Search Results for "auto-py-to-exe"
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Showing 28 open source projects for "auto-py-to-exe"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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blinker-py
Blinker python library for hardware. Works with Raspberry Pi
blinker-py is a Python library for connecting hardware projects to the Blinker IoT platform. It is designed for Raspberry Pi, Banana Pi, Linux devices, and similar single-board or embedded systems. The library helps developers control hardware through the Blinker mobile app, where users can build graphical interfaces with drag-and-drop widgets. -
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redis-py
Redis Python client
redis-py is the official Python client for interacting with Redis, the in-memory data structure store. It supports all Redis commands and data types, making it easy to build caching, messaging, or real-time analytics features in Python applications. With both synchronous and asyncio support, redis-py is suited for modern Python projects and integrates smoothly into web frameworks, task queues, and backend services. -
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pikepdf
A Python library for reading and writing PDF, powered by QPDF
pikepdf is a Python library allowing the creation, manipulation, and repair of PDFs. It provides a Pythonic wrapper around the C++ PDF content transformation library, QPDF. Python + QPDF = “py” + “qpdf” = “pyqpdf”, which looks like a dyslexia test and is no fun to type. But say “pyqpdf” out loud, and it sounds like “pikepdf”. pikepdf is a library intended for developers who want to create, manipulate, parse, repair, and abuse the PDF format. It supports reading and write PDFs, including creating from scratch. Thanks to QPDF, it supports linearizing PDFs and access to encrypted PDFs. -
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Flama
Fire up your models with the flame
Flama is a python library which establishes a standard framework for development and deployment of APIs with special focus on machine learning (ML). The main aim of the framework is to make ridiculously simple the deployment of ML APIs, simplifying (when possible) the entire process to a single line of code. The library builds on Starlette, and provides an easy-to-learn philosophy to speed up the building of highly performant GraphQL, REST and ML APIs. Besides, it comprises an ideal solution... -
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Helium
Lighter web automation with Python
Helium is a Python library built on top of Selenium to make browser automation more intuitive and human-friendly. It replaces verbose boilerplate code with natural language-like API calls such as click("Login") or write("hello", into="Name"). Helium manages browser setup, waits, and teardown, enabling quick development of scripts for testing, scraping, or task automation without requiring deep Selenium knowledge. -
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Python Progressbar
Progressbar 2 - A progress bar for Python 2 and Python 3
A text progress bar is typically used to display the progress of a long-running operation, providing a visual cue that processing is underway. The progressbar is based on the old Python progressbar package that was published on the now-defunct Google Code. Since that project was completely abandoned by its developer and the developer did not respond to my email, I decided to fork the package. This package is still backward compatible with the original progressbar package so you can safely... -
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Emoji for Python
emoji terminal output for Python
Emoji for Python. This project was inspired by kyokomi. The entire set of Emoji codes as defined by the Unicode consortium is supported in addition to a bunch of aliases. By default, only the official list is enabled but doing emoji.emojize(language='alias') enables both the full list and aliases. By default, the language is English (language='en') but also supported languages are Spanish ('es'), Portuguese ('pt'), Italian ('it'), French ('fr'), German ('de'). The... -
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Kornia
Open Source Differentiable Computer Vision Library
...It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within neural networks to train models to perform image transformations, epipolar geometry, depth estimation, and low-level image processing such as filtering and edge detection that operate directly on tensors. ... -
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EKS Best Practices
A best practices guide for day 2 operations
...The repository is maintained by AWS but open to contributions from the community, making it a living document that evolves as Kubernetes and AWS features evolve. Each section dives into operational details—for example, how to manage IAM roles for service accounts, secure the EKS endpoint, handle node auto-scaling, and design for multi-AZ resilience. Because running Kubernetes in production demands many “day-2” considerations (upgrades, drift, monitoring, incident response), the guide provides practical advice beyond simple cluster provisioning. -
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Neural Tangents
Fast and Easy Infinite Neural Networks in Python
Neural Tangents is a high-level neural network API for specifying complex, hierarchical models at both finite and infinite width, built in Python on top of JAX and XLA. It lets researchers define architectures from familiar building blocks—convolutions, pooling, residual connections, and nonlinearities—and obtain not only the finite network but also the corresponding Gaussian Process (GP) kernel of its infinite-width limit. With a single specification, you can compute NNGP and NTK kernels,... -
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FairScale
PyTorch extensions for high performance and large scale training
...It introduced Fully Sharded Data Parallel (FSDP) style techniques that shard model parameters, gradients, and optimizer states across ranks to fit bigger models into the same memory budget. The library also provides pipeline parallelism, activation checkpointing, mixed precision, optimizer state sharding (OSS), and auto-wrapping policies that reduce boilerplate in complex distributed setups. Its components are modular, so teams can adopt just the sharding optimizer or the pipeline engine without rewriting their training loop. FairScale puts emphasis on correctness and debuggability, offering hook points, logging, and reference examples for common trainer patterns. ... -
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Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. -
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earthengine-py-notebooks
A collection of 360+ Jupyter Python notebook examples
earthengine-py-notebooks is a comprehensive collection of hundreds of Jupyter Python notebooks that serve as examples and tutorials for using the Google Earth Engine Python API. These notebooks are organized into thematic areas such as image processing, machine learning, visualization, filtering, and asset management, exposing users to real geospatial analysis tasks. -
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Minkowski Engine
Auto-diff neural network library for high-dimensional sparse tensors
The Minkowski Engine is an auto-differentiation library for sparse tensors. It supports all standard neural network layers such as convolution, pooling, unspooling, and broadcasting operations for sparse tensors. The Minkowski Engine supports various functions that can be built on a sparse tensor. We list a few popular network architectures and applications here. -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than... -
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(py)biblib
A python library to handle BibTeX bibliographic data.
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Robot Framework FTP Library
FTP client for Robot Framework
SOURCE CODE MOVED TO https://github.com/kowalpy/Robot-Framework-FTP-Library . NEW RELEASES WILL APPEAR ONLY AT GITHUB AND PYPI. This Python library makes it possible to test or use FTP server using Robot Framework keywords. Together with the library, there are also available project example and keywords documentation created by libdoc. This sourceforge webpage is linked from http://robotframework.org/#test-libraries as external library so it can be considered as the official Robot... -
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Robot Framework JMeter Library
Robot Framework and JMeter integration
SOURCE CODE MOVED TO https://github.com/kowalpy/Robot-Framework-JMeter-Library . NEW RELEASES WILL APPEAR ONLY AT GITHUB AND PYPI. The Robot Framework library which can be used for starting JMeter and/or analysing and converting JMeter log files into HTML and SQLite format. -
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Gnats.py
GNATS database communication interface classes for Python
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Flask-AppBuilder
Rapid web application development (python + Flask)
Simple and rapid Application builder, built on top of Flask. includes detailed security, auto form generation, google charts and much more. Demo on: http://flaskappbuilder.pythonanywhere.com/ -
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py-astro
An astronomical library.
Python package for calculation right ascension, declination, and distance for solar system planets. -
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vsResolver
DNS Validating Stub Resolver
...These add data origin authentication and data integrity to the Domain Name System. vsResolver extends the dnspython toolkit (http://www.dnspython.org/) and uses the pycrypto library for its underlying crypto implementation(https://www.dlitz.net/software/pycrypto/). Click on this link for a ridiculously simple python page demonstrating vsResolver working - http://superawesum.novas.us/py/hello.py. Try entering some domains and click submit. Then, enable details, click submit to get the details,and compare with what you get for that domain at http://dnssec-debugger.verisignlabs.com. -
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Reblok build an Abstract Syntax Tree (AST) from a python bytecode (typically found in .pyc files).
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A collection of python libraries used by MARIMORE Inc. http://www.marimore.co.jp THIS PROJECT HAS MOVED TO https://github.com/marimore/marimorepy
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This project is redundant. All files have been copied to MaMo Py: https://sourceforge.net/projects/marimorepy/
