

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  • Scala Tuple Deconstruction

    - by dbyrne
    I am new to Scala, and ran across a small hiccup that has been annoying me. Initializing two vars in parallel works great: var (x,y) = (1,2) However I can't find a way to assign new values in parallel: (x,y) = (x+y,y-x) //invalid syntax I end up writing something like this: val xtmp = x+y; y = x-y; x = xtmp I realize writing functional code is one way of avoiding this, but there are certain situations where vars just make more sense. I have two questions: 1) Is there a better way of doing this? Am I missing something? 2) What is the reason for not allowing true parallel assignment?

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  • Project Euler #14 and memoization in Clojure

    - by dbyrne
    As a neophyte clojurian, it was recommended to me that I go through the Project Euler problems as a way to learn the language. Its definitely a great way to improve your skills and gain confidence. I just finished up my answer to problem #14. It works fine, but to get it running efficiently I had to implement some memoization. I couldn't use the prepackaged memoize function because of the way my code was structured, and I think it was a good experience to roll my own anyways. My question is if there is a good way to encapsulate my cache within the function itself, or if I have to define an external cache like I have done. Also, any tips to make my code more idiomatic would be appreciated. (use 'clojure.test) (def mem (atom {})) (with-test (defn chain-length ([x] (chain-length x x 0)) ([start-val x c] (if-let [e (last(find @mem x))] (let [ret (+ c e)] (swap! mem assoc start-val ret) ret) (if (<= x 1) (let [ret (+ c 1)] (swap! mem assoc start-val ret) ret) (if (even? x) (recur start-val (/ x 2) (+ c 1)) (recur start-val (+ 1 (* x 3)) (+ c 1))))))) (is (= 10 (chain-length 13)))) (with-test (defn longest-chain ([] (longest-chain 2 0 0)) ([c max start-num] (if (>= c 1000000) start-num (let [l (chain-length c)] (if (> l max) (recur (+ 1 c) l c) (recur (+ 1 c) max start-num)))))) (is (= 837799 (longest-chain))))

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  • Project Euler #9 (Pythagorean triplets) in Clojure

    - by dbyrne
    My answer to this problem feels too much like these solutions in C. Does anyone have any advice to make this more lispy? (use 'clojure.test) (:import 'java.lang.Math) (with-test (defn find-triplet-product ([target] (find-triplet-product 1 1 target)) ([a b target] (let [c (Math/sqrt (+ (* a a) (* b b)))] (let [sum (+ a b c)] (cond (> a target) "ERROR" (= sum target) (reduce * (list a b (int c))) (> sum target) (recur (inc a) 1 target) (< sum target) (recur a (inc b) target)))))) (is (= (find-triplet-product 1000) 31875000)))

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  • Performance Problem with Clojure Array

    - by dbyrne
    This piece of code is very slow. Execution from the slime-repl on my netbook takes a couple minutes. Am I doing something wrong? (def test-array (make-array Integer/TYPE 400 400 3)) (doseq [x (range 400), y (range 400), z (range 3)] (aset test-array x y z 0))

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  • Best Functional Approach

    - by dbyrne
    I have some mutable scala code that I am trying to rewrite in a more functional style. It is a fairly intricate piece of code, so I am trying to refactor it in pieces. My first thought was this: def iterate(count:Int,d:MyComplexType) = { //Generate next value n //Process n causing some side effects return iterate(count - 1, n) } This didn't seem functional at all to me, since I still have side effects mixed throughout my code. My second thought was this: def generateStream(d:MyComplexType):Stream[MyComplexType] = { //Generate next value n return Stream.cons(n, generateStream(n)) } for (n <- generateStream(initialValue).take(2000000)) { //process n causing some side effects } This seemed like a better solution to me, because at least I've isolated my functional value-generation code from the mutable value-processing code. However, this is much less memory efficient because I am generating a large list that I don't really need to store. This leaves me with 3 choices: Write a tail-recursive function, bite the bullet and refactor the value-processing code Use a lazy list. This is not a memory sensitive app (although it is performance sensitive) Come up with a new approach. I guess what I really want is a lazily evaluated sequence where I can discard the values after I've processed them. Any suggestions?

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  • Clojure for a lisp illiterate

    - by dbyrne
    I am a lifelong object-oriented programmer. My job is primarily java development, but I have experience in a number of languages. Ruby gave me my first real taste of functional programming. I loved the features Ruby borrowed from the functional paradigm such as closures and continuations. Eventually, I graduated to Scala. This has been a great way to gradually learn to approach non-trivial problems in a functional manner. Now I am interested in Clojure. I know all the sexy features that make it enticing (software transactional memory, macros, etc.), but I just can't get used to "thinking in lisp". I've seen Rich Hickey's screencasts aimed at java programmers, but they are geared towards explaining language features and not approaching real world problems. I am looking for any advice or resources which have made this transition easier for others.

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