I want to use package:intl to make multi lang html page.
I have seen example/basic_example.dart but don't find document of message_lookup_by_library.dart, intl_helpers.
Is there a simple example use package:intl.
Parts of that are still work in progress, e.g. there should be an update so that plurals and genders work in the next few days. To see the basic workflow, take a look at the intl/test/message_extraction directory and specifically message_extraction_test.dart That does a round-trip extraction, translation, code generation, and running the result. The end result is roughly what you see in basic_example.dart, but it actually does the intermediate steps to produce that.
That test uses a trivial JSON format for output and the translations are hard-coded. You could manually translate things using that format, but for real usage you would probably want to use a real translation tool and a format that it understood. There is a little bit of documentation at http://api.dartlang.org/docs/releases/latest/intl/Intl.html but for the time being you're probably stuck looking at the code and/or asking questions.
Related
I currently work on a personal writing project which has ended up with me maintaining a few different versions due to the differences of the relevant platforms and output formats I want to support that are not trivially solved. After several instances of me glancing at pandoc and the sheer forest that it represents, I have concluded mere templates don't do what I need, and worse, that I seem to need a combination of a custom filter and writer... suffice to say: messing with the AST is where I feel way out of my depth. Enough so that, rather than asking specific questions of 'how do I do X' here, this is a question of 'is X the right way to go about it, or what is the proper way to do it, and can you give an example of how it ties together?'... so if this question is rather lengthy: my apologies.
My current goal is to have custom markup like the following which is supposed to 'track' which character says something:
<paul|"Hi there">
If I convert to HTML, I'd want something similar to:
<span class="speech paul">"Hi there"</span>
to pop out (and perhaps the <p> tags), whereas if it is just pure markdown / plain text, I'd want it to silently disappear:
"Hi there"
Looking at the JSON AST structures I've studied, it would make sense that I'd want a new structure type similar to the 'Emph' tag called 'Speech' which allows whole blobs of text to be put inside of it with a bit of extra information attached (the person speaking). So something like this:
{"t":"Speech","speaker":"paul","c":[ ... ] }
Problem #1: At the point a lua-filter sees the document, it is obviously already distilled to an AST. This means replacing the items in a manner similar to what most macro expander samples do cannot really work since it would require reading forward. With this method, I just replace bits and pieces in place (<NAME| becomes a StartSpeech and the first solitary > that follows becomes an EndSpeech, but that would make malformed input a bigger potential problem because of silent-ish failures. Additionally, these tags would be completely out of sorts with how an AST is supposed to look.
To complicate matters even further, some of my characters end up learning a secondary language throughout the story, for which I apply a different format that contains a simplified understanding of the spoken text with perspective-characters understanding of what was said. Example:
<paul|"Heb je goed geslapen?"|"Did you ?????">
I could probably add a third 'UnderstoodSpeech' group to my filter, but (problem #2) at this point, the relationship between the speaker, the original speech, and the understood translation is completely gone. As long as the final documents need these values in these respective orders and only in these orders, it is fine... but what if I want my HTML version to look like
"Did you?????"
with a tool-tip / hover-over effect containing the original speech? That would be near impossible to achieve because the AST does not contain that kind of relational detail.
Whatever kind of AST I create in the filter is what I need to understand in my custom writer. Ideally, I want to re-use as much stock functionality of pandoc as possible for the writer, but I don't even know if that is feasible at this point.
So now my question: could someone with great pandoc understanding please give me an example on how to keep relevant data-bits together and apply them in the correct manner? By this I mean show a basic example of what needs to be put in the lua-filter and lua-writer scripts in the following toolchain
[CUSTOMIZED MARKDOWN INPUT] -> lua-filter -> lua-writer -> [CUSTOMIZED HTML5 OUTPUT]
I'm running a genetic algorithm program and can find the best individual at the end of the run (hof[0]), but i want to know which generation produced it. Is there any attributes of hof[0] that will help print the individual and the generation that created it.
I tried looking at the manuals and Google for answers but could not find it anywhere.
I also couldn't find a list of the attributes of individuals that I could print. Can someone point to the right link and documentation to that.
Thanks
This deap post suggest tracking the logbook, or explicitly adding the generation to the individual along with fitness:
https://groups.google.com/g/deap-users/c/r7fZbMwHg3I/m/BAzHh2ogBAAJ
For the latter:
If you are working with the algo locally(recommended if working beyond a tutorial as something always comes up like adding plotting or this very questions) then you can modify the fitness update line to resemble:
fitnesses = toolbox.map(toolbox.evaluate, invalid_ind)
for ind, fit in zip(invalid_ind, fitnesses):
ind.fitness.values = fit
ind.generation = gen # now we can: print(hof[0].gen)
if halloffame is not None:
halloffame.update(population)
There is no built in way to do this (yet/to the best of my knowledge), and implementing this so would probably be quite a large task. The simplest of which (simplest in thought, not in implementation) would be to change the individual to be a tuple, where tup[0] is the individual and tup[1] is the generation it was produced in, or something similar.
If you're looking for a hacky way, you could maybe try writing the children of each generation to a text file and cross-checking your final solution with the text file; but other than that I'm not sure.
You could always try posting on their Google Group, though it can take a couple of days for a reply.
Good luck!
Am thinking about a project which might use similar functionality to how "Quick Add" handles parsing natural language into something that can be understood with some level of semantics. I'm interested in understanding this better and wondered what your thoughts were on how this might be implemented.
If you're unfamiliar with what "Quick Add" is, check out Google's KB about it.
6/4/10 Update
Additional research on "Natural Language Parsing" (NLP) yields results which are MUCH broader than what I feel is actually implemented in something like "Quick Add". Given that this feature expects specific types of input rather than the true free-form text, I'm thinking this is a much more narrow implementation of NLP. If anyone could suggest more narrow topic matter that I could research rather than the entire breadth of NLP, it would be greatly appreciated.
That said, I've found a nice collection of resources about NLP including this great FAQ.
I would start by deciding on a standard way to represent all the information I'm interested in: event name, start/end time (and date), guest list, location. For example, I might use an XML notation like this:
<event>
<name>meet Sam</name>
<starttime>16:30 07/06/2010</starttime>
<endtime>17:30 07/06/2010</endtime>
</event>
I'd then aim to build up a corpus of diary entries about dates, annotated with their XML forms. How would I collect the data? Well, if I was Google, I'd probably have all sorts of ways. Since I'm me, I'd probably start by writing down all the ways I could think of to express this sort of stuff, then annotating it by hand. If I could add to this by going through friends' e-mails and whatnot, so much the better.
Now I've got a corpus, it can serve as a set of unit tests. I need to code a parser to fit the tests. The parser should translate a string of natural language into the logical form of my annotation. First, it should split the string into its constituent words. This is is called tokenising, and there is off-the-shelf software available to do it. (For example, see NLTK.) To interpret the words, I would look for patterns in the data: for example, text following 'at' or 'in' should be tagged as a location; 'for X minutes' means I need to add that number of minutes to the start time to get the end time. Statistical methods would probably be overkill here - it's best to create a series of hand-coded rules that express your own knowledge of how to interpret the words, phrases and constructions in this domain.
It would seem that there's really no narrow approach to this problem. I wanted to avoid having to pull along the entirety of NLP to figure out a solution, but I haven't found any alternative. I'll update this if I find a really great solution later.
Before I dive into ANTLR (because it is apparently not for the faint of heart), I just want to make sure I have made the right decision regarding its usage.
I want to create a grammar that will parse in a text file with predefined tags so that I can populate values within my application. (The text file is generated by another application.) So, essentially, I want to be able to parse something like this:
Name: TheFileName
Values: 5 3 1 6 1 3
Other Values: 5 3 1 5 1
In my application, TheFileName is stored as a String, and both sets of values are stored to an array. (This is just a sample, the file is much more complicated.) Anyway, am I at least going down the right path with ANTLR? Any other suggestions?
Edit
The files are created by the user and they define the areas via tags. So, it might look something like this.
Name: <string>TheFileName</string>
Values: <array>5 3 1 6 1 3</array>
Important Value: <double>3.45</double>
Something along those lines.
The basic question is how is the file more complicated? Is it basically more of the same, with a tag, a colon and one or more values, or is the basic structure of the other lines more complex? If it's basically just more of the same, code to recognize and read the data is pretty trivial, and a parser generator isn't likely to gain much. If the other lines have substantially different structure, it'll depend primarily on how they differ.
Edit: Based on what you've added, I'd go one (tiny) step further, and format your file as XML. You can then use existing XML parsers (and such) to read the files, extract data, verify that they fit a specified format, etc.
It depends on what control you have over the format of the file you are parsing. If you have no control then a parser-generator such as ANTLR may be valuable. (We do this ourselves for FORTRAN output files over which we have no control). It's quite a bit of work but we have now mastered the basic ANTLR lexer/parser strategy and it's starting to work well.
If, however, you have some or complete control over the format then create it with as much markup as necessary. I would always create such a file in XML as there are so many tools for processing it (not only the parsing, but also XPath, databases, etc.) In general we use ANTLR to parse semi-structured information into XML.
If you don't need for the format to be custom-built, then you should look into using an existing format such as JSON or XML, for which there are parsers available.
Even if you do need a custom format, you may be better off designing one that is dirt simple so that you don't need a full-blown grammar to parse it. Designing your own scripting grammar from scratch and doing a good job of it is a lot of work.
Writing grammar parsers can also be really fun, so if you're curious then you should go for it. But I don't recommend carelessly mixing learning exercises with practical work code.
Well, if it's "much more complicated", then, yes, a parser generator would be helpful. But, since you don't show the actual format of your file, how could anybody know what might be the right tool for the job?
I use the free GOLD Parser Builder, which is incredibly easy to use, and can generate the parser itself in many different languages. There are samples for parsing such expressions also.
If the format of the file is up to the user can you even define a grammar for it?
Seems like you just want a lexer at best. Using ANTLR just for the lexer part is possible, but would seem like overkill.
Are there any conventions for formatting console output from a command line app for readability and consistency? For instance, do you indent sub-information, when do you print a blank line, if ever, how should you accent important statements.
I've found output can quickly degenerate into a chaotic blur. I'm interested in hearing about what other people do.
Update: Really this is for embedded software which spits debug status out a terminal, but it's pretty much like a console app, and I figured everyone would be more familiar with that. Thanks so far.
I'd differentiate two kinds of programs:
Do you print information that might be used by a script (i.e. it should be parseable)? Then define a pretty strict format and use only that (for example fixed field separators).
Do you print information that need not be parsed by a script (or is there an alternative script-parseable format already)? Then write what comes natural:
My suggestions:
write it so that you would like to read it
indent sub-information 2 or 4 spaces, definitely not more
separate blocks of information by one empty line at most
respect the COLUMN environment variable (and possible ROWS if it applies to your output).
If this is for a *nix environment, then I'd recommend reading Basics of Unix Philosophy. It's not specific to output but there are some good guidelines for command line programs in general.
Expect the output of every program to become the input to another, as yet unknown, program. Don't clutter output with extraneous information. Avoid stringently columnar or binary input formats. Don't insist on interactive input.