Open Source Python Data Management Systems - Page 5

Ocular is a spreadsheet written entirely in python. Cell contents are evaluated by python after any standard spreadsheet coordinates are parsed. This allows the full Monty from Python to be implemented in a visual environment.

OldFileDelete (OFD) is a lightweight and efficient utility designed for those who value minimalism and order. The app helps you instantly clear selected folders of accumulated digital clutter. Featuring a modern flat design, the interface is intuitive: simply select a folder, specify the number of days, and the program will find and remove outdated files. No complex settings—just cleanliness and speed.

OpenPTV is an abbreviation of the open source particle tracking velocimetry. This is an open source framework, developed jointly by academic institutions, that deals primarily with the three-dimensional particle tracking experiments in complex and turbulent flows. More about 3D-PTV on Wikipedia and links from our website: http://www.openptv.net

PBS Cluster Viz is a project to display information useful to admins and users about a computing cluster managed by a PBS-compatible resource manager. Information includes load and job distribution. Interactive as well as static output is available.

PyPotrace is a Python programming language binding for Peter Selinger's Potrace raster to vector conversion algorithm. No separate Potrace library or application required!

Python library for parsing, processing and linearising VRML97 files

#FreeUkraine #SaveUkraine #StopRussia #StopPutin #CrimeaIsUkraine #UnitedForUkraine #RussiaInvadedUkraine UI written using wxPython. Allows you, to copy tables between Oracle databases using drag-n-drop interface. AKA filezilla, but for tables, not files.

Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is available both for Unix and Windows platforms (a dedicated platform archive is available on request). Note : if you have downloaded version 3.12 before the 8th of february, a patch exists for a minor bug on TOutputFileKey file, don't hesitate to ask us.

Display APT (Automatically Programmed Tools) geometry and toolpaths created by the apt360 processor.

VizStack is a framework to run GPU-enabled applications. You may set up tiled displays, and run popular applications on them. VizStack can convert nodes into a shared remote visualization farm. Individual GPUs can be allocated to users too.

A python-based system to diagnosis and make weather maps (wxmap) of numerical weather prediction models using the Grid Analysis and Display System (GrADS) from opengrads.org

g2 is an easy to use, portable and powerful 2D graphics library. It provides a comprehensive set of functions for simultaneous generation of graphical output on different types of devices.

Apache Gravitino is a high-performance, geo-distributed, and federated metadata lake. It manages metadata directly in different sources, types, and regions, providing users with unified metadata access for data and AI assets.

Portable Plot is a pure ansi/iso c++ plot library that makes the construction of native plot widgets easy.

Visual x-ray data processor. The routine, writed in Python using wxPython, NumPy, SciPy and mathplotlib libraries for practical and educational purpose.

AquaTerm is a Mac OS X grahics renderer. It allows command line applications written in ObjC, C, FORTRAN, Lisp, Perl or Python to display vector graphics, text and images using a simple API. Adapters for gnuplot, PGPLOT, and PLplot exists as well.

The 3D Slicer is freely available, open-source software for visualization, registration, segmentation, and quantification of medical image data. Follow the link for more info: http://slicer.org

ADOMA stands for: Alternative Display Of Multiple Alignment. ADOMA can create four different displays of a multiple sequence alignment: a ClustalW alignment in HTML format, a simplified ClustalW alignment in HTML and/or txt format and a colored ClustalW alignment in HTML format. For examples of these outputfiles check the screenshots. ADOMA uses ClustalW to create the multiple alignment from DNA or protein sequences and displays them slightly different than the normal output of ClustalW. ADOMA is a commandline program that can easily be used in pipelines. For more information check the README.md in the Files section. How to cite ADOMA: Zaal, D. and Nota, B. (2016), ADOMA: A Command Line Tool to Modify ClustalW Multiple Alignment Output. Mol. Inf., 35: 42–44. doi: 10.1002/minf.201500083 http://onlinelibrary.wiley.com/doi/10.1002/minf.201500083/abstract

AI Data Science Team is a Python library and agent ecosystem designed to accelerate and automate common data science workflows by modeling them as specialized AI “agents” that can be orchestrated to perform tasks like data cleaning, transformation, analysis, visualization, and machine learning. It provides a modular agent framework where each agent focuses on a step in the typical data science pipeline — for example, loading data from CSV/Excel files, cleaning and wrangling messy datasets, engineering predictive features, building models with AutoML, connecting to SQL databases, and producing visual outputs — all driven by natural language or programmatic instructions. The project includes ready-to-use applications that showcase these agents in action, such as an exploratory data analysis copilot that generates reports, a pandas data analyst that combines wrangling and plotting, and SQL database agents that can query business databases and output results directly.

We actively respond to the Research Open Source Initiative (DOCX) . Open source today is not just open source, but datasets, models, tutorials, and experimental records. We are also exploring other categories of open source solutions and protocols. I hope you will understand this initiative, combine this initiative with your own interests, and do what you can. Everyone's tiny contributions, together, are the entire open source ecosystem. We are iBooker, a large open-source community, we-media, and online earning community, with a QQ group of more than 10,000 people and at least 10,000 subscribers. The number of Github Stars exceeds 60k, and it ranks in the top 100 of all Github organizations. The daily up of all its websites exceeds 4k, and the peak of Alexa ranking is 20k. Our core members are certified as CSDN blog experts and short-book programmers as excellent authors. We have established ApacheCN, a non-profit document, and tutorial translation project.

Simplified interface to the Augmented Reality library ARToolKit for Python and other programming languages.

An AWS Professional Service open-source python initiative that extends the power of Pandas library to AWS connecting DataFrames and AWS data-related services. Easy integration with Athena, Glue, Redshift, Timestream, OpenSearch, Neptune, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON, and EXCEL). Built on top of other open-source projects like Pandas, Apache Arrow and Boto3, it offers abstracted functions to execute usual ETL tasks like load/unload data from Data Lakes, Data Warehouses, and Databases. Convert the column name to be compatible with Amazon Athena and the AWS Glue Catalog. Run a query against AWS CloudWatchLogs Insights and convert the results to Pandas DataFrame. Get QuickSight dashboard ID given a name and fails if there is more than 1 ID associated with this name. List IAM policy assignments in the current Amazon QuickSight account.

aws-sdk-pandas (formerly AWS Data Wrangler) bridges pandas with the AWS analytics stack so DataFrames flow seamlessly to and from cloud services. With a few lines of code, you can read from and write to Amazon S3 in Parquet/CSV/JSON/ORC, register tables in the AWS Glue Data Catalog, and query with Amazon Athena directly into pandas. The library abstracts efficient patterns like partitioning, compression, and vectorized I/O so you get performant data lake operations without hand-rolling boilerplate. It also supports Redshift, OpenSearch, and other services, enabling ETL tasks that blend SQL engines and Python transformations. Operational helpers handle IAM, sessions, and concurrency while exposing knobs for encryption, versioning, and catalog consistency. The result is a productive workflow that keeps your analytics in Python while leveraging AWS-native storage and query engines at scale.

The AWS Step Functions Data Science SDK is an open-source library that allows data scientists to easily create workflows that process and publish machine learning models using Amazon SageMaker and AWS Step Functions. You can create machine learning workflows in Python that orchestrate AWS infrastructure at scale, without having to provision and integrate the AWS services separately. The best way to quickly review how the AWS Step Functions Data Science SDK works is to review the related example notebooks. These notebooks provide code and descriptions for creating and running workflows in AWS Step Functions Using the AWS Step Functions Data Science SDK. In Amazon SageMaker, example Jupyter notebooks are available in the example notebooks portion of a notebook instance. To run the AWS Step Functions Data Science SDK example notebooks locally, download the sample notebooks and open them in a working Jupyter instance.

Agaseous-NES is a graphic app for creating integrated circuit layers. Developers can import Agaseous for SuperWikia Alpha .AJA (Agaseous Joint Application) text files to automate & create asauna plates. Also imports and intergrate Adobe .PSD files.