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PostgreSQL is a sophisticated Object-Relational DBMS, supporting almost all SQL constructs, including subselects, transactions, and user-defined types and functions. It is the most advanced open-source database available anywhere. Commercial Support is also available. The original Postgres code was the effort of many graduate students, undergraduate students, and staff programmers working under the direction of Professor Michael Stonebraker at the University of California, Berkeley. In 1995, Andrew Yu and Jolly Chen took on the task of converting the DBMS query language to SQL and created a new database system which came to known as Postgres95. Many others contributed to the porting, testing, debugging and enhancement of the Postgres95 code. As the code improved, and 1995 faded into memory, PostgreSQL was born. PostgreSQL development is presently being performed by a team of Internet developers who are now responsible for all current and future development. The development team coordinator is Marc G. Fournier (scrappy@PostgreSQL.ORG). Support is available from the PostgreSQL developer/user community through the support mailing list (questions@PostgreSQL.ORG). PostgreSQL is free and the complete source is available.

PostgreSQL is a sophisticated Object-Relational DBMS, supporting almost all SQL constructs, including subselects, transactions, and user-defined types and functions. It is the most advanced open-source database available anywhere. Commercial Support is also available. The original Postgres code was the effort of many graduate students, undergraduate students, and staff programmers working under the direction of Professor Michael Stonebraker at the University of California, Berkeley. In 1995, Andrew Yu and Jolly Chen took on the task of converting the DBMS query language to SQL and created a new database system which came to known as Postgres95. Many others contributed to the porting, testing, debugging and enhancement of the Postgres95 code. As the code improved, and 1995 faded into memory, PostgreSQL was born. PostgreSQL development is presently being performed by a team of Internet developers who are now responsible for all current and future development. The development team coordinator is Marc G. Fournier (scrappy@PostgreSQL.ORG). Support is available from the PostgreSQL developer/user community through the support mailing list (questions@PostgreSQL.ORG). PostgreSQL is free and the complete source is available.

PostgreSQL is a sophisticated Object-Relational DBMS, supporting almost all SQL constructs, including subselects, transactions, and user-defined types and functions. It is the most advanced open-source database available anywhere. Commercial Support is also available. The original Postgres code was the effort of many graduate students, undergraduate students, and staff programmers working under the direction of Professor Michael Stonebraker at the University of California, Berkeley. In 1995, Andrew Yu and Jolly Chen took on the task of converting the DBMS query language to SQL and created a new database system which came to known as Postgres95. Many others contributed to the porting, testing, debugging and enhancement of the Postgres95 code. As the code improved, and 1995 faded into memory, PostgreSQL was born. PostgreSQL development is presently being performed by a team of Internet developers who are now responsible for all current and future development. The development team coordinator is Marc G. Fournier (scrappy@PostgreSQL.ORG). Support is available from the PostgreSQL developer/user community through the support mailing list (questions@PostgreSQL.ORG). PostgreSQL is free and the complete source is available.

Beautify PHP What it does: This program tries to reformat and beautify PHP source code files automatically. The program is Open Source and distributed under the terms of GNU GPL. It is written in PHP and has a web frontend. Who needs it: - people, who get PHP code from other coders and are slightly confused - people, who can't read their own PHP code anymore - people, who want to share their PHP code Basic features: - automatic indentation of PHP source code according to given number of spaces - automatic newlines, if required - includes settings for braces according to C or PEAR style - can make use of PHPs integrated code highlight option - can limit number of chars per line. This will break the code at a space and outputs the rest on the next line with an additional indent. (I used this to reformat my code to put it in a LATEX document. This PHP code normally can't be executed anymore, it is only useful for printout.) - turn off and on beautifying by inserting "// NO_BEAUTIFY" or "// BEAUTIFY" in source code

DataDraw is an ultra-fast persistent database for high performance programs written in C. It's so fast that many programs keep all their data in a DataDraw database, even while being manipulated in inner loops of compute intensive applications. Unlike slow SQL databases, DataDraw databases are compiled, and directly link into your C programs. DataDraw databases are resident in memory, making data manipulation even faster than if they were stored in native C data structures (really). Further, they can automatically support infinite undo/redo, greatly simplifying many applications. DataDraw databases can be persistent. Modifications to persistent data are written to disk as they are made, which of course dramatically slows write times. However, DataDraw databases can also be volatile. Volatile databases exist only in memory, and only for the duration that your program needs it. Volatile databases can be directly manipulated faster than C structures, since data is better organized in memory to optimize cache performance. DataDraw supports modular design. An application can have one or more common persistent databases, and multiple volatile databases to support various tools' data structures. Classes in a tool's database can extend classes in the common database. DataDraw is also 64-bit optimized, allowing programs to run much faster and in less memory than standard C programs using 64-bit pointers. This is because DataDraw databases support over 4 billion objects of a given class with 32-bit object references.

git-annex allows managing files with git, without checking the file contents into git. While that may seem paradoxical, it is useful when dealing with files larger than git can currently easily handle, whether due to limitations in memory, time, or disk space. It can store large files in many places, from local hard drives, to a large number of cloud storage services, including S3, WebDAV, and rsync, with a dozen cloud storage providers usable via plugins. Files can be stored encrypted with gpg, so that the cloud storage provider cannot see your data. git-annex keeps track of where each file is stored, so it knows how many copies are available, and has many facilities to ensure your data is preserved. git-annex can also be used to keep a folder in sync between computers, noticing when files are changed, and automatically committing them to git and transferring them to other computers. The git-annex webapp makes it easy to set up and use git-annex this way.

Typical buffer-based incremental I/O is based around a single loop, which reads data from some source (such as a socket or file), transforms it, and generates one or more outputs (such as a line count, HTTP responses, or modified file). Although efficient and safe, these loops are all single-purpose; it is difficult or impossible to compose buffer-based processing loops. Haskell's concept of "lazy I/O" allows pure code to operate on data from an external source. However, lazy I/O has several shortcomings. Most notably, resources such as memory and file handles can be retained for arbitrarily long periods of time, causing unpredictable performance and error conditions. Enumerators are an efficient, predictable, and safe alternative to lazy I/O. Discovered by Oleg Kiselyov, they allow large datasets to be processed in near constant space by pure code. Although somewhat more complex to write, using enumerators instead of lazy I/O produces more correct programs. This library contains an enumerator implementation for Haskell, designed to be both simple and efficient.

log4net is a tool to help the programmer output log statements to a variety of output targets. In case of problems with an application, it is helpful to enable logging so that the problem can be located. With log4net it is possible to enable logging at runtime without modifying the application binary. The log4net package is designed so that log statements can remain in shipped code without incurring a high performance cost. It follows that the speed of logging (or rather not logging) is crucial. At the same time, log output can be so voluminous that it quickly becomes overwhelming. One of the distinctive features of log4net is the notion of hierarchical loggers. Using these loggers it is possible to selectively control which log statements are output at arbitrary granularity. log4net is designed with two distinct goals in mind: speed and flexibility. Features: * Support for multiple frameworks * Output to multiple logging targets * Hierarchical logging architecture * XML Configuration * Dynamic Configuration * Logging Context * Proven architecture * Modular and extensible design * High performance with flexibility

Pidl is an IDL compiler written in Perl that aims to be somewhat compatible with the midl compiler. IDL stands for "Interface Definition Language". Pidl can generate stubs for DCE/RPC server code, DCE/RPC client code and ethereal dissectors for DCE/RPC traffic. IDL compilers like pidl take a description of an interface as their input and use it to generate C (though support for other languages may be added later) code that can use these interfaces, pretty print data sent using these interfaces, or even generate ethereal dissectors that can parse data sent over the wire by these interfaces. Pidl takes IDL files in the same format as is used by midl, converts it to a .pidl file (which contains pidl's internal representation of the interface) and can then generate whatever output you need. .pidl files should be used for debugging purposes only. Write your interface definitions in .idl format. The goal of pidl is to implement a IDL compiler that can be used while developing the RPC subsystem in Samba (for both marshalling/unmarshalling and debugging purposes).

Pegex is an Acmeist parser framework. It allows you to easily create parsers that will work equivalently in lots of programming languages! The inspiration for Pegex comes from the parsing engine upon which the postmodern programming language Perl 6 is based on. Pegex brings this beauty to the other justmodern languages that have a normal regular expression engine available. Pegex gets it name by combining Parsing Expression Grammars (PEG), with Regular Expessions (Regex). That's actually what Pegex does. PEG is the cool new way to elegantly specify recursive descent grammars. The Perl 6 language is defined in terms of a self modifying PEG language called Perl 6 Rules. Regexes are familiar to programmers of most modern programming languages. Pegex defines a simple PEG syntax, where all the terminals are regexes. This means that Pegex can be quite fast and powerful. Pegex attempts to be the simplest way to define new (or old) Domain Specific Languages (DSLs) that need to be used in several programming languages and environments. Things like JSON, YAML, Markdown etc. It also great for writing parsers/compilers that only need to work in one language.