Showing 1332 open source projects for "minecraft(linux)"

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  • 1
    Dask

    Dask

    Parallel computing with task scheduling

    Dask is a Python library for parallel and distributed computing, designed to scale analytics workloads from single machines to large clusters. It integrates with familiar tools like NumPy, Pandas, and scikit-learn while enabling execution across cores or nodes with minimal code changes. Dask excels at handling large datasets that don’t fit into memory and is widely used in data science, machine learning, and big data pipelines.
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  • 2
    pydna

    pydna

    Clone with Python! Data structures for double stranded DNA

    Clone with Python! Data structures for double stranded DNA & simulation of homologous recombination, Gibson assembly, cut & paste cloning. Planning genetic constructs with many parts and assembly steps, such as recombinant metabolic pathways, are often difficult to properly document as is evident from the poor state of documentation in the scientific literature. The pydna python package provide a human-readable formal description of cloning and genetic assembly strategies in Python which...
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  • 3
    Panda-Helper

    Panda-Helper

    Panda-Helper: Data profiling utility for Pandas DataFrames and Series

    Panda-Helper is a simple data-profiling utility for Pandas DataFrames and Series. Assess data quality and usefulness with minimal effort. Quickly perform initial data exploration, so you can move on to more in-depth analysis.
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  • 4
    Recap

    Recap

    Recap tracks and transform schemas across your whole application

    Recap is a schema language and multi-language toolkit to track and transform schemas across your whole application. Your data passes through web services, databases, message brokers, and object stores. Recap describes these schemas in a single language, regardless of which system your data passes through. Recap schemas can be defined in YAML, TOML, JSON, XML, or any other compatible language.
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    Run Page

    Run Page

    Make your own running home page

    GitHub Actions manages automatic synchronization of runs and generation of new pages. Gatsby-generated static pages, fast. Support for Vercel (recommended) and GitHub Pages automated deployment. React Hooks. Mapbox for map display. Supports most sports apps such as nike strava. Automatically backup gpx data for easy backup and uploading to other software.
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  • 6
    Awesome-Quant

    Awesome-Quant

    A curated list of insanely awesome libraries, packages and resources

    awesome-quant is a curated list (“awesome list”) of libraries, packages, articles, and resources for quantitative finance (“quants”). It includes tools, frameworks, research papers, blogs, datasets, etc. It aims to help people working in algorithmic trading, quant investing, financial engineering, etc., find useful open source or educational resources. Licensed under typical “awesome” list standards.
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  • 7
    Online Boutique

    Online Boutique

    Sample cloud-first application with 10 microservices

    Online Boutique is a cloud-first microservices demo application. The application is a web-based e-commerce app where users can browse items, add them to the cart, and purchase them. Google uses this application to demonstrate the use of technologies like Kubernetes, GKE, Istio, Stackdriver, and gRPC. This application works on any Kubernetes cluster, like Google Kubernetes Engine (GKE). It’s easy to deploy with little to no configuration.
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  • 8
    classic.tplx

    classic.tplx

    A more accurate representation of jupyter notebooks

    A more accurate representation of Jupyter notebooks when converting to pdfs. This template was designed to make converted Jupyter notebooks look (almost) identical to the actual notebook. If something doesn't exist in the original notebook then it doesn't belong in the conversion. As of nbconvert 5.5.0, the majority of these improvements have been merged into nbconvert's default template. Version 3.x of this package will continue to support nbconvert 5.5.0 and lower, whereas in the future...
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  • 9
    harmonypy

    harmonypy

    Integrate multiple high-dimensional datasets with fuzzy k-means

    Harmony is an algorithm for integrating multiple high-dimensional datasets. harmonypy is a port of the harmony R package by Ilya Korsunsky. Harmony is a general-purpose R package with an efficient algorithm for integrating multiple data sets. It is especially useful for large single-cell datasets such as single-cell RNA-seq.
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  • 10
    miepython

    miepython

    Mie scattering of light by perfect spheres

    miepython is a pure Python module to calculate light scattering for non-absorbing, partially-absorbing, or perfectly-conducting spheres. Mie theory is used, following the procedure described by Wiscombe. This code has been validated against his results. This code provides functions for calculating the extinction efficiency, scattering efficiency, backscattering, and scattering asymmetry. Moreover, a set of angles can be given to calculate the scattering for a sphere at each of those angles.
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  • 11
    borb

    borb

    borb is a library for reading, creating and manipulating PDF files

    borb is a library for creating and manipulating PDF files in python. borb is a pure python library to read, write, and manipulate PDF documents. It represents a PDF document as a JSON-like data structure of nested lists, dictionaries and primitives (numbers, string, booleans, etc) This is currently a one-man project, so the focus will always be to support those use-cases that are more common in favor of those that are rare.
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  • 12
    Metacrafter

    Metacrafter

    Metadata and data identification tool and Python library

    Python command line tool and Python engine to label table fields and fields in data files. It could help to find meaningful data in your tables and data files or to find Personal identifiable information (PII). Metacrafter is a rule-based tool that helps to label fields of the tables in databases. It scans table and finds person names, surnames, midnames, PII data, basic identifiers like UUID/GUID. These rules written as .yaml files and could be easily extended.
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  • 13
    CellTypist

    CellTypist

    A tool for semi-automatic cell type classification, harmonization

    CellTypist is an automated tool for cell type classification, harmonization, and integration. Classification, transfer cell type labels from the reference to query dataset. Harmonization, match and harmonize cell types defined by independent datasets. integration, integrate cell and cell types with supervision from harmonization. CellTypist recapitulates cell type structure and biology of independent datasets. Regularised linear models with Stochastic Gradient Descent provide a fast and...
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  • 14
    LIFELINES

    LIFELINES

    Survival analysis in Python

    LIFELINES is a pure Python library for survival analysis, a statistical field focused on modeling time until an event occurs. It can be used for traditional cases like medical survival time, but also for business and product questions such as churn, subscription length, equipment failure, and customer retention. The library includes estimators such as Kaplan-Meier, Nelson-Aalen, and regression-based survival models. It is designed to be accessible to Python users and works well with common...
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  • 15
    Pyper

    Pyper

    Concurrent Python made simple

    Pyper is a Python-native orchestration and scheduling framework designed for modern data workflows, machine learning pipelines, and any task that benefits from a lightweight DAG-based execution engine. Unlike heavier platforms like Airflow, Pyper aims to remain lean, modular, and developer-friendly, embracing Pythonic conventions and minimizing boilerplate. It focuses on local development ergonomics and seamless transition to production environments, making it ideal for small teams and...
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  • 16
    DataChain

    DataChain

    AI-data warehouse to enrich, transform and analyze unstructured data

    Datachain enables multimodal API calls and local AI inferences to run in parallel over many samples as chained operations. The resulting datasets can be saved, versioned, and sent directly to PyTorch and TensorFlow for training. Datachain can persist features of Python objects returned by AI models, and enables vectorized analytical operations over them. The typical use cases are data curation, LLM analytics and validation, image segmentation, pose detection, and GenAI alignment. Datachain...
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  • 17
    Liberapay

    Liberapay

    Source code of the recurrent donations platform Liberapay

    Liberapay is an open-source platform designed to facilitate recurring donations to creators, developers, and projects, with a strong emphasis on transparency, privacy, and sustainability. It operates as a nonprofit service that allows users to financially support individuals or teams on a weekly, monthly, or yearly basis without expecting rewards in return. The platform is particularly focused on funding open-source software, free knowledge, and creative work, helping contributors maintain...
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  • 18
    LinkdAPI Python

    LinkdAPI Python

    Powerful, lightweight B2B Data API for enriching professional profiles

    LinkdAPI Python is a software development kit designed to simplify integration with the LinkdAPI platform, enabling developers to connect applications with external services through a unified API layer. It provides structured tools, libraries, and documentation that streamline authentication, request handling, and data exchange between systems. The SDK is built to reduce the complexity of working with multiple APIs by offering standardized methods for interacting with different endpoints. It...
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  • 19
    ValueCell

    ValueCell

    Community-driven, multi-agent platform for financial applications

    ValueCell is a community-driven multi-agent AI platform focused on financial research, analysis, and decision-making that lets users leverage multiple specialized AI agents for tasks like data retrieval, investment research, strategy execution, and market tracking. The system brings together a suite of collaborative agents—such as research agents that gather and interpret fundamentals, strategy agents that implement trading logic, and news agents that deliver personalized updates—to help...
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  • 20
    Lithops

    Lithops

    A multi-cloud framework for big data analytics

    Lithops is an open-source serverless computing framework that enables transparent execution of Python functions across multiple cloud providers and on-prem infrastructure. It abstracts cloud providers like IBM Cloud, AWS, Azure, and Google Cloud into a unified interface and turns your Python functions into scalable, event-driven workloads. Lithops is ideal for data processing, ML inference, and embarrassingly parallel workloads, giving you the power of FaaS (Function-as-a-Service) without...
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  • 21
    atpbar

    atpbar

    Progress bars for threading and multiprocessing tasks on terminal

    Progress bars for threading and multiprocessing tasks on the terminal and Jupyter Notebook. atpbar can display multiple progress bars simultaneously growing to show the progresses of iterations of loops in threading or multiprocessing tasks. atpbar can display progress bars on the terminal and Jupyter Notebook. atpbar can be used with Mantichora. atpbar started its development in 2015 as part of Alphatwirl. atpbar prevented physicists from terminating their running analysis codes, which...
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  • 22
    ipychart

    ipychart

    The power of Chart.js with Python

    Create charts with Python in a very similar way to creating charts using Chart.js. The charts created are fully configurable, interactive, and modular and are displayed directly in the output of the cells of your jupyter notebook environment. Charts are fully interactive, you can hover it to display tooltips and select the information you want to see directly from the output cell of your notebook. All the types of charts present in Chart.js are exposed in ipychart. Even complex features such...
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  • 23
    Kale

    Kale

    Kubeflow’s superfood for Data Scientists

    KALE (Kubeflow Automated pipeLines Engine) is a project that aims at simplifying the Data Science experience of deploying Kubeflow Pipelines workflows. Kubeflow is a great platform for orchestrating complex workflows on top Kubernetes and Kubeflow Pipeline provides the mean to create reusable components that can be executed as part of workflows. The self-service nature of Kubeflow make it extremely appealing for Data Science use, at it provides an easy access to advanced distributed jobs...
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  • 24
    Apache Airflow Provider

    Apache Airflow Provider

    Great Expectations Airflow operator

    Due to apply_default decorator removal, this version of the provider requires Airflow 2.1.0+. If your Airflow version is 2.1.0, and you want to install this provider version, first upgrade Airflow to at least version 2.1.0. Otherwise, your Airflow package version will be upgraded automatically, and you will have to manually run airflow upgrade db to complete the migration. This operator currently works with the Great Expectations V3 Batch Request API only. If you would like to use the...
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  • 25
    ydata-profiling

    ydata-profiling

    Create HTML profiling reports from pandas DataFrame objects

    ydata-profiling primary goal is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution. Like pandas df.describe() function, that is so handy, ydata-profiling delivers an extended analysis of a DataFrame while allowing the data analysis to be exported in different formats such as html and json.
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