Is it possible to update an rdf file dynamically from user generated input through a webform? The exact scenario would beskos concept definitions being created and updated through user input to html forms.
I was considering xpath but is there a better / generally accepted / best practice way of doing this kind of thing?
For this type of thing there are IMO two approaches:
1 - Using Named Graphs in a Triple Store
Rather than editing an actual fixed file you use a Graph which is stored as a named graph in a Triple Store that supports triple level updates (i.e. you can change individual Triples in a Graph). For example you could use a store like Virtuoso or a Jena based store (Jena SDB/TDB) to do this, basically any store that supports the SPARUL language or has it's own equivalent.
2 - Using a fixed RDF file and altering it
From your mention of XPath I assume that you are intending to store your file as RDF/XML. While XPath would potentially work for this it's going to be dependent on the exact serialization of your file and may get very complex. If your app is going to allow users to submit and edit their own files then they'll be no guarantees over how the RDF has been serialized into RDF/XML so your XPath expressions might not work. If you control all the serialization and processing of the RDF/XML then you can keep it in a format that your XPath will work on.
From my point of view the simplest way to do this approach is to load the file into memory using an appropriate RDF library, manipulate it in memory and then persist the whole thing back to disk when the user is done (or at regular intervals or whatever is appropriate to your application)
Related
Warning: This question is a more philosophical question than practical, but I find it well as to be asked and answered in practical contexts (forums like StackOverflow here, instead of the SoftwareEngineering stack-exchange website), due to the native development in the actual use de-facto of YAML and the way the way it's specification has evolved and features have been added to it over time. Let's ask:
As opposed to formats/languages/protocols such as JSON, the YAML format allows you (according to this link, that seems pretty official, or at least accurate and reliable source to understand the YAML specification) to embed multiple 'Documents' within one file/stream, using the three-dashes marking ("---").
If so, it's hard to ignore the fact that the concept/model/idea of 'Document' in YAML, is no longer an external definition, or "meta"-directive that helps the human/parser to organize multiple/distincted documents along each other (similar to the way file-systems defining the concept of "file" to organize different files, but each file in itself - does not necessarily recognize that it's a file, or that it's being part of a file system that wraps it, by definition, AFAIK.
However, when YAML allows for a multi-Document YAML files, that gather collections of Documents in a single YAML file (and perhaps in a way that is similar/analogous to HTTP Pipelining approach of HTTP protocol), the concept/model/idea/goal of Document receives a new, wider definition/character de-facto, as a part of the YAML grammar and it's produces, and not just of the YAML specification as an assistive concept or format description that helps to describe the specification.
If so, being a Document part of the language itself, what is the added value of this data-structure, compared to the existing, familiar and well-used good old data-structure of Collection (array of items)?
I'm asking it, because I've seen in this link (here) some snippet (in the second example), which describes a YAML sequence that is actually a collection of logs. For some reason, the author of the example, chose to prefer to present each log as a separate "Document" (separated with three-dashes), gathered together in the same YAML sequence/file, instead of writing a file that has a "Collection" of logs represented with the data-type of array. Why did he choose to do this? Is his choice fit, correct, ideal?
I can speculate that the added value of the distinction between a Document and a Collection become relevant when using more advanced features of the YAML grammar, such as Anchors, Tags, References. I guess every Document provide a guarantee that all these identifiers will be a unique set, and there is no collision or duplicates among them. Am I right? And if so, is this the only advantage, or maybe there are any more justifications for the existence of these two pretty-similar data structures?
My best for now, is to see Document as a "meta"-Collection, that is more strict, and lack of high-level logic, or as two different layers of collection schemes. Is it correct, accurate way of view?
And even if I am right, why in the above example (of the logs document from the link), when there's no use and not imply or expected to use duplications or collisions or even identifiers/anchors or compound structures at all - the author is still choosing to represent the collection's items as separate documents? Is this just not so successful selection of an example? Or maybe I'm missing something, and this is a redundancy in the specification, or an evolving syntactic-sugar due to practical needs?
Because the example was written on a website that looks serious with official information written by professionals who dealt with the essence of the language and its definition, theory and philosophy behind (as opposed to practical uses in the wild), and also in light of other provided examples I have seen in it and the added value of them being meticulous, I prefer not to assume that the example is just simply imperfect/meticulous/fit, and that there may be a good reason to choose to write it this way over another, in the specific case exampled.
First, let's look at the technical difference between the list of documents in a YAML stream and a YAML sequence (which is a collection of ordered items). For this, I'll discuss YAML tags, which are an advanced feature so I'll provide a quick overview:
YAML nodes can have tags, such as !!str (the official tag for string values) or !dice (a local tag that can be interpreted by your application but is unknown to others). This applies to all nodes: Scalars, mappings and sequences. Nodes that do not have such a tag set in the source will be assigned the non-specific tag ?, except for quoted scalars which get ! instead. These non-specific tags are later resolved to specific tags, thereby defining to which kind of data structure the node will be deserialized into.
YAML implementations in scripting languages, such as PyYAML, usually only implement resolution by looking at the node's value. For example, a scalar node containing true will become a boolean value, 42 will become an integer, and droggeljug will become a string.
YAML implementations for languages with static types, however, do this differently. For example, assume you deserialize your YAML into a Java class
public class Config {
String name;
int count;
}
Assume the YAML is
name: 42
count: five
The 42 will become a String despite the fact that it looks like a number. Likewise, five will generate an error because it is not a number; it won't be deserialized into a string. This means that not the content of the node defines how it will be deserialized, but the path to the node.
What does this have to do with documents? Well, the YAML spec says:
Resolving the tag of a node must only depend on the following three parameters: (1) the non-specific tag of the node, (2) the path leading from the root to the node and (3) the content (and hence the kind) of the node.)
So, the technical difference is: If you put your data into a single document with a collection at the top, the YAML processor is allowed to take into account the position of the data in the top-level collection when resolving a tag. However, when you put your data in different documents, the YAML processor must not depend on the position of the document in the YAML stream for resolving the tag.
What does this mean in practice? It means that YAML documents are structurally disjoint from one another. Whether a YAML document is valid or not must not depend on any preceeding or succeeding documents. Consequentially, even when deserialization runs into a semantic problem (such as with the five above) in one document, a following document may still be deserialized successfully.
The goal of this design is to be able to concatenate arbitrary YAML documents together without altering their semantics: A middleware component may, without understanding the semantics of the YAML documents, collect multiple streams together or split up a single stream. As long as they are syntactically correct, stream splitting and merging are sound operations that do not invalidate a YAML document even if another document is structurally invalid.
This design primary focuses on sending and receiving data over networks. Of course, nowadays, YAML is primarily used as configuration language. This is why this feature is seldom used and of rather little importance.
Edit: (Reply to comment)
What about end-cases like a string-tagged Document starts with a folded-string, making even its following "---" and "..." just a characters of the global string?
That is not the case, see rules l-bare-document and c-forbidden. A line containing un-indented ... not followed by non-whitespace will always end a document if one is open.
Moreover, ... doesn't do anything if no document is open. This ensures that a stream merger can always append ... to a document to ensure that the current document is closed, but no additional one is created.
--- has widely been adopted as separator between YAML documents (and, perhaps more prominently, between YAML front matter and content in tools like Jekyll) where ... would have been more appropriate, particularly in Jekyll. This gives the false impression that --- should be used by tooling to separate documents, when in reality ... is the syntactic element designed for that use-case.
In the docs for FieldMask the paths use the field names (e.g., foo.bar.buzz), which means renaming the message field names can result in a breaking change.
Why doesn't FieldMask use the field numbers to define the path?
Something like 1.3.1?
You may want to consider filing an issue on the GitHub protocolbuffers repo for a definitive answer from the code's authors.
Your proposal seems logical. Using names may be a historical artifact. There's a possibly relevant comment on an issue thread in that repo:
https://github.com/protocolbuffers/protobuf/issues/3793#issuecomment-339734117
"You are right that if you use FieldMasks then you can't safely rename fields. But for that matter, if you use the JSON format or text format then you have the same issue that field names are significant and can't be changed easily. Changing field names really only works if you use the binary format only and avoid FieldMasks."
The answer for your question lies in the fact FieldMasks are a convention/utility developed on top of the proto3 schema definition language, and not a feature of it (and that utility is not present in all of the language bindings)
While you’re right in your observation that it can break easily (as schemas tend evolve and change), you need to consider this design choice from a user friendliness POV:
If you’re building an API and want to allow the user to select the field set present inside the response payload (the common use case for field masks), it’ll be much more convenient for you to allow that using field paths, rather then binary fields indices, as the latter would force the user of the gRPC/protocol generated code to be “aware” of the schema. That’s not always the desired case when providing API as a code software packages.
While implementing this as a proto schema feature can allow the user to have the best of both worlds (specify field paths, have them encoded as binary indices) for binary encoding, it would also:
Complicate code generation requirements
Still be an issue for plain text encoding.
So, you can understand why it was left as an “external utility”.
I am currently working on my first small desktop menubar app (macOS, Swift 3). It needs to access
a) A list of words (Think word dictionary, 1k-5k words, per supported language)
b) A list of structured data (Think simple structs, ~500)
I am currently pondering, whether to build these in code - maybe a factory class per language. Or include them in my app as json and parse at runtime. Or maybe build an SQLite file and read that during runtime, although that approach would be harder to diff in source control ...
As I am new to the platform I was wondering whether there might be a better way that I am not aware of, or maybe performance considerations that render one of the mentioned approaches useless.
As usual, thanks in advance folks !
Your listed solutions can be used for this task. However I think for such kind of tasks the best solution is to use CoreData, where you can store a list of words as well as structured data, also make relations between them if you need it
I am new to XQuery and MarkLogic.
I am trying to update documents in MarkLogic and get the extended tree cache full error.
Just to get the work done I have increased the expanded tree cache but that is not recommended.
I would like to tune this query so that it does not need to simultaneously cache as much XML.
Here is my query
I have uploaded my query as an image because it was not so pretty when I pasted it on the editor. If any one knows a better way please suggest.
Thanks in advance.
Expanded tree cache errors can be caused by executing queries that select too many XML nodes at once. In your example, this is likely the culprit: /tx:AttVal[tx:AttributeName/text()=$attributeName].
It's possible that calling text() is the source of your problem (and text() probably not what you mean anyway - see this blog), causing MarkLogic to evaluate that function on all these nodes, and that by simply using /tx:AttVal[tx:AttributeName=$attributeName] it may solve your problem.
Next I would consider an adding a path range index on /tx:AttVal/tx:AttributeName and query those nodes using cts:search and cts:path-range-query. This will be substantially faster than just XPath without a range index. It's also possible to use XPath with a range index: MarkLogic will automatically optimize the XPath expression to use the range index; however, there can be reasons it doesn't optimize the expression correctly, and you would want to check that using xdmp:plan.
Also note that the general best practice recommendation for XML in MarkLogic is to use "semantic XML". E.g., when you mean an attribute, use an attribute: <some-node AttributeName=AttVal>. MarkLogic's indexes are optimized out of the box for semantic XML design. However, if you don't have an option but to work with XML that's not, then that's what path range indexes were designed for.
I've just solved exactly this scenario. There are two things I did
I put the node-replace and node-insert type calls (that is any calls that modify the XML structure into a separate module and then called that module using xdmp:invoke, passing in any parameters required, like this
let $update := xdmp:invoke("/app/lib/update-attribute-node.xqy",
(xs:QName("newValue"), $new),
{xdmp:modules-database()})
The reason why this works is that the call to xdmp:invoke happens in it's own transaction and once it completes, the memory is cleared up. If you don't do this then, each time you call the update or insert function, it will not actually do the write, until the end in a single transaction meaning your memory will fill up pretty quickly.
Any time I needed to loop over paths in MarkLogic (or documents or whatever they are called - I've only been using MarkLogic for a few days) and there are a large number of them I processed them only a few at a time like below. I came up with an elaborate way of skipping and taking only a batch of documents at a time, but you can do it in any number of ways.
let $whatever:= xdmp:directory("/whatever/")[$start to $end]
I also put this into a separate module so that it is processed immediately and not in a single transaction.
Putting all expensive calls into separate modules and taking only a subset of large data sets at a time helped me solve my expanded tree cache full errors.
Is there a data structure within LiveCode that can be used as a "holder" for associated data, letting me handle it collectively? I come from a Java / Javascript / C background so I am looking for a Class or Struct sort of data structure.
I've found examples of Groups, which seem to have some of this functionality, but it feels a bit like I'm bending the language to meet my needs.
As a specific example, suppose I had an image field on my screen that would randomly display an image and, when pressed, play an associated sound clip. I'd expect to create a list of "structures" that contained the path to the image and the path to the associated sound clip, and use that data to populate the image field and to decide what sound clip to play.
Would a Group be the correct structure to use in this case? Or am I approaching this in a way that isn't really fitting with the way LiveCode works?
It takes a little getting used to, but the xTalk world is much simpler and more open than any ordinary procedural language. So much of what you once had to manage is no longer required.
So when splash21 said that you could store all your image and sound references in a custom property, he was really saying that the LiveCode environment contains intrinsic, high level functionality that makes these sorts of things instantly accessible, and the only thing required of you is to call for them, and they simply work.
The only way to appreciate this is to make a few simple programs, to really see what is possible. Make your application. Everything you mentioned can be accomplished with perhaps a dozen lines of code in a single handler. I recommend that you join the LiveCode use list and forums. The community is vibrant and eager to help, frequently with full blown solutions to specific problems, but more importantly, as guides and mentors to new users
Craig Newman
Arrays in LiveCode are actually associative arrays (like hash maps). A key is associated with a value. The value might be as well an array.
Chapter 5.5.7 of the User's Guide says
Array elements may contain nested or sub-elements, making them multi-dimensional.
This type of array is ideal for processing hierarchical data structures such as trees or
XML. To access a sub-element, simply declare it using an additional set of square
brackets.
put "ABC" into myVariable["myKeyName"][“aChildElement”]
see also
How to store pictures in a stack?
Dave- I'm hoping to get a struct-like container implemented in the near future. Meanwhile you can, as splash21 mentioned, use custom properties (or better yet, custom property sets) to do what you want. This will give you a pseudo-struct for each object and you can implement the file and sound specifications into the properties. And if you use that in conjunction with a behavior object you'll end up very close to a real inheritable class formation.