Search Results for "python 3.5 library" - Page 15
Sort By:
Showing 855 open source projects for "python 3.5 library"
View related business solutions-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
-
1
Whisper Library
Whisper is a file-based time-series database format for Graphite
Whisper is one of three components within the Graphite project. Whisper is a fixed-size database, similar in design and purpose to RRD (round-robin-database). It provides fast, reliable storage of numeric data over time. Whisper allows for higher resolution (seconds per point) of recent data to degrade into lower resolutions for long-term retention of historical data. Copies data from src in dst, if missing. Unlike whisper-merge, don't overwrite data that's already present in the target... -
2
Clipper
Polygon and line clipping and offsetting library (C++, C#, Delphi)
This library is now obsolete and no longer being maintained. It has been superceded by my Clipper2 library - https://github.com/AngusJohnson/Clipper2. -
3
rrule.js
JS library for working with recurrence rules for calendar dates
JavaScript library for working with recurrence rules for calendar dates as defined in the iCalendar RFC and more. rrule.js supports recurrence rules as defined in the iCalendar RFC, with a few important differences. It is a partial port of the rrule module from the excellent python-dateutil library. On top of that, it supports parsing and serialization of recurrence rules from and to natural language. -
4
osm4scala
Reading OpenStreetMap Pbf files.
Scala and polyglot Spark library (Scala, PySpark, SparkSQL, ... ) focused on reading OpenStreetMap Pbf files. -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
5
Blankly
Easily build, backtest and deploy your algo in just a few lines
Blankly is a live trading engine, backtest runner and development framework wrapped into one powerful open-source package. Models can be instantly backtested, paper traded, sandbox tested and run live by simply changing a single line. We built blankly for every type of quant including training & running ML models in the same environment, cross-exchange/cross-symbol arbitrage, and even long/short positions on stocks (all with built-in WebSockets). Blankly is the first framework to enable... -
6
-
7
µPipenv
A lightweight wrapper for pip to support requirements.txt
A lightweight wrapper for pip to support requirements.txt, Pipenv and Poetry lock files or converting them to pip-tools compatible output. Designed for containerized Python applications but not limited to them. if requirements.txt state all the packages in a pinned version with hashes (e.g. pip-tools), micropipenv installs packages with a possible fallback if the installation order is relevant. micropipenv does not substitute Poetry it rather complements it for containerized deployments... -
8
SageMaker MXNet Inference Toolkit
Toolkit for allowing inference and serving with MXNet in SageMaker
SageMaker MXNet Inference Toolkit is an open-source library for serving MXNet models on Amazon SageMaker. This library provides default pre-processing, predict and postprocessing for certain MXNet model types and utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep... -
9
The FMI++ Library
A High-level Utility Package for FMI-based Software Development
The Functional Mock-up Interface (FMI) specification intentionally provides only the most essential and fundamental functionalities in the form of a C interface. On the one hand, this increases flexibility in use and portability to virtually any platform. On the other hand, such a low-level approach implies several prerequisites a simulation tool has to fulfill in order to be able to utilize such an FMI component. The FMI++ library addresses this problem for models and tools with... -
99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
-
10
Faster-Rcnn
This is a pytorch implementation library of faster-rcnn
Faster-Rcnn is a PyTorch implementation of the Faster R-CNN two-stage object detection model. It is designed for training and evaluating detectors on VOC-format datasets, including VOC07+12 and custom datasets arranged with VOC-style annotations and images. The repository includes scripts for training, prediction, evaluation, annotation generation, and model summary inspection. It supports backbone options through pretrained VGG and ResNet weights, making it useful for comparing feature... -
11
AugLy
A data augmentations library for audio, image, text, and video
AugLy is a data augmentations library that currently supports four modalities (audio, image, text & video) and over 100 augmentations. Each modality’s augmentations are contained within its own sub-library. These sub-libraries include both function-based and class-based transforms, composition operators, and have the option to provide metadata about the transform applied, including its intensity. AugLy is a great library to utilize for augmenting your data in model training, or to evaluate... -
12
m2cgen
Transform ML models into a native code
m2cgen (Model 2 Code Generator) - is a lightweight library that provides an easy way to transpile trained statistical models into a native code (Python, C, Java, Go, JavaScript, Visual Basic, C#, PowerShell, R, PHP, Dart, Haskell, Ruby, F#, Rust, Elixir). Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies. -
13
Apache MXNet (incubating)
A flexible and efficient library for deep learning
Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable. -
14
Jupyter Dash
Dash v2.11+ has Jupyter support built in
Dash 2.11 and later supports running Dash apps in classic Jupyter Notebooks and in JupyterLab without the need to update the code or use the additional JupyterDash library. If you are using an earlier version of Dash, you can run Dash apps in a notebook using JupyterDash. This page documents additional options available when running Dash apps in notebooks as well as troubleshooting information. -
15
OpenPrompt
An Open-Source Framework for Prompt-Learning
Prompt-learning is the latest paradigm to adapt pre-trained language models (PLMs) to downstream NLP tasks, which modifies the input text with a textual template and directly uses PLMs to conduct pre-trained tasks. OpenPrompt is a library built upon PyTorch and provides a standard, flexible and extensible framework to deploy the prompt-learning pipeline. OpenPrompt supports loading PLMs directly from huggingface transformers. In the future, we will also support PLMs implemented by other... -
16
Binarytree
Python library for studying Binary Trees
Binarytree is Python library that lets you generate, visualize, inspect and manipulate binary trees. Skip the tedious work of setting up test data, and dive straight into practicing algorithms. Heaps and BSTs (binary search trees) are also supported. Binarytree supports another representation which is more compact but without the indexing properties. -
17
CoffeeScript
Unfancy JavaScript
CoffeeScript is a lightweight programming language that compiles into JavaScript. It adds syntactic sugar inspired by Ruby, Python, and Haskell to improve brevity and readability, while producing predictable and efficient JavaScript output. Its design emphasizes that “It’s just JavaScript,” meaning any JS library works seamlessly, and compiled output is clean and performant. Adds syntactic sugar like list comprehensions and destructuring assignment. Supports literate programming via .litcoffee or Markdown-embedded files. -
18
Awesome Conformal Prediction
A professionally curated list of awesome Conformal Prediction videos
awesome-conformal-prediction is a curated “awesome list” repository on GitHub collecting high-quality resources related to conformal prediction: tutorials, books, papers, theses, open-source libraries, videos, and other educational material. It is not a software library itself but a directory of resources for those wanting to learn or work with conformal prediction and uncertainty quantification. This exceptional resource is the culmination of my PhD journey in Machine Learning, specializing... -
19
SageMaker Scikit-Learn Extension
A library of additional estimators and SageMaker tools based on scikit
A library of additional estimators and SageMaker tools based on scikit-learn. This project contains standalone scikit-learn estimators and additional tools to support SageMaker Autopilot. Many of the additional estimators are based on existing scikit-learn estimators. SageMaker Scikit-Learn Extension is a Python module for machine learning built on top of scikit-learn. -
20
Triton
Triton is a dynamic binary analysis library
Triton is a dynamic binary analysis library. It provides internal components that allow you to build your program analysis tools, automate reverse engineering, perform software verification or just emulate code. Linux, Windows and OS X compatible. You can directly compile source code from our Github repository. The Triton library is Linux, Windows and OS X compatible. A potential way to getting started is to see our Python examples already bootstrapped. -
21
Spyne
A transport agnostic sync/async RPC library
Spyne is a Python RPC toolkit that makes it easy to expose online services that have a well-defined API using multiple protocols and transports. It integrates with popular Python web frameworks as well as libraries like SQLAlchemy to keep your code as DRY as possible. Spyne aims to save the protocol implementers the hassle of implementing their own remote procedure call api and the application programmers the hassle of jumping through hoops just to expose their services using multiple... -
22
AWS Step Functions Data Science SDK
For building machine learning (ML) workflows and pipelines on AWS
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. ... -
23
Interpret-Text
State-of-the-art explainers for text-based machine learning models
A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard. Interpret-Text builds on Interpret, an open source python package for training interpretable models and helping to explain blackbox machine learning systems. We have added extensions to support text models. -
24
Detectron2
Next-generation platform for object detection and segmentation
Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. Can be used as a library to support different projects on top of it. We'll... -
25
TensorNetwork
A library for easy and efficient manipulation of tensor networks
TensorNetwork is a high-level library for building and contracting tensor networks—graphical factorizations of large tensors that underpin many algorithms in physics and machine learning. It abstracts networks as nodes and edges, then compiles efficient contraction orders across multiple numeric backends so users can focus on model structure rather than index bookkeeping. Common network families (MPS/TT, PEPS, MERA, tree networks) are expressed with concise APIs that encourage...