Projects

JsonMaker

An utility with simple methods to serialize Java objects into JSON-formatted ones.

flexxb

FlexXB is an open source library for Adobe Flex/Air applications that provides annotation based marshalling/un-marshalling of Flash objects in order to facilitate data communication between Flex UI and backend servers or to process various content. It offers a built-in xml handling mechanism. ... [More] FlexXB is now serialization format agnostic and allows users to extend the engine and add support for different serialization formats (JSON, etc) while still sharing the base features such as object caching, circular reference handling, constructor annotations, id fields, version extraction. The advantage is that the base features are integrated by default with the new serialization context that defines the new format and one should only care about the actual AS3 object - ? conversions. [Less]

Griffon Thrift Plugin

Provides integration with Apache Thrift – a software framework for scalable cross-language services development. It combines a software stack with a code generation engine to build services that work efficiently and seamlessly between C++, Java, Python, PHP, Ruby, Erlang, Perl, Haskell, C#, Cocoa, Smalltalk, and OCaml.

Serialize.Linq

django-serializable

Highly customizable serialization for Python and Django.

Freeze Dried SharePoint Site Column

This project is a custom site column for SharePoint that “freeze dries” .NET data structures and stores them in a column. Except for what is surfaced to the column rendering in the view, the data is “opaque” to the SharePoint API. By that I mean you can stuff just about anything you want ... [More] into the column and get it back. So other than it being a cool demonstration of how to build a Site column, why would you want to use it, or help me make it better. I don’t know about you, but almost every project I have done needs to track data associated with items, that is not really SharePoint typed data, but needs to be associated with an item. Usually I end up creating an external table, linked on the item Guid, and it serves as a place to store things like workflow state, collections of other things to do, links to other systems, configuration data, audit information ,etc. Well I got tired of writing little SQL tables and procedures and started storing this type of stuff in XML in a Note field in SharePoint. Well that worked fine, except it was almost as cumbersome writing specific parsers to populate data structures as it was to put it in SQL. And, end users sometimes ended up seeing the data (by monkeying with views). So I set about to build a small framework for storing binary serialized data in a SharePoint field, that would render acceptably in list views, and on forms. What I ended up with was this project, called the FreezeDriedDataSiteColumn. Its current codebase lets you store just about anything (I even uploaded a 20 meg file as a byte array) and get it back in your code simply by casting the field to your type. It has a custom field definition, a pretty basic property configuration page and a few cute tricks for getting the custom properties to work in list views. [Less]

pickle-js

pickle.js is a JavaScript implementation of the Python pickle format. It supports pickles containing a cross-language subset of the primitive types. Key differences between pickle.js and pickle.py:text pickles only some types are lossily converted (e.g. int) some types are not supported (e.g. ... [More] class) Key differences between pickles and JSON:pickles are not human readable pickles can express complex objects (multiple references and recursion) APIThe API for pickle.js was chosen to match the Python pickle module. pickle.dumps(object) -> string pickle.loads(string) -> objectConversionsDifferences between Python and JavaScript types prevent pickling with pickle.js from being cleanly invertible. For instance, in Python, there is a distinction between integer and floating point numerical types, but in JavaScript there is only one type. Integers contained within a pickle are unpickeled to Numbers and so on. unpickle (loads) from Python to JavaScript str String int Number float Number list Array dict Object (all keys get stringed) bool Boolean None null pickle (dumps) from JavaScript to Python String str Number float Array list Object dict Boolean bool null None [Less]

floatingstack

Serialzation/Unserizleization is an very important for network programming. This tools can offer an easy way to complete this task.

phpsimpledb

April 17th 2009Given the recent update and how broken this project still is, Im going to move into a different direction. I'll be dropping the filter calls and just allow ordering, indices, and caching results. SQL is not in the mind of a programmer, simpledb aims to simplify the process of ... [More] creating a small database application. So if your making a small application with about 0-10,000 entries per table, consider simpledb. ===Release Log=== Past Releases 0.6.6 Fixed an issue with deleting a row and the key still being visible. 0.6.5 Fixed an issue with moving the database folder to another path. 0.6.4 Fixed bad results with mixed filters and orders. 0.6.3 Fixed key/value of result sets returned by a pure filter. Added ClearCache function 0.6.2 Accidently disabled caching, re-enabled. 0.6.1 New TmpCache, importing ArraySets, and building FromArray. Also fixed issues with Ordering. 0.5.1 Fixed errors with cache. 0.5.0 Fixed errors with empty tables. Filters 6x Faster / Ordering - 3.5x Faster. New Index Format, please use "reindex()" function to reindex your current database files if you are updating from 0.4.3 include 'lib.simpledb.php'; class User extends SimpleDb { protected $__indexes = array('username', 'password'); public $username; public $password; public $signup; public $lastlogin; } $user = new User('data'); $user->reindex();New Function: reindex() - for migration / fix broken indexed files Or if your adding a new index. [Less]

serializer

Serializer is a binary data serializer library written in C++ that is designed to be used for easily parsing binary formatted data in an efficient and platform independent manner. Compatible C++ Compilers: GCC 4.0+ Intel C++ Compiler 9.0+ Microsoft Visual C++ 8.0+ Comeau C/C++ 4.1+