Open Source Python Data Management Systems - Page 9
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Python Data Management Systems
View 4225 business solutionsBrowse free open source Python Data Management Systems and projects below. Use the toggles on the left to filter open source Python Data Management Systems by OS, license, language, programming language, and project status.
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End-To-End Document Management SoftwareUnForm® is a platform-independent software product that creates, delivers, stores and retrieves graphically enhanced documents from ERP application printing. A complete, end-to-end document management solution, UnForm interfaces at the point of printing to produce documents in various formats for printing and electronic delivery.
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CompanyCam is a photo-based solution created for contractors, by contractors.Take unlimited photos—which are location and time-stamped, sent to the cloud, and stored securely. Every photo is organized by project and instantly available to your team, allowing you to see what’s going on anytime, anywhere. Annotate photos with drawings, arrows, comments, tags, and voice notes, and create project timelines, photo galleries, reports, and transformation photos through the app. Sharing photos with customers and insurance adjusters has never been easier, and keeping your entire process organized has never been simpler.
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An Open Source IEC 61131-3 Integrated Development Environment, providing PLCOpen SoftPLC programming, CanOpen IO's, and SVG based HMI.
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Blender Multibool, Searching for Fractal
Multibool function is slow ;)
Booleans all meshes on the screen. Plus: A fractal generator and attractor generator with a delicious SEARCH function ;) <meta name="google-site-verification" content="cULQewNGfx-aXCQR9fTJZ1Z7DXbLA5GjqjvAfF_oH5I" /> -
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Bloxs
Build dashboards in Jupyter Notebook with numeric and chart boxes
Bloxs is a simple Python package that helps you display information in an attractive way (formed in blocks). Perfect for building dashboards, reports and apps in the notebook. -
MaintainX is the world-leading mobile-first workflow management platform for industrial and frontline workers.Your day-to-day maintenance tasks, simplified. MaintainX eliminates the paperwork, so you can spend less time on your clipboard and more time getting things done.
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CAPLET
GDS visualization and parallelized capacitance extraction
Project CAPLET is a capacitance extraction toolkit that extract capacitance at field-solver accuracy. CAPLET can directly handle GDS2 layout files into capacitance matrices in both GUI and command line interfaces. The internal extraction algorithm is specialized for VLSI interconnect structures but not exclusively, as long as the structure is of Manhattan geometry and embedded in a uniform dielectric material. -
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A collection of tools for working with the comparative data analysis ontology including import/export facilities for common phylogenetic file formats, and also a triple-store framework.
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Parse, analyze and -- most importantly -- use COBOL data definitions. This gives you access to COBOL data from Python programs. Write data analyzers, one-time data conversion utilities and Python programs that are part of COBOL systems. Really.
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COV2HTML
A visualization and analysis tool of Bacterial NGS data for Biologists
COV2HTML provides an easy and 'in home' web interface for biologists that allows coverage visualization of the NGS alignment needed for the analysis. It combines two essential processes: (i) MAP2COV, a tool that converts the huge NGS mapping or coverage files into light specific coverage files which contains genetic elements informations. (ii) COV2HTML, a visualization interface allowing a real-time analysis of data with selected criteria. Thus this interface offers a visualization of NGS mapping coverage data (DNA-seq, RNA-seq, ChIP-seq and TSS) performed in different prokaryotic organisms (bacteria, viruses...) or different experimental conditions (mutant versus wild type strains or different growth states…) facilitating studies. -
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CSV*Extractor Pro (Windows command line)
Spool you scalar data in CSV format from 14 major Databases.
Command line tool for data export from major relational data stores (RDBMS). DB2 Advanced Enterprise Server DB2 Advanced Workgroup Server DB2 Developer Edition DB2 Enterprise Server DB2 Express DB2 Express C DB2 Workgroup Server Exadata Infobright Informix IDS Informix Innovator C MariaDB MySQL Oracle Oracle XE PostgreSQL SAP Sybase ASE SQL Lite SQL Server Enterprise SQL Server Express Sybase IQ Sybase SQL Anywhere TimesTen -
SOCRadar Extended Threat Intelligence PlatformSOCRadar Extended Threat Intelligence, a natively single platform from its inception that proactively identifies and analyzes cyber threats with contextual and actionable intelligence.
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CSV*Extractor for RDBMS (command line)
Extract table data is CSV format from 14 databases.
Spools data for a given query or table from 14 databases. Windows command-line application. -
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CSV*Loader PRO (Windows command line)
Loads CSV file to14 databases
Windows command line tool for CSV data load to 14 relational stores. -
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CSV*Loader for Oracle
Simplified CSV turbo loader to Oracle
Tired of writing control files? No problem! CSV*Loader will generate control file for SQL*Loader. Too slow? No problem! CSV*Loader turbo mode may load it 10x faster to your Oracle database than your good old Perl::DBI script. -
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# CSV Splitter Uma ferramenta para dividir arquivos CSV em múltiplos arquivos com base na quantidade de registros especificada, mantendo a integridade dos dados e permitindo configurações de charset, separador e formatação. Ideal para lidar com grandes arquivos CSV que precisam ser fragmentados para melhor manuseio e processamento. ## Funcionalidades - **Divisão de CSV**: Divide o arquivo original em múltiplos arquivos CSV, com o número de registros por arquivo definido pelo usuário. - **Detecção Automática de Charset e Separador**: O charset e o separador do arquivo de origem podem ser detectados automaticamente ou especificados manualmente. - **Configuração de Destino Personalizável**: Permite definir charset e separador de destino. - **Formatação de Dados**: Formatação opcional para os padrões BR, EUA, EU e UK, com exemplos para ajudar na escolha do formato desejado. - **Interface Gráfica Intuitiva**: Interface com `Tkinter`, incluindo barra de progresso e log do proc
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CairoPlot is a Python module to plot graphics in an easy and intuitive way, creating beautiful results for presentations, websites and reports.
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CalPyLab is an open source data acquisition and (light) analysis software suite for scientific laboratories. The goal of this project is to provide a lightweight replacement for lab-view, to provide a quick and easy way to connect to your equipment.
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CellTypist
A tool for semi-automatic cell type classification, harmonization
CellTypist is an automated tool for cell type classification, harmonization, and integration. Classification, transfer cell type labels from the reference to query dataset. Harmonization, match and harmonize cell types defined by independent datasets. integration, integrate cell and cell types with supervision from harmonization. CellTypist recapitulates cell type structure and biology of independent datasets. Regularised linear models with Stochastic Gradient Descent provide a fast and accurate prediction. Scalable and flexible. Python-based implementation is easy to integrate into existing pipelines. A community-driven encyclopedia for cell types. -
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Cellicone is a project to develop an artificial life organism with the necessary components to make it comparable to biological life as we know it. This includes components ranging from proteins to cells to organs to limbs, and many steps between.
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Chartshare is a computer based system for the production, analysis, and distribution of Standard Celeration Charts (http://www.celeration.org).
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clusterviz allows to cluster three-dimensional data. The clustering process is visualized using OpenGL. As clustering algorithms the family of k-means algorithms is implemented, including mixture models.
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CoSimA+
The Co-Simulation Adaptation Platform
The co-simulation adapation platform serves as programming framework and middleware to enable coupling of distributed, heterogeneous numerical models. The framework facilitates the adaptation and integration of new sub-models into a common simulation platform. -
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Collaborative Computing Project for NMR
Collaborative Computing Project for NMR (CCPN)
The Collaborative Computational Project for NMR (CCPN) provides tools and knowledge to maximise the impact of the biological NMR studies. The CCPN software facilitates data analysis and software integration. The project actively promotes the exchange of knowledge and provides training and best practices for the NMR community. CCPN also has a leading role in the development of a NMR data-sharing standard and coordination of NMR instrumentation proposals for RCUK and BIS. The 28 partners of CCPN jointly cover all aspects of biomolecular NMR and together they promote excellence in science in their respective fields. -
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CollectD-CSV Plotter
Web interface for visualizing CSV data from CollectD monitoring system
CollectD-CSV Plotter is a web interface for fetching and visualizing data that is saved in CollectD CSV format. An HTML form is used for defining the time interval and choosing the wanted measurements. The plotter is actually a front-end for collectd-csv module (http://pypi.python.org/pypi/collectd-csv/), which it uses for fetching the data. Technologies CollectD-CSV Plotter uses include CGI/Python, HTML5/JavaScript, jQuery, jQuery-UI and Gnuplot. -
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Computer Controlled Optical Microscopy is a package to enable camera equipped microscopes to generate multi-modal time-lapse image sequences of 3D volumes. This is achieved by periodically changing optical settings, xyz positions and acquiring images.
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CorNetMap
A tool for Gene Expression Correlation Network
Capabilities of CorNetMap: 1. Read data as tab-delimited text file. Can be used for analysis of any data set beyond gene expression. 2. Capable of both two-dimensional and multidimensional data analysis. 3. Calculate Pearson correlation and cross-correlation for analysis data with phase difference. 4. Generate correlation Heat-map and draws network map. 5. Save correlation data as text file. How to use and doccumentation: https://sourceforge.net/projects/cornetmap/files/Documentation_corNetMap.pdf Sample data for testing: https://sourceforge.net/projects/cornetmap/files/Test%20Data/ Citation: Cite CornetMap as " Khaund, A. Bose, B. CorNetMap. https://sourceforge.net/projects/cornetmap " Credit: Abhigyan Khaund, Biplab Bose, IIT Guwahati
