Nabu svn235 review

Nabu is a simple framework that extracts chunks of various types of information from documents written in simple text files (written

License: GPL (GNU General Public License) File size: 3K Developer: Martin Blais

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Nabu is a simple framework that extracts chunks of various types of information from documents written in simple text files (written with reStructuredText conventions) and that stores this information (including the document) in a remote database for later retrieval.

The processing and extraction of the document is handled on a server, and there is a small and simple client that is used to push the files to the server for processing and storage (think rsync). The client requires only Python to work.

The presentation layer is left unspecified: you can use whichever web application framework you like to present the extracted data in the way that you prefer.

Here are some key features of "Nabu":
It is flexible: you can use
any text editor you like to edit the files;
any source code control system you like to store and maintain them (or none);
any database for storage;
and any web application framework for presentation. Nabu does not dictate how the information is presented/served to the clients;
you edit files locally, not in a bleeping web browser window (programmers will appreciate the value of this), in your favourite editor environment;
the organization of the source files in subdirectories has nothing to do with how the content is presented. We use a unique ID system (similar to arch) where your document to be published must contain a unique string to mark it with that id. You can put that string in a reStructuredText comment or a bibliographic field. Unlike Wikis, this allows you to change the title of your documents while keeping the possibility of a permanent link to them.
It effectively offers you a sandbox for creating content, and then how you organize and present the content is dictated by ways that you decide, most likely independent of the source file organization structure;
the input data can be scattered over many files, it does not have to be stored in files per-category (for example, you don't have to store all your "contacts" in a single "address book" file, they can be found within/across all your body of published file and a server might present as a single list if desired). I conjecture that this may be closer to how humans think of this data. This body of files can be used to create a mind-mapping system;
we recognize that the value of the information lies in the source itself, the text files. This valuable source remains with you, and you are free to manage them in any way you prefer, with any version control system you like (if you want to do that). You can completely dump the data stored in the database and rebuild it from the text files;
various semantic chunks of content are automatically extracted from your document. These semantic things are easily written with little code and are configurable. Nabu comes with example content extractors;
a light-weight program with minimal dependencies is used to upload the files to the server. The server processes the files for content. This maximizes the potential that you will be able to use Nabu anywhere, on any platform. The client only requires Python to work;