Open Source Python Enterprise Software

Barman (backup and recovery manager) is an administration tool for disaster recovery of PostgreSQL servers written in Python. It allows to perform remote backups of multiple servers in business critical environments and help DBAs during the recovery phase. Barman's most wanted features include backup catalogs, retention policies, remote recovery, archiving and compression of WAL files and backups. Barman is written and maintained by PostgreSQL professionals 2ndQuadrant.

ConDEnSE (Confidential Data Enabled Statistical Exploration) will be a web-based environment for statistical analysis of confidential data from various database sources, based on Plone and R, and using the Jackknife method of confidentiality protection.

OLAP aggregation engine with MDX support, web interface (slice & dice) and relational database backend. See "Documentation" for more. Presentation: http://cubulus.sourceforge.net/. See online demo courtesy of Webfaction, http://alxtoth.webfactional.com

Pipe your scalar data between Oracle databases.

A group a subprojects for Data Cleaning projects, mainly as a step of a Data Mining Project. Visit www.datacleaningopensource.com to review our current applications or if you want to add yours. NOTE: PROGRAMMING SKILLS ARE REQUIRED.

Command-line tool lets you copy table data from Oracle to SQLServer database. Touch and go design.

Platform Course 5.0.0 is opensource framework for easy development of original solutions for unique business process. Main advantages: cross-domain auth, LDAP integration, cross-browser GWT-based UI, big tables handling, chart and geo maps, input forms on XForms. Tested with MSSQL, PostgreSQL and Oracle. Actual SVN Repository for this product is located at https://share.curs.ru/svn/showcase/branches/stable/ Login: reader Password: reader If you wish to know further details or participate in platform development, fell free to contact us via info@curs.ru Wiki page of the Platform: https://share.curs.ru/wiki

CostosPy esta diseñado para manejar la ejecucion de pequeños proyectos de construcción, ayudar a la facturación y el analisis dia a dia de costos vs producido.

Project has moved to: https://github.com/OptimalBPM/qal QAL is a collection of libraries for mining, transforming and writing data from and to a number of places. Sources and destinations include different SQL and NoSQL backends, file formats like .csv, XML and excel. Even untidy HTML web pages. It has a database abstraction layer that supports connectivity to Postgres, MySQL, DB2, Oracle, MS SQL server. JSON and MongoDB is coming. It uses XML/JSON formats(self-generated SQL schemas) for representing queries, transformation and merging, making it scriptable. This means that QAL can be backend agnostic about a subset of SQL features and data types. Of course custom SQL:s are also supported. It is currently distributed as a Python 3 Library (pip3 install python3-qal) and Debian .deb package. It is related the Optimal BPM project, see its Optimal Sync application for usage examples. The text of this page is released under the Creative Commons Zero Waiver 1.0 (CC0).

TORCH is a web enabled electronic health record (EHR) application. TORCH is usable in single practitioner offices and scalable up to multi-site practices.

Top Engine the Semantic Web Engine for the Enterprise. Top Engine is a Business Rule Engine that utilize OWL DL ontologies for vocabulary primitive to write rules on top of ontology. Top Engine support forward and backward chaining with truth maintenance

An attempt to create a competitive new package for management of a veterinary practice. Goals are to have a solid and robust internal structure and an extremely efficient, attractive, and intuitive user interface.

The Wedgetail project provides the basis for a shared electronic health record. The project provides a schema for an SQL implementation of a sharedEHR, as well as the tools required to interact securely with the database.

To build a public open dataset of chest X-ray and CT images of patients who are positive or suspected of COVID-19 or other viral and bacterial pneumonia (MERS, SARS, and ARDS.). Data will be collected from public sources as well as through indirect collection from hospitals and physicians. All images and data will be released publicly in this GitHub repo. This project is approved by the University of Montreal's Ethics Committee #CERSES-20-058-D. We can extract images from publications. Help identify publications that are not already included using a GitHub issue (DOIs we have are listed in the metadata file). There is a searchable database of COVID-19 papers. We want to improve prognostic predictions to triage and manage patient care. Data is the first step to developing any diagnostic/prognostic tool. Our goal is to use these images to develop AI-based approaches to predict and understand the infection.

tux_oracle allows you create Tuxedo clients and servers that attach an Oracle database

This application allows bulk import and exports between Banner EPAFs and Excel spreadsheets. Despite what your sales rep told you, doing EPAFs in Excel and then importing them into Banner is no easy task. Each EPAF can have a variable number of rows in variable number of tables and transaction numbers must be carefully kept in sync among all of these rows and records. WindEPAF takes this difficult and error-prone process and makes it easy.