Search Results for "ofn-extract-objects.py"
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7 projects for "ofn-extract-objects.py" with 2 filters applied:
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Gen AI apps are built with MongoDB AtlasMongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
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Keep company data safe with Chrome EnterpriseMake AI work your way with Chrome Enterprise. Block unapproved sites and set custom data controls that align with your company's policies.
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ldif-extract
Extrect selected entries from LDIF files like grep
ldif-extract is a small 'grep' like tool to extract and convert data from LDIF files. It could be used standalone or also in a pipe together with other tools like ldapsearch. -
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This small perl program allows you to easily export LDAP entries from an LDAP server (MS ActiveDirectory for example) to csv format. It can export various csv formats and can deal with mutlivalued attributes.
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ldif-preg_replace
sed-like modify and convert LDIF files using regular expressions
...Unlike the sed-command this tool deals well with LDIF files, supporting base64 encoding/decoding and wrapping/folding. It can be used in a pipe, making it the ideal choice for automation and enhances common commands like ldapsearch and ldif-extract. -
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LogMiner is a powerful log analysis package for Apache/IIS (or other web servers using the "combined" or Extended W3C log formats). It can extract and present statistics about visits, hits, traffic, navigation paths, browsers and OS's used by users.
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safecopy is a data recovery tool which tries to extract as much data as possible from a problematic (i.e. damaged sectors) source - like floppy drives, harddisk partitions, CDs, tape devices, ..., where other tools like dd would fail doe to I/O errors.
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A tool to extract the information in any log file into a database. It has no inherent knowledge of particular log formats but by using inbuilt rules and asking a few simple questions should be able to parse any type of text log intelligently.
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