Open Source Python Software Development Software - Page 50

Please take a look at our project wiki for more detailed information: https://github.com/monsdar/CxxProf/wiki/What-is-CxxProf%3F

Cyclone is java-based rich GUI web tool for automating tasks with ease. Cyclone is a project that was borne out of necessity. Agreed, there are many native tools that allow task to be scheduled or automated on most operating systems, however, Cyclone is more than just an automation tool. In many programming languages, there are batch module/libraries available to schedule jobs, but need quite a bit of enhancements to provide similar feature set as Cyclone. Cyclone comes with a number of fascinating features Real-time progress and status montoring for jobs Pause, resume and stop an executing job Multi-user environment with in-built authentication and authorization modules Polygot - jobs can be implemented in java, groovy, ruby, javascript and python Easy administration and configuration - user management etc. Extensible security module

This project provides a system tray application that monitors the status of a project which uses a DART dashboard. Status is displayed by color-coded icons, and message dialogs alert the user when the build status changes.

DAXFi is a Python package that helps configure several different kinds of firewalls in a consistent way. The rules are described in XML. It comes with a Python package, useful to build other applications and includes some useful example programs.

Db Api client is a simple Python DB Api v2.0 client. It shows some information about database, tables, table\'s description. Db Api Client provides sql queries executing, shows results, and exports to some formats (html, csv).

DB form generator, for database-content edition. Based on an existing database structure or an XML-based definition, the tool generates a highly customizable set of tools for editing the database tables (PHP/www and Python/GTK interfaces)

DBFrames is an application framework for building data aware applications for Windows Mobile devices. It uses PythonCE, SQLite and PocketPyGui. Version for Android (writen in Java): https://github.com/yurtk/dbfragments

DC/OS (Datacenter Operating System) is an open-source distributed operating system based on the Apache Mesos kernel. It abstracts a cluster of machines into a single logical computer, simplifying the deployment and management of containerized applications and services. DC/OS provides a comprehensive platform for running modern applications with features like container orchestration, service discovery, and scalability.​

A DCPU-16 Assembler in Python. This assembler is based on the specifications published at http://0x10c.com/doc/dcpu-16.txt

Standard linux distributions are not very optimized when used as linux storage appliances. DCT decided to create a linux distrubution based on Debian which has been adjusted to server better as an appliance platform with as main goal storage purposes.

DEE Excellent Editor is a simple source code editor whit syntax highlighting for many languages with a file browser panel to quickly select files. DEE can open files from the local system or directly from an ftp server.

PyTorch training code and pretrained models for DETR (DEtection TRansformer). We replace the full complex hand-crafted object detection pipeline with a Transformer, and match Faster R-CNN with a ResNet-50, obtaining 42 AP on COCO using half the computation power (FLOPs) and the same number of parameters. Inference in 50 lines of PyTorch. What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based global loss, which forces unique predictions via bipartite matching, and a Transformer encoder-decoder architecture. Given a fixed small set of learned object queries, DETR reasons about the relations of the objects and the global image context to directly output the final set of predictions in parallel. Due to this parallel nature, DETR is very fast and efficient.

Build your models with PyTorch, TensorFlow or Apache MXNet. Fast and memory-efficient message passing primitives for training Graph Neural Networks. Scale to giant graphs via multi-GPU acceleration and distributed training infrastructure. DGL empowers a variety of domain-specific projects including DGL-KE for learning large-scale knowledge graph embeddings, DGL-LifeSci for bioinformatics and cheminformatics, and many others. We are keen to bringing graphs closer to deep learning researchers. We want to make it easy to implement graph neural networks model family. We also want to make the combination of graph based modules and tensor based modules (PyTorch or MXNet) as smooth as possible. DGL provides a powerful graph object that can reside on either CPU or GPU. It bundles structural data as well as features for a better control. We provide a variety of functions for computing with graph objects including efficient and customizable message passing primitives for Graph Neural Networks.

The key difference with current graph deep learning libraries, such as PyTorch Geometric (PyG) and Deep Graph Library (DGL), is that, while PyG and DGL support basic graph deep learning operations, DIG provides a unified testbed for higher level, research-oriented graph deep learning tasks, such as graph generation, self-supervised learning, explainability, 3D graphs, and graph out-of-distribution. If you are working or plan to work on research in graph deep learning, DIG enables you to develop your own methods within our extensible framework, and compare with current baseline methods using common datasets and evaluation metrics without extra efforts. It includes unified implementations of data interfaces, common algorithms, and evaluation metrics for several advanced tasks. Our goal is to enable researchers to easily implement and benchmark algorithms.

This is a command line tool that list all registered occurences of a DLL from the windows registry and allows to unregister them all with regsvr32.

This project contains some test scripts and software for Analog Devices' DSP chip emulators. This verifies whether a particular emulator is working correctly with a particular PC and target board.

Scripting languages for the D language.

Simple user database with exports for network infrastruction

DWIG is a software tool that connects existing Delphi code with the Python scripting language. With DWIG, you can easily turn your Delphi units to Python extension modules. The extension modules can be used to control your existing Delphi programs.

Daemonize is a Python library that makes it easy to convert a normal Python program to run as a daemon.

System to assist with the management of a local Buddhist study library. Will download and install chosen documentation (sutras, etc), index them, and provide a web interface. Python, HTML. Needs a webserver, namazu. Can be used for other documents, too.

darts is a Python library for easy manipulation and forecasting of time series. It contains a variety of models, from classics such as ARIMA to deep neural networks. The models can all be used in the same way, using fit() and predict() functions, similar to scikit-learn. The library also makes it easy to backtest models, combine the predictions of several models, and take external data into account. Darts supports both univariate and multivariate time series and models. The ML-based models can be trained on potentially large datasets containing multiple time series, and some of the models offer a rich support for probabilistic forecasting. We recommend to first setup a clean Python environment for your project with at least Python 3.7 using your favorite tool (conda, venv, virtualenv with or without virtualenvwrapper).

This work is some notes of learning and practicing data structures and algorithms. Part I is a brief introduction of basic data structures and algorithms, such as, linked lists, stack, queues, trees, sorting and etc. This book notes about learning data structure and algorithms. It was written in Simplified Chinese but other languages such as English and Traditional Chinese are also working in progress.

dfShell is a graphical shell in the style of a data flow composition tool. The programs launched by the shell can have >1 inputs and outputs. Backwards compatible with command line programs that use stdin and stdout.

Data Science Blogs is a curated repository that aggregates a wide range of high-quality blogs and resources related to data science, machine learning, and analytics into a single organized collection. It serves as a discovery platform for practitioners, researchers, and learners who want to stay updated with industry trends, techniques, and insights without manually searching for reliable sources. The repository includes links to personal blogs, professional publications, and educational resources, often accompanied by RSS feeds for easy subscription and content tracking. By organizing these resources in a centralized and structured format, it reduces the friction associated with finding relevant and trustworthy information in a rapidly evolving field. The project is community-driven, allowing contributors to expand and maintain the list as new blogs emerge and existing ones evolve.