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Is there a way to use the namelist I/O feature to read in a derived type with allocatable components?
The only thing I've been able to find about it is https://software.intel.com/en-us/forums/intel-fortran-compiler-for-linux-and-mac-os-x/topic/269585 which ended on an fairly unhelpful note.
Edit:
I have user-defined derived types that need to get filled with information from an input file. So, I'm trying to find a convenient way of doing that. Namelist seems like a good route because it is so succinct (basically two lines). One to create the namelist and then a namelist read. Namelist also seems like a good choice because in the text file it forces you to very clearly show where each value goes which I find highly preferable to just having a list of values that the compiler knows the exact order of. This makes it much more work if I or anyone else needs to know which value corresponds to which variable, and much more work to keep clean when inevitably a new value is needed.
I'm trying to do something of the basic form:
!where myType_T is a type that has at least one allocatable array in it
type(myType_T) :: thing
namelist /nmlThing/ thing
open(1, file"input.txt")
read(1, nml=nmlThing)
I may be misunderstanding user-defined I/O procedures, but they don't seem to be a very generic solution. It seems like I would need to write a new one any time I need to do this action, and they don't seem to natively support the
&nmlThing
thing%name = "thing1"
thing%siblings(1) = "thing2"
thing%siblings(2) = "thing3"
thing%siblings(3) = "thing4"
!siblings is an allocatable array
/
syntax that I find desirable.
There are a few solutions I've found to this problem, but none seem to be very succinct or elegant. Currently, I have a dummy user-defined type that has arrays that are way large instead of allocatable and then I write a function to copy the information from the dummy namelist friendly type to the allocatable field containing type. It works just fine, but it is ugly and I'm up to about 4 places were I need to do this same type of operation in the code.
Hence trying to find a good solution.
If you want to use allocatable components, then you need to have an accessible generic interface for a user defined derived type input/output procedure (typically by the type having a generic binding for such a procedure). You link to a thread with an example with such a procedure.
Once invoked, that user defined derived type input/output procedure is then responsible for reading and writing the data. That can include invoking namelist input/output on the components of the derived type.
Fortran 2003 also offers derived types with length parameters. These may offer a solution without the need for a user defined derived type input/output procedure. However, use of derived types with length parameters, in combination with namelist, will put you firmly in the "highly experimental" category with respect to the current compiler implementation.
In every project I've started in languages without type systems, I eventually begin to invent a runtime type system. Maybe the term "type system" is too strong; at the very least, I create a set of type/value-range validators when I'm working with complex data types, and then I feel the need to be paranoid about where data types can be created and modified.
I hadn't thought twice about it until now. As an independent developer, my methods have been working in practice on a number of small projects, and there's no reason they'd stop working now.
Nonetheless, this must be wrong. I feel as if I'm not using dynamically-typed languages "correctly". If I must invent a type system and enforce it myself, I may as well use a language that has types to begin with.
So, my questions are:
Are there existing programming paradigms (for languages without types) that avoid the necessity of using or inventing type systems?
Are there otherwise common recommendations on how to solve the problems that static typing solves in dynamically-typed languages (without sheepishly reinventing types)?
Here is a concrete example for you to consider. I'm working with datetimes and timezones in erlang (a dynamic, strongly typed language). This is a common datatype I work with:
{{Y,M,D},{tztime, {time, HH,MM,SS}, Flag}}
... where {Y,M,D} is a tuple representing a valid date (all entries are integers), tztime and time are atoms, HH,MM,SS are integers representing a sane 24-hr time, and Flag is one of the atoms u,d,z,s,w.
This datatype is commonly parsed from input, so to ensure valid input and a correct parser, the values need to be checked for type correctness, and for valid ranges. Later on, instances of this datatype are compared to each other, making the type of their values all the more important, since all terms compare. From the erlang reference manual
number < atom < reference < fun < port < pid < tuple < list < bit string
Aside from the confsion of static vs. dynamic and strong vs. weak typing:
What you want to implement in your example isn't really solved by most existing static typing systems. Range checks and complications like February 31th and especially parsed input are usually checked during runtime no matter what type system you have.
Your example being in Erlang I have a few recommendations:
Use records. Besides being usefull and helpfull for a whole bunch of reasons, the give you easy runtime type checking without a lot of effort e.g.:
is_same_day(#datetime{year=Y1, month=M1, day=D1},
#datetime{year=Y2, month=M2, day=D2}) -> ...
Effortless only matches for two datetime records. You could even add guards to check for ranges if the source is untrusted. And it conforms to erlangs let it crash method of error handling: if no match is found you get a badmatch, and can handle this on the level where it is apropriate (usually the supervisor level).
Generally write your code that it crashes when the assumptions are not valid
If this doesn't feel static checked enough: use typer and dialyzer to find the kind of errors that can be found statically, whatever remains will be checkd at runtime.
Don't be too restrictive in your functions what "types" you accept, sometimes the added functionality of just doing someting useful even for different inputs is worth more than checking the types and ranges on every function. If you do it where it matters usually you will catch the error early enough for it to be easy fixable. This is especially true for a functionaly language where you allways know where every value comes from.
A lot of good answers, let me add:
Are there existing programming paradigms (for languages without types) that avoid the necessity of using or inventing type systems?
The most important paradigm, especially in Erlang, is this: Assume the type is right, otherwise let it crash. Don't write excessively checking paranoid code, but assume that the input you get is of the right type or the right pattern. Don't write (there are exceptions to this rule, but in general)
foo({tag, ...}) -> do_something(..);
foo({tag2, ...}) -> do_something_else(..);
foo(Otherwise) ->
report_error(Otherwise),
try to fix problem here...
Kill the last clause and have it crash right away. Let a supervisor and other processes do the cleanup (you can use monitors() for janitorial processes to know when a crash has occurred).
Do be precise however. Write
bar(N) when is_integer(N) -> ...
baz([]) -> ...
baz(L) when is_list(L) -> ...
if the function is known only to work with integers or lists respectively. Yes, it is a runtime check but the goal is to convey information to the programmer. Also, HiPE tend to utilize the hint for optimization and eliminate the type check if possible. Hence, the price may be less than what you think it is.
You choose an untyped/dynamically-typed language so the price you have to pay is that type checking and errors from clashes will happen at runtime. As other posts hint, a statically typed language is not exempt from doing some checks as well - the type system is (usually) an approximation of a proof of correctness. In most static languages you often get input which you can't trust. This input is transformed at the "border" of the application and then converted to an internal format. The conversion serves to mark trust: From now on, the thing has been validated and we can assume certain things about it. The power and correctness of this assumption is directly tied to its type signature and how good the programmer is with juggling the static types of the language.
Are there otherwise common recommendations on how to solve the problems that static typing solves in dynamically-typed languages (without sheepishly reinventing types)?
Erlang has the dialyzer which can be used to statically analyze and infer types of your programs. It will not come up with as many type errors as a type checker in e.g., Ocaml, but it won't "cry wolf" either: An error from the dialyzer is provably an error in the program. And it won't reject a program which may be working ok. A simple example is:
and(true, true) -> true;
and(true, _) -> false;
and(false, _) -> false.
The invocation and(true, greatmistake) will return false, yet a static type system will reject the program because it will infer from the first line that the type signature takes a boolean() value as the 2nd parameter. The dialyzer will accept this function in contrast and give it the signature (boolean(), term()) -> boolean(). It can do this, because there is no need to protect a priori for an error. If there is a mistake, the runtime system has a type check that will capture it.
In order for a statically-typed language to match the flexibility of a dynamically-typed one, I think it would need a lot, perhaps infinitely many, features.
In the Haskell world, one hears a lot of sophisticated, sometimes to the point of being scary, teminology. Type classes. Parametric polymorphism. Generalized algebraic data types. Type families. Functional dependencies. The Ωmega programming language takes it even further, with the website listing "type-level functions" and "level polymorphism", among others.
What are all these? Features added to static typing to make it more flexible. These features can be really cool, and tend to be elegant and mind-blowing, but are often difficult to understand. Learning curve aside, type systems often fail to model real-world problems elegantly. A particularly good example of this is interacting with other languages (a major motivation for C# 4's dynamic feature).
Dynamically-typed languages give you the flexibility to implement your own framework of rules and assumptions about data, rather than be constrained by the ever-limited static type system. However, "your own framework" won't be machine-checked, meaning the onus is on you to ensure your "type system" is safe and your code is well-"typed".
One thing I've found from learning Haskell is that I can carry lessons learned about strong typing and sound reasoning over to weaker-typed languages, such as C and even assembly, and do the "type checking" myself. Namely, I can prove that sections of code are correct in and of themselves, by bearing in mind the rules my functions and values are supposed to follow, and the assumptions I am allowed to make about other functions and values. When debugging, I go through and check things again, and think through whether or not my approach is sound.
The bottom line: dynamic typing puts more flexibility at your fingertips. On the other hand, statically-typed languages tend to be more efficient (by orders of magnitude), and good static type systems drastically cut down on debugging time by letting the computer do much of it for you. If you want the benefits of both, install a static type checker in your brain by learning decent, strongly-typed languages.
Sometimes data need validation. Validating any data received from the network is almost always a good idea — especially data from a public network. Being paranoid here is only good. If something resembling a static type system helps this in the least painful way, so be it. There's a reason why Erlang allows type annotations. Even pattern matching can be seen as just a kind of dynamic type checking; nevertheless, it's a central feature of the language. The very structure of data is its 'type' in Erlang.
The good thing is that you can custom-tailor your 'type system' to your needs, make it flexible and smart, while type systems of OO languages typically have fixed features. When data structures you use are immutable, once you've validated such a structure, you're safe to assume it conforms your restrictions, just like with static typing.
There's no point in being ready to process any kind of data at any point of a program, dynamically-typed or not. A 'dynamic type' is essentially a union of all possible types; limiting it to a useful subset is a valid way to program.
A statically typed language detects type errors at compile time. A dynamically typed language detects them at runtime. There are some modest restrictions on what one can write in a statically typed language such that all type errors can be caught at compile time.
But yes, you still have types even in a dynamically typed language, and that's a good thing. The problem is you wander into lots of runtime checks to ensure that you have the types you think you do, since the compiler hasn't taken care of that for you.
Erlang has a very nice tool for specifying and statically verifying lots of types -- dialyzer: Erlang type system, for references.
So don't reinvent types, use the typing tools that Erlang already provides, to handle the types that already exist in your program (but which you haven't yet specified).
And this on its own won't eliminate range checks, unfortunately. Without lots of special sauce you really have to enforce this on your own by convention (and smart constructors, etc. to help), or fall back to runtime checks, or both.
One of the huge benefits in languages that have some sort of reflection/introspecition is that objects can be automatically constructed from a variety of sources.
For example, in Java I can use the same objects for persisting to a db (with Hibernate), serializing to XML (with JAXB), and serializing to JSON (json-lib). You can do the same in Ruby and Python also usually following some simple rules for properties or annotations for Java.
Thus I don't need lots "Domain Transfer Objects". I can concentrate on the domain I am working in.
It seems in very strict FP like Haskell and Ocaml this is not possible.
Particularly Haskell. The only thing I have seen is doing some sort of preprocessing or meta-programming (ocaml). Is it just accepted that you have to do all the transformations from the bottom upwards?
In other words you have to do lots of boring work to turn a data type in haskell into a JSON/XML/DB Row object and back again into a data object.
I can't speak to OCaml, but I'd say that the main difficulty in Haskell is that deserialization requires knowing the type in advance--there's no universal way to mechanically deserialize from a format, figure out what the resulting value is, and go from there, as is possible in languages with unsound or dynamic type systems.
Setting aside the type issue, there are various approaches to serializing data in Haskell:
The built-in type classes Read/Show (de)serialize algebraic data types and most built-in types as strings. Well-behaved instances should generally be such that read . show is equivalent to id, and that the result of show can be parsed as Haskell source code constructing the serialized value.
Various serialization packages can be found on Hackage; typically these require that the type to be serialized be an instance of some type class, with the package providing instances for most built-in types. Sometimes they merely require an automatically derivable instance of the type-reifying, reflective metaprogramming Data class (the charming fully qualified name for which is Data.Data.Data), or provide Template Haskell code to auto-generate instances.
For truly unusual serialization formats--or to create your own package like the previously mentioned ones--one can reach for the biggest hammer available, sort of a "big brother" to Read and Show: parsing and pretty-printing. Numerous packages are available for both, and while it may sound intimidating at first, parsing and pretty-printing are in fact amazingly painless in Haskell.
A glance at Hackage indicates that serialization packages already exist for various formats, including binary data, JSON, YAML, and XML, though I've not used any of them so I can't personally attest to how well they work. Here's a non-exhaustive list to get you started:
binary: Performance-oriented serialization to lazy ByteStrings
cereal: Similar to binary, but a slightly different interface and uses strict ByteStrings
genericserialize: Serialization via built-in metaprogramming, output format is extensible, includes R5RS sexp output.
json: Lightweight serialization of JSON data
RJson: Serialization to JSON via built-in metaprogramming
hexpat-pickle: Combinators for serialization to XML, using the "hexpat" package
regular-xmlpickler: Serialization to XML of recursive data structures using the "regular" package
The only other problem is that, inevitably, not all types will be serializable--if nothing else, I suspect you're going to have a hard time serializing polymorphic types, existential types, and functions.
For what it's worth, I think the pre-processor solution found in OCaml (as exemplified by sexplib, binprot and json-wheel among others) is pretty great (and I think people do very similar things with Template Haskell). It's far more efficient than reflection, and can also be tuned to individual types in a natural way. If you don't like the auto-generated serializer for a given type foo, you can always just write your own, and it fits beautifully into the auto-generated serializers for types that include foo as a component.
The only downside is that you need to learn camlp4 to write one of these for yourself. But using them is quite easy, once you get your build-system set up to use the preprocessor. It's as simple as adding with sexp to the end of a type definition:
type t = { foo: int; bar: float }
with sexp
and now you have your serializer.
You wanted
to do lot of boring work to turn a data type in haskell into JSON/XML/DB Row object and back again into a data object.
There are many ways to serialize and unserialize data types in Haskell. You can use for example,
Data.Binary
Text.JSON
as well as other common formants (protocol buffers, thrift, xml)
Each package often/usually comes with a macro or deriving mechanism to allow you to e.g. derive JSON. For Data.Binary for example, see this previous answer: Erlang's term_to_binary in Haskell?
The general answer is: we have many great packages for serialization in Haskell, and we tend to use the existing class 'deriving' infrastructure (with either generics or template Haskell macros to do the actual deriving).
My understanding is that the simplest way to serialize and deserialize in Haskell is to derive from Read and Show. This is simple and isn't fullfilling your requirements.
However there are HXT and Text.JSON which seem to provide what you need.
The usual approach is to employ Data.Binary. This provides the basic serialisation capability. Binary instances for data types are easy to write and can easily be built out of smaller units.
If you want to generate the instances automatically then you can use Template Haskell. I don't know of any package to do this, but I wouldn't be surprised if one already exists.
Which do the concepts control flow, data type, statement, expression and operation belong to? Syntax or semantics?
What is the relation between control flow, data type, statement, expression, operation, function, ...? How a program is built from these primitives level by level?
I would like to understand these primitive concepts and their relations in order to figure out what aspects of a new language should one learn.
Thanks and regards!
All of those language elements have both syntax (how it is written) and semantics (how the way it is written corresponds to what it actually means). Control flow determines which statements are executed and when, expressions yield a value and can be made up of functions and other language elements (although the details depend on the programming language). An operation is usually a sequence of statements. The meaning of "function" varies from language to language; in some languages, any operation that can be invoked by name is a function. In other languages, a function is an operation that yields a result (as opposed to a procedure that does not report a result). Some languages also require that functions be non-mutating while procedures can be mutating, although this varies from language to language. Data types encapsulate both data and the operations/procedures/functions that can be operated on that data.
They belong to both worlds:
Syntax will describe which are the operators, which are primitive types (int, float), which are the keywords (return, for, while). So syntax decides which "words" you can use in the programming language. With word I mean every single possible token: = is a token, void is a token, varName12345 is a token that is considered as an identifier, 12.4 is a token considered as a float and so on..
Semantics will describe how these tokens can be combined together inside you language.
For example you will have that while semantics is something like:
WHILE ::= 'while' '(' CONDITION ')' '{' STATEMENTS '}'
CONDITION ::= CONDITION '&&' CONDITION | CONDITION '||' CONDITION | ...
STATEMENTS ::= STATEMENT ';' STATEMENTS | empty_rule
and so on. This is the grammar of the language that describes exactly how the language is structured. So it will be able to decide if a program is correct according to the language semantics.
Then there is a third aspect of the semantics, that is "what does that construct mean?". You can see it as a correspondence between, for example, a for loop and how it is translated into the lower level language needed to be executed.
This third aspect will decide if your program is correct with respect to the allowed operations. Usually you can make a compiler reject many of programs that have no meaning (because they violates the semantic) but to be able to find many different mistakes you will have to introduce a new tool: the type checker that will also check that whenever you do operations they are correct according to the types.
For example you grammar can allow doing varName = 12.4 but the typechecker will use the declaration of varName to understand if you can assign a float to it. (of course we're talking about static type checking)
Those concepts belong to both.
Statements, expressions, control flow operations, data types, etc. have their structure defined using the syntax. However, their meaning comes from the semantics.
When you have defined syntax and semantics for a programming language and its constructs, this basically provides you with a set of building blocks. The syntax is used to understand the structure in the code - usually represented using an abstract syntax tree, or AST. You can then traverse the tree and apply the semantics to each element to execute the program, or generate some instructions for some instruction set so you can execute the code later.
I just came across this question in the Go FAQ, and it reminded me of something that's been bugging me for a while. Unfortunately, I don't really see what the answer is getting at.
It seems like almost every non C-like language puts the type after the variable name, like so:
var : int
Just out of sheer curiosity, why is this? Are there advantages to choosing one or the other?
There is a parsing issue, as Keith Randall says, but it isn't what he describes. The "not knowing whether it is a declaration or an expression" simply doesn't matter - you don't care whether it's an expression or a declaration until you've parsed the whole thing anyway, at which point the ambiguity is resolved.
Using a context-free parser, it doesn't matter in the slightest whether the type comes before or after the variable name. What matters is that you don't need to look up user-defined type names to understand the type specification - you don't need to have understood everything that came before in order to understand the current token.
Pascal syntax is context-free - if not completely, at least WRT this issue. The fact that the variable name comes first is less important than details such as the colon separator and the syntax of type descriptions.
C syntax is context-sensitive. In order for the parser to determine where a type description ends and which token is the variable name, it needs to have already interpreted everything that came before so that it can determine whether a given identifier token is the variable name or just another token contributing to the type description.
Because C syntax is context-sensitive, it very difficult (if not impossible) to parse using traditional parser-generator tools such as yacc/bison, whereas Pascal syntax is easy to parse using the same tools. That said, there are parser generators now that can cope with C and even C++ syntax. Although it's not properly documented or in a 1.? release etc, my personal favorite is Kelbt, which uses backtracking LR and supports semantic "undo" - basically undoing additions to the symbol table when speculative parses turn out to be wrong.
In practice, C and C++ parsers are usually hand-written, mixing recursive descent and precedence parsing. I assume the same applies to Java and C#.
Incidentally, similar issues with context sensitivity in C++ parsing have created a lot of nasties. The "Alternative Function Syntax" for C++0x is working around a similar issue by moving a type specification to the end and placing it after a separator - very much like the Pascal colon for function return types. It doesn't get rid of the context sensitivity, but adopting that Pascal-like convention does make it a bit more manageable.
the 'most other' languages you speak of are those that are more declarative. They aim to allow you to program more along the lines you think in (assuming you aren't boxed into imperative thinking).
type last reads as 'create a variable called NAME of type TYPE'
this is the opposite of course to saying 'create a TYPE called NAME', but when you think about it, what the value is for is more important than the type, the type is merely a programmatic constraint on the data
If the name of the variable starts at column 0, it's easier to find the name of the variable.
Compare
QHash<QString, QPair<int, QString> > hash;
and
hash : QHash<QString, QPair<int, QString> >;
Now imagine how much more readable your typical C++ header could be.
In formal language theory and type theory, it's almost always written as var: type. For instance, in the typed lambda calculus you'll see proofs containing statements such as:
x : A y : B
-------------
\x.y : A->B
I don't think it really matters, but I think there are two justifications: one is that "x : A" is read "x is of type A", the other is that a type is like a set (e.g. int is the set of integers), and the notation is related to "x ε A".
Some of this stuff pre-dates the modern languages you're thinking of.
An increasing trend is to not state the type at all, or to optionally state the type. This could be a dynamically typed langauge where there really is no type on the variable, or it could be a statically typed language which infers the type from the context.
If the type is sometimes given and sometimes inferred, then it's easier to read if the optional bit comes afterwards.
There are also trends related to whether a language regards itself as coming from the C school or the functional school or whatever, but these are a waste of time. The languages which improve on their predecessors and are worth learning are the ones that are willing to accept input from all different schools based on merit, not be picky about a feature's heritage.
"Those who cannot remember the past are condemned to repeat it."
Putting the type before the variable started innocuously enough with Fortran and Algol, but it got really ugly in C, where some type modifiers are applied before the variable, others after. That's why in C you have such beauties as
int (*p)[10];
or
void (*signal(int x, void (*f)(int)))(int)
together with a utility (cdecl) whose purpose is to decrypt such gibberish.
In Pascal, the type comes after the variable, so the first examples becomes
p: pointer to array[10] of int
Contrast with
q: array[10] of pointer to int
which, in C, is
int *q[10]
In C, you need parentheses to distinguish this from int (*p)[10]. Parentheses are not required in Pascal, where only the order matters.
The signal function would be
signal: function(x: int, f: function(int) to void) to (function(int) to void)
Still a mouthful, but at least within the realm of human comprehension.
In fairness, the problem isn't that C put the types before the name, but that it perversely insists on putting bits and pieces before, and others after, the name.
But if you try to put everything before the name, the order is still unintuitive:
int [10] a // an int, ahem, ten of them, called a
int [10]* a // an int, no wait, ten, actually a pointer thereto, called a
So, the answer is: A sensibly designed programming language puts the variables before the types because the result is more readable for humans.
I'm not sure, but I think it's got to do with the "name vs. noun" concept.
Essentially, if you put the type first (such as "int varname"), you're declaring an "integer named 'varname'"; that is, you're giving an instance of a type a name. However, if you put the name first, and then the type (such as "varname : int"), you're saying "this is 'varname'; it's an integer". In the first case, you're giving an instance of something a name; in the second, you're defining a noun and stating that it's an instance of something.
It's a bit like if you were defining a table as a piece of furniture; saying "this is furniture and I call it 'table'" (type first) is different from saying "a table is a kind of furniture" (type last).
It's just how the language was designed. Visual Basic has always been this way.
Most (if not all) curly brace languages put the type first. This is more intuitive to me, as the same position also specifies the return type of a method. So the inputs go into the parenthesis, and the output goes out the back of the method name.
I always thought the way C does it was slightly peculiar: instead of constructing types, the user has to declare them implicitly. It's not just before/after the variable name; in general, you may need to embed the variable name among the type attributes (or, in some usage, to embed an empty space where the name would be if you were actually declaring one).
As a weak form of pattern-matching, it is intelligable to some extent, but it doesn't seem to provide any particular advantages, either. And, trying to write (or read) a function pointer type can easily take you beyond the point of ready intelligability. So overall this aspect of C is a disadvantage, and I'm happy to see that Go has left it behind.
Putting the type first helps in parsing. For instance, in C, if you declared variables like
x int;
When you parse just the x, then you don't know whether x is a declaration or an expression. In contrast, with
int x;
When you parse the int, you know you're in a declaration (types always start a declaration of some sort).
Given progress in parsing languages, this slight help isn't terribly useful nowadays.
Fortran puts the type first:
REAL*4 I,J,K
INTEGER*4 A,B,C
And yes, there's a (very feeble) joke there for those familiar with Fortran.
There is room to argue that this is easier than C, which puts the type information around the name when the type is complex enough (pointers to functions, for example).
What about dynamically (cheers #wcoenen) typed languages? You just use the variable.