Search Results

Search found 13859 results on 555 pages for 'non functional'.

Page 2/555 | < Previous Page | 1 2 3 4 5 6 7 8 9 10 11 12  | Next Page >

  • Functional Programming - Does Knowing It Help Job Prospects?

    - by Jetti
    The main language that I use at the moment is C# and I am the most comfortable with it. However, I have started dabbling in F# and Haskell and really enjoy those langauges. I would love to improve my skills in either of those languages over time since it truly is fun for me to use them (as opposed to Ruby, which is hyped as "fun", I just don't get where the fun is, but I digress...). My question is directed at those who have hired/interviewed for programming positions (junior/mid-level): if you see a functional programming language on a resume, does it affect your opinion (whether positive or negatively) of that candidate? My rationale for knowledge of functional programming affecting the view of a candidate is because it can show that the candidate can adapt to different methodologies and take a mulit-dimensional approach to problems rather than the "same old OO approach". (This may be off-base, please let me know if this assumption is as well!)

    Read the article

  • What are functional-programming ways of implementing Conway's Game of Life

    - by George Mauer
    I recently implemented for fun Conway's Game of Life in Javascript (actually coffeescript but same thing). Since javascript can be used as a functional language I was trying to stay to that end of the spectrum. I was not happy with my results. I am a fairly good OO programmer and my solution smacked of same-old-same-old. So long question short: what is the (pseudocode) functional style of doing it? Here is Pseudocode for my attempt: class Node update: (board) -> get number_of_alive_neighbors from board get this_is_alive from board if this_is_alive and number_of_alive_neighbors < 2 then die if this_is_alive and number_of_alive_neighbors > 3 then die if not this_is_alive and number_of_alive_neighbors == 3 then alive class NodeLocations at: (x, y) -> return node value at x,y of: (node) -> return x,y of node class Board getNeighbors: (node) -> use node_locations to check 8 neighbors around node and return count nodes = for 1..100 new Node state = new NodeState(nodes) locations = new NodeLocations(nodes) board = new Board(locations, state) executeRound: state = clone state accumulated_changes = for n in nodes n.update(board) apply accumulated_changes to state board = new Board(locations, state)

    Read the article

  • Composing programs from small simple pieces: OOP vs Functional Programming

    - by Jay Godse
    I started programming when imperative programming languages such as C were virtually the only game in town for paid gigs. I'm not a computer scientist by training so I was only exposed to Assembler and Pascal in school, and not Lisp or Prolog. Over the 1990s, Object-Oriented Programming (OOP) became more popular because one of the marketing memes for OOP was that complex programs could be composed of loosely coupled but well-defined, well-tested, cohesive, and reusable classes and objects. And in many cases that is quite true. Once I learned object-oriented programming my C programs became better because I structured them more like classes and objects. In the last few years (2008-2014) I have programmed in Ruby, an OOP language. However, Ruby has many functional programming (FP) features such as lambdas and procs, which enable a different style of programming using recursion, currying, lazy evaluation and the like. (Through ignorance I am at a loss to explain why these techniques are so great). Very recently, I have written code to use methods from the Ruby Enumerable library, such as map(), reduce(), and select(). Apparently this is a functional style of programming. I have found that using these methods significantly reduce code volume, and make my code easier to debug. Upon reading more about FP, one of the marketing claims made by advocates is that FP enables developers to compose programs out of small well-defined, well-tested, and reusable functions, which leads to less buggy code, and low code volume. QUESTIONS: Is the composition of complex program by using FP techniques contradictory to or complementary to composition of a complex program by using OOP techniques? In which situations is OOP more effective, and when is FP more effective? Is it possible to use both techniques in the same complex program? Do the techniques overlap or contradict each other?

    Read the article

  • functional, bind1st and mem_fun

    - by Neil G
    Why won't this compile? #include <functional> #include <boost/function.hpp> class A { A() { typedef boost::function<void ()> FunctionCall; FunctionCall f = std::bind1st(std::mem_fun(&A::process), this); } void process() {} }; Errors: In file included from /opt/local/include/gcc44/c++/bits/stl_function.h:712, from /opt/local/include/gcc44/c++/functional:50, from a.cc:1: /opt/local/include/gcc44/c++/backward/binders.h: In instantiation of 'std::binder1st<std::mem_fun_t<void, A> >': a.cc:7: instantiated from here /opt/local/include/gcc44/c++/backward/binders.h:100: error: no type named 'second_argument_type' in 'class std::mem_fun_t<void, A>' /opt/local/include/gcc44/c++/backward/binders.h:103: error: no type named 'first_argument_type' in 'class std::mem_fun_t<void, A>' /opt/local/include/gcc44/c++/backward/binders.h:106: error: no type named 'first_argument_type' in 'class std::mem_fun_t<void, A>' /opt/local/include/gcc44/c++/backward/binders.h:111: error: no type named 'second_argument_type' in 'class std::mem_fun_t<void, A>' /opt/local/include/gcc44/c++/backward/binders.h:117: error: no type named 'second_argument_type' in 'class std::mem_fun_t<void, A>' /opt/local/include/gcc44/c++/backward/binders.h: In function 'std::binder1st<_Operation> std::bind1st(const _Operation&, const _Tp&) [with _Operation = std::mem_fun_t<void, A>, _Tp = A*]': a.cc:7: instantiated from here /opt/local/include/gcc44/c++/backward/binders.h:126: error: no type named 'first_argument_type' in 'class std::mem_fun_t<void, A>' In file included from /opt/local/include/boost/function/detail/maybe_include.hpp:13, from /opt/local/include/boost/function/detail/function_iterate.hpp:14, from /opt/local/include/boost/preprocessor/iteration/detail/iter/forward1.hpp:47, from /opt/local/include/boost/function.hpp:64, from a.cc:2: /opt/local/include/boost/function/function_template.hpp: In static member function 'static void boost::detail::function::void_function_obj_invoker0<FunctionObj, R>::invoke(boost::detail::function::function_buffer&) [with FunctionObj = std::binder1st<std::mem_fun_t<void, A> >, R = void]': /opt/local/include/boost/function/function_template.hpp:913: instantiated from 'void boost::function0<R>::assign_to(Functor) [with Functor = std::binder1st<std::mem_fun_t<void, A> >, R = void]' /opt/local/include/boost/function/function_template.hpp:722: instantiated from 'boost::function0<R>::function0(Functor, typename boost::enable_if_c<boost::type_traits::ice_not::value, int>::type) [with Functor = std::binder1st<std::mem_fun_t<void, A> >, R = void]' /opt/local/include/boost/function/function_template.hpp:1064: instantiated from 'boost::function<R()>::function(Functor, typename boost::enable_if_c<boost::type_traits::ice_not::value, int>::type) [with Functor = std::binder1st<std::mem_fun_t<void, A> >, R = void]' a.cc:7: instantiated from here /opt/local/include/boost/function/function_template.hpp:153: error: no match for call to '(std::binder1st<std::mem_fun_t<void, A> >) ()'

    Read the article

  • How do functional languages handle random numbers?

    - by Electric Coffee
    What I mean about that is that in nearly every tutorial I've read about functional languages, is that one of the great things about functions, is that if you call a function with the same parameters twice, you'll always end up with the same result. How on earth do you then make a function that takes a seed as a parameter, and then returns a random number based on that seed? I mean this would seem to go against one of the things that are so good about functions, right? Or am I completely missing something here?

    Read the article

  • How to organize functional programs

    - by bleakcabal
    In OOP, your basic unit of organization for code is the class. A frequently used methodology in Java, C# and similar languages is to organize your code around having one file for each class with the file name following the class name. You can consider each of these class as a unit of organization to group a single concept. These classes are in in namespaces which often follow the directory structure of the files in the solution/project. Namespaces are another level of organization. How are large projects in functional languages typically organized? How to you determine how to split your functions into different files? Are other units of grouping beside files used? How is code typically organized within a single file?

    Read the article

  • Using "public" vars or attributes in class calls, functional approach

    - by marw
    I was always wondering about two things I tend to do in my little projects. Sometimes I will have this design: class FooClass ... self.foo = "it's a bar" self._do_some_stuff(self) def _do_some_stuff(self): print(self.foo) And sometimes this one: class FooClass2 ... self.do_some_stuff(foo="it's a bar") def do_some_stuff(self, foo): print(foo) Although I roughly understand the differences between functional and class approaches, I struggle with the design. For example, in FooClass the self.foo is always accessible as an attribute. If there are numerous calls to it, is that faster than making foo a local variable that is passed from method to method (like in FooClass2)? What happens in memory in both cases? If FooClass2 is preferred (ie. I don't need to access foo) and other attributes inside do not change their states (the class is executed once only and returns the result), should the code then be written as a series of functions in a module?

    Read the article

  • Functional Methods on Collections

    - by GlenPeterson
    I'm learning Scala and am a little bewildered by all the methods (higher-order functions) available on the collections. Which ones produce more results than the original collection, which ones produce less, and which are most appropriate for a given problem? Though I'm studying Scala, I think this would pertain to most modern functional languages (Clojure, Haskell) and also to Java 8 which introduces these methods on Java collections. Specifically, right now I'm wondering about map with filter vs. fold/reduce. I was delighted that using foldRight() can yield the same result as a map(...).filter(...) with only one traversal of the underlying collection. But a friend pointed out that foldRight() may force sequential processing while map() is friendlier to being processed by multiple processors in parallel. Maybe this is why mapReduce() is so popular? More generally, I'm still sometimes surprised when I chain several of these methods together to get back a List(List()) or to pass a List(List()) and get back just a List(). For instance, when would I use: collection.map(a => a.map(b => ...)) vs. collection.map(a => ...).map(b => ...) The for/yield command does nothing to help this confusion. Am I asking about the difference between a "fold" and "unfold" operation? Am I trying to jam too many questions into one? I think there may be an underlying concept that, if I understood it, might answer all these questions, or at least tie the answers together.

    Read the article

  • Functional programming and stateful algorithms

    - by bigstones
    I'm learning functional programming with Haskell. In the meantime I'm studying Automata theory and as the two seem to fit well together I'm writing a small library to play with automata. Here's the problem that made me ask the question. While studying a way to evaluate a state's reachability I got the idea that a simple recursive algorithm would be quite inefficient, because some paths might share some states and I might end up evaluating them more than once. For example, here, evaluating reachability of g from a, I'd have to exclude f both while checking the path through d and c: So my idea is that an algorithm working in parallel on many paths and updating a shared record of excluded states might be great, but that's too much for me. I've seen that in some simple recursion cases one can pass state as an argument, and that's what I have to do here, because I pass forward the list of states I've gone through to avoid loops. But is there a way to pass that list also backwards, like returning it in a tuple together with the boolean result of my canReach function? (although this feels a bit forced) Besides the validity of my example case, what other techniques are available to solve this kind of problems? I feel like these must be common enough that there have to be solutions like what happens with fold* or map. So far, reading learnyouahaskell.com I didn't find any, but consider I haven't touched monads yet. (if interested, I posted my code on codereview)

    Read the article

  • Functional Programming, JavaScript and UI - some neophyte questions

    - by jamesson
    This has been discussed in other threads, however I am hoping for some comments relevant to UI and an explanation of some vitriol I had flung my way in a Certain IRC Channel Which shall remain nameless. In the discussion here, the comments in the accepted answer suggest that I approach the given code from a functional perspective, which was new to me at the time. Wikipedia said, among other things, that FP "avoids state and mutable data", which includes according to the discussion global vars. Now, being that I am already pretty far along in my project I am not going to learn FP before I finish, but... How is it possible to avoid global vars if, for instance, I have a UI whose entire functionality changes if a mousebutton is down? I have a number of things like this. Why was there a strong negative reaction in the Certain IRC channel to implementing FP in JS? When I Brought up what seemed to me to be supportive comments by Crockford, people got even madder. Now, this being IRC there is no rep system, but they at least gave indication of having read TGP (which I haven't gotten to yet) so I'm assuming they're not idiots. Many thanks in advance Joe

    Read the article

  • What functional language is most suited to create games with?

    - by Ricket
    I have had my eye on functional programming languages for a while, but am hesitating to actually get into them. But I think it's about time I at least starting glancing that direction to make sure I'm ready for anything. I've seen talk of Haskell, F#, Scala, and so on. But I have no clue the differences between the languages and their communities, nor do I particularly care; except in the context of game development. So, from a game development standpoint, which functional programming language has the most features suited for game programming? For example, are there any functional game development libraries/engines/frameworks or graphics engines for functional languages? Is there a language that handles certain data structures which are commonly used in game development better? Bottom line: what functional programming language is best for functional game programming, and why? I believe/hope this question will declare a clear best language therefore I haven't marked it CW despite its subjective tendency.

    Read the article

  • The Incremental Architect&rsquo;s Napkin - #5 - Design functions for extensibility and readability

    - by Ralf Westphal
    Originally posted on: http://geekswithblogs.net/theArchitectsNapkin/archive/2014/08/24/the-incremental-architectrsquos-napkin---5---design-functions-for.aspx The functionality of programs is entered via Entry Points. So what we´re talking about when designing software is a bunch of functions handling the requests represented by and flowing in through those Entry Points. Designing software thus consists of at least three phases: Analyzing the requirements to find the Entry Points and their signatures Designing the functionality to be executed when those Entry Points get triggered Implementing the functionality according to the design aka coding I presume, you´re familiar with phase 1 in some way. And I guess you´re proficient in implementing functionality in some programming language. But in my experience developers in general are not experienced in going through an explicit phase 2. “Designing functionality? What´s that supposed to mean?” you might already have thought. Here´s my definition: To design functionality (or functional design for short) means thinking about… well, functions. You find a solution for what´s supposed to happen when an Entry Point gets triggered in terms of functions. A conceptual solution that is, because those functions only exist in your head (or on paper) during this phase. But you may have guess that, because it´s “design” not “coding”. And here is, what functional design is not: It´s not about logic. Logic is expressions (e.g. +, -, && etc.) and control statements (e.g. if, switch, for, while etc.). Also I consider calling external APIs as logic. It´s equally basic. It´s what code needs to do in order to deliver some functionality or quality. Logic is what´s doing that needs to be done by software. Transformations are either done through expressions or API-calls. And then there is alternative control flow depending on the result of some expression. Basically it´s just jumps in Assembler, sometimes to go forward (if, switch), sometimes to go backward (for, while, do). But calling your own function is not logic. It´s not necessary to produce any outcome. Functionality is not enhanced by adding functions (subroutine calls) to your code. Nor is quality increased by adding functions. No performance gain, no higher scalability etc. through functions. Functions are not relevant to functionality. Strange, isn´t it. What they are important for is security of investment. By introducing functions into our code we can become more productive (re-use) and can increase evolvability (higher unterstandability, easier to keep code consistent). That´s no small feat, however. Evolvable code can hardly be overestimated. That´s why to me functional design is so important. It´s at the core of software development. To sum this up: Functional design is on a level of abstraction above (!) logical design or algorithmic design. Functional design is only done until you get to a point where each function is so simple you are very confident you can easily code it. Functional design an logical design (which mostly is coding, but can also be done using pseudo code or flow charts) are complementary. Software needs both. If you start coding right away you end up in a tangled mess very quickly. Then you need back out through refactoring. Functional design on the other hand is bloodless without actual code. It´s just a theory with no experiments to prove it. But how to do functional design? An example of functional design Let´s assume a program to de-duplicate strings. The user enters a number of strings separated by commas, e.g. a, b, a, c, d, b, e, c, a. And the program is supposed to clear this list of all doubles, e.g. a, b, c, d, e. There is only one Entry Point to this program: the user triggers the de-duplication by starting the program with the string list on the command line C:\>deduplicate "a, b, a, c, d, b, e, c, a" a, b, c, d, e …or by clicking on a GUI button. This leads to the Entry Point function to get called. It´s the program´s main function in case of the batch version or a button click event handler in the GUI version. That´s the physical Entry Point so to speak. It´s inevitable. What then happens is a three step process: Transform the input data from the user into a request. Call the request handler. Transform the output of the request handler into a tangible result for the user. Or to phrase it a bit more generally: Accept input. Transform input into output. Present output. This does not mean any of these steps requires a lot of effort. Maybe it´s just one line of code to accomplish it. Nevertheless it´s a distinct step in doing the processing behind an Entry Point. Call it an aspect or a responsibility - and you will realize it most likely deserves a function of its own to satisfy the Single Responsibility Principle (SRP). Interestingly the above list of steps is already functional design. There is no logic, but nevertheless the solution is described - albeit on a higher level of abstraction than you might have done yourself. But it´s still on a meta-level. The application to the domain at hand is easy, though: Accept string list from command line De-duplicate Present de-duplicated strings on standard output And this concrete list of processing steps can easily be transformed into code:static void Main(string[] args) { var input = Accept_string_list(args); var output = Deduplicate(input); Present_deduplicated_string_list(output); } Instead of a big problem there are three much smaller problems now. If you think each of those is trivial to implement, then go for it. You can stop the functional design at this point. But maybe, just maybe, you´re not so sure how to go about with the de-duplication for example. Then just implement what´s easy right now, e.g.private static string Accept_string_list(string[] args) { return args[0]; } private static void Present_deduplicated_string_list( string[] output) { var line = string.Join(", ", output); Console.WriteLine(line); } Accept_string_list() contains logic in the form of an API-call. Present_deduplicated_string_list() contains logic in the form of an expression and an API-call. And then repeat the functional design for the remaining processing step. What´s left is the domain logic: de-duplicating a list of strings. How should that be done? Without any logic at our disposal during functional design you´re left with just functions. So which functions could make up the de-duplication? Here´s a suggestion: De-duplicate Parse the input string into a true list of strings. Register each string in a dictionary/map/set. That way duplicates get cast away. Transform the data structure into a list of unique strings. Processing step 2 obviously was the core of the solution. That´s where real creativity was needed. That´s the core of the domain. But now after this refinement the implementation of each step is easy again:private static string[] Parse_string_list(string input) { return input.Split(',') .Select(s => s.Trim()) .ToArray(); } private static Dictionary<string,object> Compile_unique_strings(string[] strings) { return strings.Aggregate( new Dictionary<string, object>(), (agg, s) => { agg[s] = null; return agg; }); } private static string[] Serialize_unique_strings( Dictionary<string,object> dict) { return dict.Keys.ToArray(); } With these three additional functions Main() now looks like this:static void Main(string[] args) { var input = Accept_string_list(args); var strings = Parse_string_list(input); var dict = Compile_unique_strings(strings); var output = Serialize_unique_strings(dict); Present_deduplicated_string_list(output); } I think that´s very understandable code: just read it from top to bottom and you know how the solution to the problem works. It´s a mirror image of the initial design: Accept string list from command line Parse the input string into a true list of strings. Register each string in a dictionary/map/set. That way duplicates get cast away. Transform the data structure into a list of unique strings. Present de-duplicated strings on standard output You can even re-generate the design by just looking at the code. Code and functional design thus are always in sync - if you follow some simple rules. But about that later. And as a bonus: all the functions making up the process are small - which means easy to understand, too. So much for an initial concrete example. Now it´s time for some theory. Because there is method to this madness ;-) The above has only scratched the surface. Introducing Flow Design Functional design starts with a given function, the Entry Point. Its goal is to describe the behavior of the program when the Entry Point is triggered using a process, not an algorithm. An algorithm consists of logic, a process on the other hand consists just of steps or stages. Each processing step transforms input into output or a side effect. Also it might access resources, e.g. a printer, a database, or just memory. Processing steps thus can rely on state of some sort. This is different from Functional Programming, where functions are supposed to not be stateful and not cause side effects.[1] In its simplest form a process can be written as a bullet point list of steps, e.g. Get data from user Output result to user Transform data Parse data Map result for output Such a compilation of steps - possibly on different levels of abstraction - often is the first artifact of functional design. It can be generated by a team in an initial design brainstorming. Next comes ordering the steps. What should happen first, what next etc.? Get data from user Parse data Transform data Map result for output Output result to user That´s great for a start into functional design. It´s better than starting to code right away on a given function using TDD. Please get me right: TDD is a valuable practice. But it can be unnecessarily hard if the scope of a functionn is too large. But how do you know beforehand without investing some thinking? And how to do this thinking in a systematic fashion? My recommendation: For any given function you´re supposed to implement first do a functional design. Then, once you´re confident you know the processing steps - which are pretty small - refine and code them using TDD. You´ll see that´s much, much easier - and leads to cleaner code right away. For more information on this approach I call “Informed TDD” read my book of the same title. Thinking before coding is smart. And writing down the solution as a bunch of functions possibly is the simplest thing you can do, I´d say. It´s more according to the KISS (Keep It Simple, Stupid) principle than returning constants or other trivial stuff TDD development often is started with. So far so good. A simple ordered list of processing steps will do to start with functional design. As shown in the above example such steps can easily be translated into functions. Moving from design to coding thus is simple. However, such a list does not scale. Processing is not always that simple to be captured in a list. And then the list is just text. Again. Like code. That means the design is lacking visuality. Textual representations need more parsing by your brain than visual representations. Plus they are limited in their “dimensionality”: text just has one dimension, it´s sequential. Alternatives and parallelism are hard to encode in text. In addition the functional design using numbered lists lacks data. It´s not visible what´s the input, output, and state of the processing steps. That´s why functional design should be done using a lightweight visual notation. No tool is necessary to draw such designs. Use pen and paper; a flipchart, a whiteboard, or even a napkin is sufficient. Visualizing processes The building block of the functional design notation is a functional unit. I mostly draw it like this: Something is done, it´s clear what goes in, it´s clear what comes out, and it´s clear what the processing step requires in terms of state or hardware. Whenever input flows into a functional unit it gets processed and output is produced and/or a side effect occurs. Flowing data is the driver of something happening. That´s why I call this approach to functional design Flow Design. It´s about data flow instead of control flow. Control flow like in algorithms is of no concern to functional design. Thinking about control flow simply is too low level. Once you start with control flow you easily get bogged down by tons of details. That´s what you want to avoid during design. Design is supposed to be quick, broad brush, abstract. It should give overview. But what about all the details? As Robert C. Martin rightly said: “Programming is abot detail”. Detail is a matter of code. Once you start coding the processing steps you designed you can worry about all the detail you want. Functional design does not eliminate all the nitty gritty. It just postpones tackling them. To me that´s also an example of the SRP. Function design has the responsibility to come up with a solution to a problem posed by a single function (Entry Point). And later coding has the responsibility to implement the solution down to the last detail (i.e. statement, API-call). TDD unfortunately mixes both responsibilities. It´s just coding - and thereby trying to find detailed implementations (green phase) plus getting the design right (refactoring). To me that´s one reason why TDD has failed to deliver on its promise for many developers. Using functional units as building blocks of functional design processes can be depicted very easily. Here´s the initial process for the example problem: For each processing step draw a functional unit and label it. Choose a verb or an “action phrase” as a label, not a noun. Functional design is about activities, not state or structure. Then make the output of an upstream step the input of a downstream step. Finally think about the data that should flow between the functional units. Write the data above the arrows connecting the functional units in the direction of the data flow. Enclose the data description in brackets. That way you can clearly see if all flows have already been specified. Empty brackets mean “no data is flowing”, but nevertheless a signal is sent. A name like “list” or “strings” in brackets describes the data content. Use lower case labels for that purpose. A name starting with an upper case letter like “String” or “Customer” on the other hand signifies a data type. If you like, you also can combine descriptions with data types by separating them with a colon, e.g. (list:string) or (strings:string[]). But these are just suggestions from my practice with Flow Design. You can do it differently, if you like. Just be sure to be consistent. Flows wired-up in this manner I call one-dimensional (1D). Each functional unit just has one input and/or one output. A functional unit without an output is possible. It´s like a black hole sucking up input without producing any output. Instead it produces side effects. A functional unit without an input, though, does make much sense. When should it start to work? What´s the trigger? That´s why in the above process even the first processing step has an input. If you like, view such 1D-flows as pipelines. Data is flowing through them from left to right. But as you can see, it´s not always the same data. It get´s transformed along its passage: (args) becomes a (list) which is turned into (strings). The Principle of Mutual Oblivion A very characteristic trait of flows put together from function units is: no functional units knows another one. They are all completely independent of each other. Functional units don´t know where their input is coming from (or even when it´s gonna arrive). They just specify a range of values they can process. And they promise a certain behavior upon input arriving. Also they don´t know where their output is going. They just produce it in their own time independent of other functional units. That means at least conceptually all functional units work in parallel. Functional units don´t know their “deployment context”. They now nothing about the overall flow they are place in. They are just consuming input from some upstream, and producing output for some downstream. That makes functional units very easy to test. At least as long as they don´t depend on state or resources. I call this the Principle of Mutual Oblivion (PoMO). Functional units are oblivious of others as well as an overall context/purpose. They are just parts of a whole focused on a single responsibility. How the whole is built, how a larger goal is achieved, is of no concern to the single functional units. By building software in such a manner, functional design interestingly follows nature. Nature´s building blocks for organisms also follow the PoMO. The cells forming your body do not know each other. Take a nerve cell “controlling” a muscle cell for example:[2] The nerve cell does not know anything about muscle cells, let alone the specific muscel cell it is “attached to”. Likewise the muscle cell does not know anything about nerve cells, let a lone a specific nerve cell “attached to” it. Saying “the nerve cell is controlling the muscle cell” thus only makes sense when viewing both from the outside. “Control” is a concept of the whole, not of its parts. Control is created by wiring-up parts in a certain way. Both cells are mutually oblivious. Both just follow a contract. One produces Acetylcholine (ACh) as output, the other consumes ACh as input. Where the ACh is going, where it´s coming from neither cell cares about. Million years of evolution have led to this kind of division of labor. And million years of evolution have produced organism designs (DNA) which lead to the production of these different cell types (and many others) and also to their co-location. The result: the overall behavior of an organism. How and why this happened in nature is a mystery. For our software, though, it´s clear: functional and quality requirements needs to be fulfilled. So we as developers have to become “intelligent designers” of “software cells” which we put together to form a “software organism” which responds in satisfying ways to triggers from it´s environment. My bet is: If nature gets complex organisms working by following the PoMO, who are we to not apply this recipe for success to our much simpler “machines”? So my rule is: Wherever there is functionality to be delivered, because there is a clear Entry Point into software, design the functionality like nature would do it. Build it from mutually oblivious functional units. That´s what Flow Design is about. In that way it´s even universal, I´d say. Its notation can also be applied to biology: Never mind labeling the functional units with nouns. That´s ok in Flow Design. You´ll do that occassionally for functional units on a higher level of abstraction or when their purpose is close to hardware. Getting a cockroach to roam your bedroom takes 1,000,000 nerve cells (neurons). Getting the de-duplication program to do its job just takes 5 “software cells” (functional units). Both, though, follow the same basic principle. Translating functional units into code Moving from functional design to code is no rocket science. In fact it´s straightforward. There are two simple rules: Translate an input port to a function. Translate an output port either to a return statement in that function or to a function pointer visible to that function. The simplest translation of a functional unit is a function. That´s what you saw in the above example. Functions are mutually oblivious. That why Functional Programming likes them so much. It makes them composable. Which is the reason, nature works according to the PoMO. Let´s be clear about one thing: There is no dependency injection in nature. For all of an organism´s complexity no DI container is used. Behavior is the result of smooth cooperation between mutually oblivious building blocks. Functions will often be the adequate translation for the functional units in your designs. But not always. Take for example the case, where a processing step should not always produce an output. Maybe the purpose is to filter input. Here the functional unit consumes words and produces words. But it does not pass along every word flowing in. Some words are swallowed. Think of a spell checker. It probably should not check acronyms for correctness. There are too many of them. Or words with no more than two letters. Such words are called “stop words”. In the above picture the optionality of the output is signified by the astrisk outside the brackets. It means: Any number of (word) data items can flow from the functional unit for each input data item. It might be none or one or even more. This I call a stream of data. Such behavior cannot be translated into a function where output is generated with return. Because a function always needs to return a value. So the output port is translated into a function pointer or continuation which gets passed to the subroutine when called:[3]void filter_stop_words( string word, Action<string> onNoStopWord) { if (...check if not a stop word...) onNoStopWord(word); } If you want to be nitpicky you might call such a function pointer parameter an injection. And technically you´re right. Conceptually, though, it´s not an injection. Because the subroutine is not functionally dependent on the continuation. Firstly continuations are procedures, i.e. subroutines without a return type. Remember: Flow Design is about unidirectional data flow. Secondly the name of the formal parameter is chosen in a way as to not assume anything about downstream processing steps. onNoStopWord describes a situation (or event) within the functional unit only. Translating output ports into function pointers helps keeping functional units mutually oblivious in cases where output is optional or produced asynchronically. Either pass the function pointer to the function upon call. Or make it global by putting it on the encompassing class. Then it´s called an event. In C# that´s even an explicit feature.class Filter { public void filter_stop_words( string word) { if (...check if not a stop word...) onNoStopWord(word); } public event Action<string> onNoStopWord; } When to use a continuation and when to use an event dependens on how a functional unit is used in flows and how it´s packed together with others into classes. You´ll see examples further down the Flow Design road. Another example of 1D functional design Let´s see Flow Design once more in action using the visual notation. How about the famous word wrap kata? Robert C. Martin has posted a much cited solution including an extensive reasoning behind his TDD approach. So maybe you want to compare it to Flow Design. The function signature given is:string WordWrap(string text, int maxLineLength) {...} That´s not an Entry Point since we don´t see an application with an environment and users. Nevertheless it´s a function which is supposed to provide a certain functionality. The text passed in has to be reformatted. The input is a single line of arbitrary length consisting of words separated by spaces. The output should consist of one or more lines of a maximum length specified. If a word is longer than a the maximum line length it can be split in multiple parts each fitting in a line. Flow Design Let´s start by brainstorming the process to accomplish the feat of reformatting the text. What´s needed? Words need to be assembled into lines Words need to be extracted from the input text The resulting lines need to be assembled into the output text Words too long to fit in a line need to be split Does sound about right? I guess so. And it shows a kind of priority. Long words are a special case. So maybe there is a hint for an incremental design here. First let´s tackle “average words” (words not longer than a line). Here´s the Flow Design for this increment: The the first three bullet points turned into functional units with explicit data added. As the signature requires a text is transformed into another text. See the input of the first functional unit and the output of the last functional unit. In between no text flows, but words and lines. That´s good to see because thereby the domain is clearly represented in the design. The requirements are talking about words and lines and here they are. But note the asterisk! It´s not outside the brackets but inside. That means it´s not a stream of words or lines, but lists or sequences. For each text a sequence of words is output. For each sequence of words a sequence of lines is produced. The asterisk is used to abstract from the concrete implementation. Like with streams. Whether the list of words gets implemented as an array or an IEnumerable is not important during design. It´s an implementation detail. Does any processing step require further refinement? I don´t think so. They all look pretty “atomic” to me. And if not… I can always backtrack and refine a process step using functional design later once I´ve gained more insight into a sub-problem. Implementation The implementation is straightforward as you can imagine. The processing steps can all be translated into functions. Each can be tested easily and separately. Each has a focused responsibility. And the process flow becomes just a sequence of function calls: Easy to understand. It clearly states how word wrapping works - on a high level of abstraction. And it´s easy to evolve as you´ll see. Flow Design - Increment 2 So far only texts consisting of “average words” are wrapped correctly. Words not fitting in a line will result in lines too long. Wrapping long words is a feature of the requested functionality. Whether it´s there or not makes a difference to the user. To quickly get feedback I decided to first implement a solution without this feature. But now it´s time to add it to deliver the full scope. Fortunately Flow Design automatically leads to code following the Open Closed Principle (OCP). It´s easy to extend it - instead of changing well tested code. How´s that possible? Flow Design allows for extension of functionality by inserting functional units into the flow. That way existing functional units need not be changed. The data flow arrow between functional units is a natural extension point. No need to resort to the Strategy Pattern. No need to think ahead where extions might need to be made in the future. I just “phase in” the remaining processing step: Since neither Extract words nor Reformat know of their environment neither needs to be touched due to the “detour”. The new processing step accepts the output of the existing upstream step and produces data compatible with the existing downstream step. Implementation - Increment 2 A trivial implementation checking the assumption if this works does not do anything to split long words. The input is just passed on: Note how clean WordWrap() stays. The solution is easy to understand. A developer looking at this code sometime in the future, when a new feature needs to be build in, quickly sees how long words are dealt with. Compare this to Robert C. Martin´s solution:[4] How does this solution handle long words? Long words are not even part of the domain language present in the code. At least I need considerable time to understand the approach. Admittedly the Flow Design solution with the full implementation of long word splitting is longer than Robert C. Martin´s. At least it seems. Because his solution does not cover all the “word wrap situations” the Flow Design solution handles. Some lines would need to be added to be on par, I guess. But even then… Is a difference in LOC that important as long as it´s in the same ball park? I value understandability and openness for extension higher than saving on the last line of code. Simplicity is not just less code, it´s also clarity in design. But don´t take my word for it. Try Flow Design on larger problems and compare for yourself. What´s the easier, more straightforward way to clean code? And keep in mind: You ain´t seen all yet ;-) There´s more to Flow Design than described in this chapter. In closing I hope I was able to give you a impression of functional design that makes you hungry for more. To me it´s an inevitable step in software development. Jumping from requirements to code does not scale. And it leads to dirty code all to quickly. Some thought should be invested first. Where there is a clear Entry Point visible, it´s functionality should be designed using data flows. Because with data flows abstraction is possible. For more background on why that´s necessary read my blog article here. For now let me point out to you - if you haven´t already noticed - that Flow Design is a general purpose declarative language. It´s “programming by intention” (Shalloway et al.). Just write down how you think the solution should work on a high level of abstraction. This breaks down a large problem in smaller problems. And by following the PoMO the solutions to those smaller problems are independent of each other. So they are easy to test. Or you could even think about getting them implemented in parallel by different team members. Flow Design not only increases evolvability, but also helps becoming more productive. All team members can participate in functional design. This goes beyon collective code ownership. We´re talking collective design/architecture ownership. Because with Flow Design there is a common visual language to talk about functional design - which is the foundation for all other design activities.   PS: If you like what you read, consider getting my ebook “The Incremental Architekt´s Napkin”. It´s where I compile all the articles in this series for easier reading. I like the strictness of Function Programming - but I also find it quite hard to live by. And it certainly is not what millions of programmers are used to. Also to me it seems, the real world is full of state and side effects. So why give them such a bad image? That´s why functional design takes a more pragmatic approach. State and side effects are ok for processing steps - but be sure to follow the SRP. Don´t put too much of it into a single processing step. ? Image taken from www.physioweb.org ? My code samples are written in C#. C# sports typed function pointers called delegates. Action is such a function pointer type matching functions with signature void someName(T t). Other languages provide similar ways to work with functions as first class citizens - even Java now in version 8. I trust you find a way to map this detail of my translation to your favorite programming language. I know it works for Java, C++, Ruby, JavaScript, Python, Go. And if you´re using a Functional Programming language it´s of course a no brainer. ? Taken from his blog post “The Craftsman 62, The Dark Path”. ?

    Read the article

  • New functional languages

    - by AnnaR
    Functional programming has been around since at least 1958 (creation of Lisp), but is experiencing a renaissance now with old functional languages being dusted off and new functional languages being created. Which functional languages are there that are newly developed or are in the making? I realize that you can write purely functional programs in most high level languages, so with functional languages I imply languages that are specifically designed for functional programming such as F#. If you have links to tutorials, wikis or code examples I encourage you to add them to your answer!

    Read the article

  • Turning your code inside out (functional style) compared to a OO paradigm

    - by Acaz Souza
    I have find this article Turning Your Code Inside Out and I want to know how this approach described in article is for OO programmers/languages. Is this style of design used in OO programmers/languages? What's downsides and goodsides of this approach in a OO language? Update: OO objects have state and behavior, the design explained in article is stateless. Is not only Single Responsability Principle. (If I'm talking shit, please explain to me instead of only downside/close votes)

    Read the article

  • Are there any specific workflows or design patterns that are commonly used to create large functional programming applications?

    - by Andrew
    I have been exploring Clojure for a while now, although I haven't used it on any nontrivial projects. Basically, I have just been getting comfortable with the syntax and some of the idioms. Coming from an OOP background, with Clojure being the first functional language that I have looked very much into, I'm naturally not as comfortable with the functional way of doing things. That said, are there any specific workflows or design patterns that are common with creating large functional applications? I'd really like to start using functional programming "for real", but I'm afraid that with my current lack of expertise, it would result in an epic fail. The "Gang of Four" is such a standard for OO programmers, but is there anything similar that is more directed at the functional paradigm? Most of the resources that I have found have great programming nuggets, but they don't step back to give a broader, more architectural look.

    Read the article

  • How can a non-technical person learn to write a spec for small projects?

    - by Joseph Turian
    How can a non-technical person learn to write specs for small projects? A friend of mine is trying to outsource some development on a statistics project. In particular, he does a lot of work in excel, and wants to outsource the creation of scripts to do what he now does by hand. However, my friend is extremely non-technical. He is poor at writing technical specs. When he does write a spec, it is written the way you would describe doing something in excel (go to this cell and then copy the value to that cell). It is also overly verbose, and does examples several times. I'm not sure if he properly describes corner cases. The first project he outsourced was a failure. I think he overdescribed some details, but underdescribed corner cases. That and/or the coder he hired didn't think through the corner cases and ask appropriate questions. I'm not sure. I got on IM with him and it took me half an hour to dig out a description that should have taken five minutes or less to describe. I wrote the scripts for him at the end, but didn't examine why his process with the coder failed. He has asked me for help. However, I refuse to get involved, because taking his spec and translating it into clear requirements is 10x more work than executing on a clearly written spec. What is the right way for him to learn? Are there resources he could use? Are there ways he can learn from small, low-pressure practice projects with coders? Most of his scripts are statistical and data processing oriented. e.g. take this column and run an average over it. Remove these rows under these conditions. So the challenge is different than spec'ing a web app.

    Read the article

  • How can a non-technical person can learn to write a spec for small projects?

    - by Joseph Turian
    How can a non-technical person learn to write specs for small projects? A friend of mine is trying to outsource some development on a statistics project. In particular, he does a lot of work in excel, and wants to outsource the creation of scripts to do what he now does by hand. However, my friend is extremely non-technical. He is poor at writing technical specs. When he does write a spec, it is written the way you would describe doing something in excel (go to this cell and then copy the value to that cell). It is also overly verbose, and does examples several times. I'm not sure if he properly describes corner cases. The first project he outsourced was a failure. I think he overdescribed some details, but underdescribed corner cases. That and/or the coder he hired didn't think through the corner cases and ask appropriate questions. I'm not sure. I got on IM with him and it took me half an hour to dig out a description that should have taken five minutes or less to describe. I wrote the scripts for him at the end, but didn't examine why his process with the coder failed. He has asked me for help. However, I refuse to get involved, because taking his spec and translating it into clear requirements is 10x more work than executing on a clearly written spec. What is the right way for him to learn? Are there resources he could use? Are there ways he can learn from small, low-pressure practice projects with coders? [edit: Most of his scripts are statistical and data processing oriented. e.g. take this column and run an average over it. Remove these rows under these conditions. So the challenge is different than spec'ing a web app.]

    Read the article

  • Is Haskell's type system an obstacle to understanding functional programming?

    - by FarmBoy
    I'm studying Haskell for the purpose of understanding functional programming, with the expectation that I'll apply the insight that I gain in other languages (Groovy, Python, JavaScript mainly.) I choose Haskell because I had the impression that it is very purely functional, and wouldn't allow for any reliance on state. I did not choose to learn Haskell because I was interested in navigating an extremely rigid type system. My question is this: Is a strong type system a necessary by-product of an extremely pure functional language, or is this an unrelated design choice particular to Haskell? If it is the latter, I'm curious what would be the most purely functional language that is dynamically typed. I'm not particularly opposed to strong typing, it has its place, but I'm having a hard time seeing how it benefits me in this educational endeavor.

    Read the article

  • how a pure functional programming language manage without assignment statements?

    - by Gnijuohz
    When reading the famous SICP,I found the authors seem rather reluctant to introduce the assignment statement to Scheme in Chapter 3.I read the text and kind of understand why they feel so. As Scheme is the first functional programming language I ever know something about,I am kind of surprised that there are some functional programming languages(not Scheme of course) can do without assignments. Let use the example the book offers,the bank account example.If there is no assignment statement,how can this be done?How to change the balance variable?I ask so because I know there are some so-called pure functional languages out there and according to the Turing complete theory,this must can be done too. I learned C,Java,Python and use assignments a lot in every program I wrote.So it's really an eye-opening experience.I really hope someone can briefly explain how assignments are avoided in those functional programming languages and what profound impact(if any) it has on these languages. The example mentioned above is here: (define (make-withdraw balance) (lambda (amount) (if (>= balance amount) (begin (set! balance (- balance amount)) balance) "Insufficient funds"))) This changed the balance by set!.To me it looks a lot like a class method to change the class member balance. As I said,I am not familiar with functional programming languages,so if I said something wrong about them,feel free to point out.

    Read the article

  • Is Haskell's type system an obstacle to understanding functional programming?

    - by Eric Wilson
    I'm studying Haskell for the purpose of understanding functional programming, with the expectation that I'll apply the insight that I gain in other languages (Groovy, Python, JavaScript mainly.) I choose Haskell because I had the impression that it is very purely functional, and wouldn't allow for any reliance on state. I did not choose to learn Haskell because I was interested in navigating an extremely rigid type system. My question is this: Is a strong type system a necessary by-product of an extremely pure functional language, or is this an unrelated design choice particular to Haskell? If it is the latter, I'm curious what would be the most purely functional language that is dynamically typed. I'm not particularly opposed to strong typing, it has its place, but I'm having a hard time seeing how it benefits me in this educational endeavor.

    Read the article

  • Scheme vs Haskell for an Introduction to Functional Programming?

    - by haziz
    I am comfortable with programming in C and C#, and will explore C++ in the future. I may be interested in exploring functional programming as a different programming paradigm. I am doing this for fun, my job does not involve computer programming, and am somewhat inspired by the use of functional programming, taught fairly early, in computer science courses in college. Lambda calculus is certainly beyond my mathematical abilities, but I think I can handle functional programming. Which of Haskell or Scheme would serve as a good intro to functional programming? I use emacs as my text editor and would like to be able to configure it more easily in the future which would entail learning Emacs Lisp. My understanding, however, is that Emacs Lisp is fairly different from Scheme and is also more procedural as opposed to functional. I would likely be using "The Little Schemer" book, which I have already bought, if I pursue Scheme (seems to me a little weird from my limited leafing through it). Or would use the "Learn You a Haskell for Great Good" if I pursue Haskell. I would also watch the Intro to Haskell videos by Dr Erik Meijer on Channel 9. Any suggestions, feedback or input appreciated. Thanks. P.S. BTW I also have access to F# since I have Visual Studio 2010 which I use for C# development, but I don't think that should be my main criteria for selecting a language.

    Read the article

  • Are closures with side-effects considered "functional style"?

    - by Giorgio
    Many modern programming languages support some concept of closure, i.e. of a piece of code (a block or a function) that Can be treated as a value, and therefore stored in a variable, passed around to different parts of the code, be defined in one part of a program and invoked in a totally different part of the same program. Can capture variables from the context in which it is defined, and access them when it is later invoked (possibly in a totally different context). Here is an example of a closure written in Scala: def filterList(xs: List[Int], lowerBound: Int): List[Int] = xs.filter(x => x >= lowerBound) The function literal x => x >= lowerBound contains the free variable lowerBound, which is closed (bound) by the argument of the function filterList that has the same name. The closure is passed to the library method filter, which can invoke it repeatedly as a normal function. I have been reading a lot of questions and answers on this site and, as far as I understand, the term closure is often automatically associated with functional programming and functional programming style. The definition of function programming on wikipedia reads: In computer science, functional programming is a programming paradigm that treats computation as the evaluation of mathematical functions and avoids state and mutable data. It emphasizes the application of functions, in contrast to the imperative programming style, which emphasizes changes in state. and further on [...] in functional code, the output value of a function depends only on the arguments that are input to the function [...]. Eliminating side effects can make it much easier to understand and predict the behavior of a program, which is one of the key motivations for the development of functional programming. On the other hand, many closure constructs provided by programming languages allow a closure to capture non-local variables and change them when the closure is invoked, thus producing a side effect on the environment in which they were defined. In this case, closures implement the first idea of functional programming (functions are first-class entities that can be moved around like other values) but neglect the second idea (avoiding side-effects). Is this use of closures with side effects considered functional style or are closures considered a more general construct that can be used both for a functional and a non-functional programming style? Is there any literature on this topic? IMPORTANT NOTE I am not questioning the usefulness of side-effects or of having closures with side effects. Also, I am not interested in a discussion about the advantages / disadvantages of closures with or without side effects. I am only interested to know if using such closures is still considered functional style by the proponent of functional programming or if, on the contrary, their use is discouraged when using a functional style.

    Read the article

  • Package Dependencies Error in almost every install

    - by Betaxpression
    New to Ubuntu. In the other sofware sources i have "Debian 4.0 eth" officially supported "non-us.debian.org/"; etc ... "ppa.launcpad.net" and installing applications has stopped working. I think i first came across this problem after installing Blender 2.58 When using update manager it is prompting for a partial upgrade. Almost every software when trying to install showing the same error Package Dependencies Error or GPG PUB KEY missing, tried to fixing to them but no luck. Output to: sudo apt-get update && sudo apt-get upgrade (links disabled http:// -- http:/ as new user can't put more no. of hyperlinks) Ign http:/non-us.debian.org stable/non-US InRelease Ign http:/non-us.debian.org stable/non-US Release.gpg Ign http:/non-us.debian.org stable/non-US Release Ign http:/non-us.debian.org stable/non-US/contrib TranslationIndex Ign http:/non-us.debian.org stable/non-US/main TranslationIndex Ign http:/non-us.debian.org stable/non-US/non-free TranslationIndex Err http:/non-us.debian.org stable/non-US/main Sources 503 Service Unavailable Err http:/non-us.debian.org stable/non-US/contrib Sources 503 Service Unavailable Err http:/non-us.debian.org stable/non-US/non-free Sources 503 Service Unavailable Err http:/non-us.debian.org stable/non-US/main amd64 Packages 503 Service Unavailable Err http:/non-us.debian.org stable/non-US/contrib amd64 Packages 503 Service Unavailable Err http:/non-us.debian.org stable/non-US/non-free amd64 Packages 503 Service Unavailable Ign http:/non-us.debian.org stable/non-US/contrib Translation-en_IN Ign http:/non-us.debian.org stable/non-US/contrib Translation-en Ign http:/non-us.debian.org stable/non-US/main Translation-en_IN Ign http:/non-us.debian.org stable/non-US/main Translation-en Ign http:/non-us.debian.org stable/non-US/non-free Translation-en_IN Ign http:/non-us.debian.org stable/non-US/non-free Translation-en Ign http:/archive.ubuntu.com natty InRelease Ign http:/archive.canonical.com natty InRelease Ign http:/extras.ubuntu.com natty InRelease Ign http:/http.us.debian.org stable InRelease Ign http:/ftp.us.debian.org etch InRelease Ign http:/archive.ubuntu.com natty-updates InRelease Hit http:/archive.canonical.com natty Release.gpg Get:1 http:/extras.ubuntu.com natty Release.gpg [72 B] Ign http:/ppa.launchpad.net natty InRelease Get:2 http:/http.us.debian.org stable Release.gpg [1,672 B] Ign http:/linux.dropbox.com natty InRelease Ign http:/ftp.us.debian.org etch Release.gpg Ign http:/archive.ubuntu.com natty-security InRelease Hit http:/archive.canonical.com natty Release Hit http:/extras.ubuntu.com natty Release Ign http:/ppa.launchpad.net natty InRelease Get:3 http:/linux.dropbox.com natty Release.gpg [489 B] Ign http:/ftp.us.debian.org etch Release Ign http:/dl.google.com stable InRelease Get:4 http:/archive.ubuntu.com natty Release.gpg [198 B] Ign http:/ppa.launchpad.net natty InRelease Hit http:/archive.canonical.com natty/partner Sources Hit http:/extras.ubuntu.com natty/main Sources Get:5 http:/linux.dropbox.com natty Release [2,599 B] Get:6 http:/archive.ubuntu.com natty-updates Release.gpg [198 B] Ign http:/ppa.launchpad.net natty InRelease Hit http:/archive.canonical.com natty/partner amd64 Packages Hit http:/extras.ubuntu.com natty/main amd64 Packages Get:7 http:/linux.dropbox.com natty/main amd64 Packages [784 B] Get:8 http:/archive.ubuntu.com natty-security Release.gpg [198 B] Ign http:/ppa.launchpad.net natty InRelease Ign http:/archive.canonical.com natty/partner TranslationIndex Ign http:/extras.ubuntu.com natty/main TranslationIndex Get:9 http:/http.us.debian.org stable Release [104 kB] Ign http:/linux.dropbox.com natty/main TranslationIndex Hit http:/archive.ubuntu.com natty Release Ign http:/ppa.launchpad.net natty InRelease Ign http:/http.us.debian.org stable Release Hit http:/archive.ubuntu.com natty-updates Release Get:10 http:/ppa.launchpad.net natty InRelease [316 B] Ign http:/ppa.launchpad.net natty InRelease Hit http:/archive.ubuntu.com natty-security Release Get:11 http:/ppa.launchpad.net natty InRelease [316 B] Ign http:/ppa.launchpad.net natty InRelease Hit http:/archive.ubuntu.com natty/restricted Sources Get:12 http:/ppa.launchpad.net natty Release.gpg [316 B] Ign http:/http.us.debian.org stable/main Sources/DiffIndex Get:13 http:/ppa.launchpad.net natty Release.gpg [316 B] Hit http:/archive.ubuntu.com natty/main Sources Ign http:/ftp.us.debian.org etch/contrib TranslationIndex Ign http:/http.us.debian.org stable/contrib Sources/DiffIndex Get:14 http:/ppa.launchpad.net natty Release.gpg [1,502 B] Ign http:/http.us.debian.org stable/non-free Sources/DiffIndex Ign http:/ftp.us.debian.org etch/main TranslationIndex Get:15 http:/ppa.launchpad.net natty Release.gpg [1,928 B] Ign http:/http.us.debian.org stable/main amd64 Packages/DiffIndex Ign http:/ftp.us.debian.org etch/non-free TranslationIndex Ign http:/ppa.launchpad.net natty Release.gpg Hit http:/http.us.debian.org stable/contrib amd64 Packages/DiffIndex W: GPG error: http:/http.us.debian.org stable Release: The following signatures couldn't be verified because the public key is not available: NO_PUBKEY AED4B06F473041FA NO_PUBKEY 64481591B98321F9 W: GPG error: http:/ppa.launchpad.net natty InRelease: File /var/lib/apt/lists/partial/ppa.launchpad.net_sunab_kdenlive-release_ubuntu_dists_natty_InRelease doesn't start with a clearsigned message W: GPG error: http:/ppa.launchpad.net natty InRelease: File /var/lib/apt/lists/partial/ppa.launchpad.net_ubuntu-wine_ppa_ubuntu_dists_natty_InRelease doesn't start with a clearsigned message E: Could not open file /var/lib/apt/lists/http.us.debian.org_debian_dists_stable_contrib_binary-amd64_Packages.IndexDiff - open (2: No such file or directory) output to: sudo cat /etc/apt/sources.list # deb cdrom:[Ubuntu 11.04 _Natty Narwhal_ - Release amd64 (20110427.1)]/ natty main restricted # See http:/help.ubuntu.com/community/UpgradeNotes for how to upgrade to # newer versions of the distribution. deb http:/archive.ubuntu.com/ubuntu natty main restricted deb-src http:/archive.ubuntu.com/ubuntu natty restricted main multiverse universe #Added by software-properties ## Major bug fix updates produced after the final release of the ## distribution. deb http:/archive.ubuntu.com/ubuntu natty-updates main restricted deb-src http:/archive.ubuntu.com/ubuntu natty-updates restricted main multiverse universe #Added by software-properties ## N.B. software from this repository is ENTIRELY UNSUPPORTED by the Ubuntu ## team. Also, please note that software in universe WILL NOT receive any ## review or updates from the Ubuntu security team. deb http:/archive.ubuntu.com/ubuntu natty universe deb http:/archive.ubuntu.com/ubuntu natty-updates universe ## N.B. software from this repository is ENTIRELY UNSUPPORTED by the Ubuntu ## team, and may not be under a free licence. Please satisfy yourself as to ## your rights to use the software. Also, please note that software in ## multiverse WILL NOT receive any review or updates from the Ubuntu ## security team. deb http:/archive.ubuntu.com/ubuntu natty multiverse deb http:/archive.ubuntu.com/ubuntu natty-updates multiverse ## Uncomment the following two lines to add software from the 'backports' ## repository. ## N.B. software from this repository may not have been tested as ## extensively as that contained in the main release, although it includes ## newer versions of some applications which may provide useful features. ## Also, please note that software in backports WILL NOT receive any review ## or updates from the Ubuntu security team. # deb http:/us.archive.ubuntu.com/ubuntu/ natty-backports main restricted universe multiverse # deb-src http:/us.archive.ubuntu.com/ubuntu/ natty-backports main restricted universe multiverse deb http:/archive.ubuntu.com/ubuntu natty-security main restricted deb-src http:/archive.ubuntu.com/ubuntu natty-security restricted main multiverse universe #Added by software-properties deb http:/archive.ubuntu.com/ubuntu natty-security universe deb http:/archive.ubuntu.com/ubuntu natty-security multiverse ## Uncomment the following two lines to add software from Canonical's ## 'partner' repository. ## This software is not part of Ubuntu, but is offered by Canonical and the ## respective vendors as a service to Ubuntu users. deb http:/archive.canonical.com/ubuntu natty partner deb-src http:/archive.canonical.com/ubuntu natty partner ## This software is not part of Ubuntu, but is offered by third-party ## developers who want to ship their latest software. deb http:/extras.ubuntu.com/ubuntu natty main deb-src http:/extras.ubuntu.com/ubuntu natty main deb http:/ftp.us.debian.org/debian/ etch main contrib non-free deb-src http:/ftp.us.debian.org/debian/ etch main contrib non-free deb http:/http.us.debian.org/debian stable main contrib non-free deb-src http:/http.us.debian.org/debian stable main contrib non-free deb http:/non-us.debian.org/debian-non-US stable/non-US main contrib non-free deb-src http:/non-us.debian.org/debian-non-US stable/non-US main contrib non-free Thanks But after removing Debian repositories still getting this error: W:GPG error: http://ppa.launchpad.net natty Release: The following signatures couldn't be verified because the public key is not available: NO_PUBKEY 9BDB3D89CE49EC21, W:GPG error: http://ppa.launchpad.net natty Release: The following signatures couldn't be verified because the public key is not available: NO_PUBKEY 80E7349A06ED541C, W:GPG error: http://ppa.launchpad.net natty Release: The following signatures couldn't be verified because the public key is not available: NO_PUBKEY 8C851674F96FD737, W:GPG error: http://ppa.launchpad.net natty Release: The following signatures couldn't be verified because the public key is not available: NO_PUBKEY 94E58C34A8670E8C, E:Unable to parse package file /var/lib/apt/lists/partial/archive.ubuntu.com_ubuntu_dists_natty-updates_multiverse_i18n_Index (1) I actually tried this before, but i am always getting this error --Executing: gpg --ignore-time-conflict --no-options --no-default-keyring --secret-keyring /etc/apt/secring.gpg --trustdb-name /etc/apt/trustdb.gpg --keyring /etc/apt/trusted.gpg --primary-keyring /etc/apt/trusted.gpg --keyserver keyserver.ubuntu.com --recv-keys 8C851674F96FD737 gpg: requesting key F96FD737 from hkp server keyserver.ubuntu.com ?: keyserver.ubuntu.com: Connection refused gpgkeys: HTTP fetch error 7: couldn't connect: Connection refused gpg: no valid OpenPGP data found. gpg: Total number processed: 0

    Read the article

  • Pair programming business logic with a non-IT person

    - by user1598390
    Have you have any experience in which a non-IT person works with a programmer during the coding process? It's like pair programming, but one person is a non-IT person that knows a lot about the business, maybe a process engineer with math background who knows how things are calculated and can understand non-idiomatic, procedural code. I've found that some procedural, domain-specific languages like PL/SQL are quite understandable by non-IT engineers. These person end up being co-authors of the code and guarantee the correctness of formulas, factors etc. I've found this kind of pair programming quite productive, this kind of engineer user feel they are also "owners" and "authors" of the code and help minimize misunderstanding in the communication process. They even help design the test cases. Is this practice common ? Does it have a name ? Have you had similar experiences ?

    Read the article

  • Non-trivial functions that operate on any monad

    - by Strilanc
    I'm looking for examples of interesting methods that take an arbitrary monad and do something useful with it. Monads are extremely general, so methods that operate on monads are widely applicable. On the other hand, methods I know of that can apply to any monad tend to be... really, really trivial. Barely worth extracting into a function. Here's a really boring example: joinTwice. It just flattens an m m m t into an m t: join n = n >>= id joinTwice n = (join . join) n main = print (joinTwice [[[1],[2, 3]], [[4]]]) -- prints [1,2,3,4] The only non-trivial method for monads that I know of is bindFold (see my answer below). Are there more?

    Read the article

< Previous Page | 1 2 3 4 5 6 7 8 9 10 11 12  | Next Page >