Showing 1560 open source projects for "python-dateutil"

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  • Automate contact and company data extraction Icon
    Automate contact and company data extraction

    Build lead generation pipelines that pull emails, phone numbers, and company details from directories, maps, social platforms. Full API access.

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  • 1
    Datasette

    Datasette

    An open source multi-tool for exploring and publishing data

    Datasette is a tool for exploring and publishing data. It helps people take data of any shape or size, analyze and explore it, and publish it as an interactive website and accompanying API. Datasette is aimed at data journalists, museum curators, archivists, local governments, scientists, researchers and anyone else who has data that they wish to share with the world. It is part of a wider ecosystem of tools and plugins dedicated to making working with structured data as productive as...
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  • 2
    SageMaker Training Toolkit

    SageMaker Training Toolkit

    Train machine learning models within Docker containers

    Train machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and...
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  • 3
    CUDOS Framework

    CUDOS Framework

    Command Line Interface tool for Cloud Intelligence Dashboards

    The AWS Cloud Intelligence Dashboards Framework is a set of open-source tools and templates designed to help organizations deploy and manage advanced data visualization dashboards that offer insights into cost, usage, governance, and operational health across AWS environments. It is part of the AWS Solutions Library and includes CloudFormation templates, CLI commands, and pre-built dashboards that collect, process, and visualize data from AWS billing, cost management, budgets, and usage...
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  • 4
    Fondant

    Fondant

    Production-ready data processing made easy and shareable

    Fondant is a modular, pipeline-based framework designed to simplify the preparation of large-scale datasets for training machine learning models, especially foundation models. It offers an end-to-end system for ingesting raw data, applying transformations, filtering, and formatting outputs—all while remaining scalable and traceable. Fondant is designed with reproducibility in mind and supports containerized steps using Docker, making it easy to share and reuse data processing components....
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  • 5
    Elementary

    Elementary

    Open-source data observability for analytics engineers

    Elementary is an open-source data observability solution for data & analytics engineers. Monitor your dbt project and data in minutes, and be the first to know of data issues. Gain immediate visibility, detect data issues, send actionable alerts, and understand the impact and root cause. Generate a data observability report, host it or share with your team. Monitoring of data quality metrics, freshness, volume and schema changes, including anomaly detection. Elementary data monitors are...
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  • 6
    OptScale

    OptScale

    FinOps and MLOps platform to run ML/AI and regular cloud workloads

    Run ML/AI or any type of workload with optimal performance and infrastructure cost. OptScale allows ML teams to multiply the number of ML/AI experiments running in parallel while efficiently managing and minimizing costs associated with cloud and infrastructure resources. OptScale MLOps capabilities include ML model leaderboards, performance bottleneck identification and optimization, bulk run of ML/AI experiments, experiment tracking, and more. The solution enables ML/AI engineers to run...
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  • 7
    whylogs

    whylogs

    The open standard for data logging

    whylogs is an open-source library for logging any kind of data. With whylogs, users are able to generate summaries of their datasets (called whylogs profiles) which they can use to track changes in their dataset Create data constraints to know whether their data looks the way it should. Quickly visualize key summary statistics about their datasets. whylogs profiles are the core of the whylogs library. They capture key statistical properties of data, such as the distribution (far beyond...
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  • 8
    PyTorch Forecasting

    PyTorch Forecasting

    Time series forecasting with PyTorch

    PyTorch Forecasting aims to ease state-of-the-art time series forecasting with neural networks for both real-world cases and research alike. The goal is to provide a high-level API with maximum flexibility for professionals and reasonable defaults for beginners. A time series dataset class that abstracts handling variable transformations, missing values, randomized subsampling, multiple history lengths, etc. A base model class that provides basic training of time series models along with...
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  • 9
    oscar

    oscar

    Domain-driven eCommerce for Django

    Oscar is an open-source eCommerce framework for Django. Oscar makes few assumptions about your project, allowing virtually any part of the framework to be extended and customized. In this way, complex business rules can be captured in an elegant and cohesive way. Any class can be overridden, replaced and extended. This is the key feature that allows any project to be captured accurately in the codebase, no workarounds! A well-designed set of models built on the experience of many e-commerce...
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  • 10
    SDGym

    SDGym

    Benchmarking synthetic data generation methods

    The Synthetic Data Gym (SDGym) is a benchmarking framework for modeling and generating synthetic data. Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking. You also customize the process to include your own work. Select any of the publicly available datasets from the...
    Downloads: 1 This Week
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  • 11
    Mezzanine

    Mezzanine

    CMS framework for Django

    Mezzanine is a powerful open source content management platform built using the Django framework. In many ways it is like many other content management tools, offering an intuitive interface for managing all of your content. But Mezzanine is different in that it provides most of its functionality by default. While other platforms rely heavily on modules or reusable applications, Mezzanine comes ready with all the functionality you need, making it the more efficient choice. Mezzanine has a...
    Downloads: 1 This Week
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  • 12
    SalesGPT

    SalesGPT

    Context-aware AI Sales Agent to automate sales outreach

    This repo is an implementation of a context-aware AI Agent for Sales using LLMs and can work across voice, email and texting (SMS, WhatsApp, WeChat, Weibo, Telegram, etc.). SalesGPT is context-aware, which means it can understand what stage of a sales conversation it is in and act accordingly. Moreover, SalesGPT has access to tools, such as your own pre-defined product knowledge base, significantly reducing hallucinations.
    Downloads: 0 This Week
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  • 13
    Modin

    Modin

    Scale your Pandas workflows by changing a single line of code

    Scale your pandas workflow by changing a single line of code. Modin uses Ray, Dask or Unidist to provide an effortless way to speed up your pandas notebooks, scripts, and libraries. Unlike other distributed DataFrame libraries, Modin provides seamless integration and compatibility with existing pandas code. Even using the DataFrame constructor is identical. It is not necessary to know in advance the available hardware resources in order to use Modin. Additionally, it is not necessary to...
    Downloads: 0 This Week
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  • 14
    data-diff

    data-diff

    Efficiently diff rows across two different databases

    We're excited to announce the launch of a new open-source product, data-diff that makes comparing datasets across databases fast at any scale. data-diff automates data quality checks for data replication and migration. In modern data platforms, data is constantly moving between systems, and at the modern data volume and complexity, systems go out of sync all the time. Until now, there has not been any tooling to ensure that when the data is correctly copied. Replicating data at scale, across...
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  • 15
    ThetaGang

    ThetaGang

    ThetaGang is an IBKR bot for collecting money

    ThetaGang is an IBKR trading bot for collecting premiums by selling options using "The Wheel" strategy. The Wheel is a strategy that surfaced on Reddit but has been used by many in the past. This bot implements a slightly modified version of The Wheel, with my own personal tweaks. The strategy, as implemented here, does a few things differently from the one described in the post above. For one, it's intended to be used to augment a typical index-fund-based portfolio with specific asset...
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  • 16
    Yahoo! Finance market data downloader

    Yahoo! Finance market data downloader

    Yahoo! Finance market data downloader

    Ever since Yahoo! finance decommissioned their historical data API, many programs that relied on it to stop working. yfinance aims to solve this problem by offering a reliable, threaded, and Pythonic way to download historical market data from Yahoo! finance. yfinance aimed to offer a temporary fix to the problem by scraping the data from Yahoo! Finance and returning a the data in the same format as pandas_datareader's get_data_yahoo(), thus keeping the code changes in existing software to a...
    Downloads: 0 This Week
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  • 17
    TensorBoardX

    TensorBoardX

    tensorboard for pytorch (and chainer, mxnet, numpy, etc.)

    The SummaryWriter class provides a high-level API to create an event file in a given directory and add summaries and events to it. The class updates the file contents asynchronously. This allows a training program to call methods to add data to the file directly from the training loop, without slowing down training. TensorboardX now supports logging directly to Comet. Comet is a free cloud based solution that allows you to automatically track, compare and explain your experiments. It adds a...
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  • 18
    Every Door

    Every Door

    A dedicated app for collecting thousands of POI for OpenStreetMap

    The best OpenStreetMap editor for POIs and entrances. The best app for on-the-ground surveying for OpenStreetMap! Add shops and amenities, survey benches and trees, collect addresses, or use them as walking papers. This editor does not make you think. Just go to a mall, and start Every Door. You'll see mapped shops around you: tap on the checkmark for any that are still there, and add shops that are not on the map. That's the entire process: you can keep your entire town up-to-date thanks to...
    Downloads: 0 This Week
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  • 19
    NeuralProphet

    NeuralProphet

    A simple forecasting package

    NeuralProphet bridges the gap between traditional time-series models and deep learning methods. It's based on PyTorch and can be installed using pip. A Neural Network based Time-Series model, inspired by Facebook Prophet and AR-Net, built on PyTorch. You can find the datasets used in the tutorials, including data preprocessing examples, in our neuralprophet-data repository. The documentation page may not we entirely up to date. Docstrings should be reliable, please refer to those when in...
    Downloads: 0 This Week
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  • 20
    AutoGluon

    AutoGluon

    AutoGluon: AutoML for Image, Text, and Tabular Data

    AutoGluon enables easy-to-use and easy-to-extend AutoML with a focus on automated stack ensembling, deep learning, and real-world applications spanning image, text, and tabular data. Intended for both ML beginners and experts, AutoGluon enables you to quickly prototype deep learning and classical ML solutions for your raw data with a few lines of code. Automatically utilize state-of-the-art techniques (where appropriate) without expert knowledge. Leverage automatic hyperparameter tuning,...
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  • 21
    Recommenders

    Recommenders

    Best practices on recommendation systems

    The Recommenders repository provides examples and best practices for building recommendation systems, provided as Jupyter notebooks. The module reco_utils contains functions to simplify common tasks used when developing and evaluating recommender systems. Several utilities are provided in reco_utils to support common tasks such as loading datasets in the format expected by different algorithms, evaluating model outputs, and splitting training/test data. Implementations of several...
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  • 22
    Dagster

    Dagster

    An orchestration platform for the development, production

    Dagster is an orchestration platform for the development, production, and observation of data assets. Dagster as a productivity platform: With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early. Dagster as a robust orchestration engine: Put your pipelines into production with a robust...
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  • 23
    NVIDIA Merlin

    NVIDIA Merlin

    Library providing end-to-end GPU-accelerated recommender systems

    NVIDIA Merlin is an open-source library that accelerates recommender systems on NVIDIA GPUs. The library enables data scientists, machine learning engineers, and researchers to build high-performing recommenders at scale. Merlin includes tools to address common feature engineering, training, and inference challenges. Each stage of the Merlin pipeline is optimized to support hundreds of terabytes of data, which is all accessible through easy-to-use APIs. For more information, see NVIDIA...
    Downloads: 0 This Week
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  • 24
    GemGIS

    GemGIS

    Spatial data processing for geomodeling

    GemGIS is a Python-based, open-source geographic information processing library. It is capable of preprocessing spatial data such as vector data (shape files, geojson files, geopackages,…), raster data (tif, png,…), data obtained from online services (WCS, WMS, WFS) or XML/KML files (soon). Preprocessed data can be stored in a dedicated Data Class to be passed to the geomodeling package GemPy in order to accelerate the model-building process.
    Downloads: 1 This Week
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  • 25
    PortableApps.com

    PortableApps.com

    Portable software for cloud, local, and portable USB drives

    PortableApps.com is the world's most popular portable software solution allowing you to take your favorite software with you. A fully open source and free platform, it works from any synced cloud folder (DropBox, Google Drive, Box, etc), from your local PC on an internal or external drive, or on any portable storage device (USB flash drive, memory card, portable SSD or hard drive, etc) moved between PCs. With millions of users all over the world, nearly 500 real open source and freeware apps...
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    Downloads: 328,385 This Week
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