Search Results for "memory test"

There's plenty of other CSV parsers in the wild, but I had a hard time finding what I wanted. Inspired by Python's csv module, I wanted a library with simple, intuitive syntax. Furthermore, I wanted support for special use cases such as calculating statistics on very large files. With the deluge of large datasets available, a performant CSV parser is a necessity. By using overlapped threads, memory-mapped IO, and efficient data structures, this parser can quickly tackle large CSV files....

*asammdf* is a fast Python parser and editor for ASAM (Associtation for Standardisation of Automation and Measuring Systems) MDF / MF4 (Measurement Data Format) files. It supports MDF versions 2 (.dat), 3 (.mdf) and 4 (.mf4). *asammdf* works on Python 2.7, and Python >= 3.4

The gSOAP toolkit is an extensive suite of portable C and C++ software to develop XML Web services with powerful type-safe XML data bindings. Easy-to-use code-generator tools allow you to directly integrate XML data in C and C++. Serializes native application data in XML. Includes WSDL/XSD schema binding and auto-coding tools, stub/skeleton compiler, Web server integration with Apache module and IIS extension, high-performance XML processing with schema validation, fast MIME/MTOM streaming,...

Rdbtools is a parser for Redis' dump.rdb files. The parser generates events similar to an XML sax parser and is very efficient memory-wise. Rdbtools is written in Python, though there are similar projects in other languages. Every run of RDB Tool requires to specify a command to indicate what should be done with the parsed RDB data. Valid commands are JSON, diff, justkeys, justkeyvals and protocol. The JSON command output is UTF-8 encoded JSON. By default, the callback try to parse RDB data...

DJSON is a JSON decoder for Go that is 2~ to 3~ times faster than the standard encoding/json and the existing solutions when dealing with arbitrary JSON payload. It is a good approach for people who are using json.Unmarshal together with interface, don't know what the schema is, and still want good performance with minimal changes. DJSON is faster and allocates less memory than the other alternatives.