Search Results for "summary"
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Showing 388 open source projects for "summary"
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Profile Summary
Tool for visualizing GitHub profiles
Profile Summary for GitHub is a web application for turning a public GitHub account into a more visual overview of its development activity. It uses the GitHub API to collect profile and repository information and present it as summary graphics and statistics. Its visualizations include repository distribution by programming language and commit distribution by language. -
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Git Extras
GIT utilities, repo summary, repl, changelog population, and more
GIT extra utilities, like repo summary, repl, changelog population, author commit percentages and more. Supports several sub-commands such as git-ignore, git-setup, git-summary, git-changelog, git-effort, etc. Some commands require extra dependencies which are unavailable in some platforms. You may need to install them manually. Note that only the Homebrew package is maintained by the git-extras developers directly. -
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ggstatsplot
Enhancing {ggplot2} plots with statistical analysis
...The central idea of {ggstatsplot} is simple: combine these two phases into one in the form of graphics with statistical details, which makes data exploration simpler and faster. Summary of statistical tests and effect sizes. -
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gtsummary
Presentation-Ready Data Summary and Analytic Result Tables
gtsummary is an R package for creating elegant, customizable, publication-ready summary tables of datasets and statistical models. It provides concise code to produce demographic tables (tbl_summary()), regression result tables, and more, with flexible styling options for reporting. -
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5
BTC RPC Explorer
Database-free, self-hosted Bitcoin explorer, via RPC to Bitcoin Core
...With this explorer, you can explore not just the blockchain database, but also explore all of the functional capabilities of your own node. Optional transaction history for addresses by querying from Electrum-protocol servers (e.g. Electrs, ElectrumX), blockchain, blockchair or blockcypher. Mempool summary, with fee, size, and age breakdowns. See raw JSON content from bitcoind used to generate most pages. Analysis tools for viewing stats on blocks, transactions, and miner activity. -
6
hey
HTTP load generator, ApacheBench (ab) replacement
...It’s simple, efficient, performant, powerful, and was designed as a more modern alternative to Apache’s AB. Why ever look elsewhere one may ask? Well the answer for me is that the summary output, whilst very cool, is a little too simplistic for my use-case. -
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gotestsum
'go test' runner with output optimized for humans, JUnit XML for CI
gotestsum runs tests using go test -json, prints formatted test output, and a summary of the test run. It is designed to work well for both local developments, and for automation like CI. When the --rerun-fails flag is set, gotestsum will re-run any failed tests. The tests will be re-run until each passes once, or the number of attempts exceeds the maximum attempts. Maximum attempts defaults to 2, and can be changed with --rerun-fails=n. gotestsum supports executing a compiled test binary (created with go test -c) by running it as a custom command. pkgname is the name of the package being tested, it will show up in the test output. .... -
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mysqlclient
MySQL/MariaDB connector for Python
Summary: mysqlclient is a MySQL/MariaDB connector for Python, providing a convenient interface for database interactions. -
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BenchmarkDotNet
Powerful .NET library for benchmarking
BenchmarkDotNet is a powerful .NET library designed for creating accurate and reproducible benchmarks. It handles complexities like warm-up, outlier removal, and statistical analysis, presenting results in a clean, customizable summary format. BenchmarkDotNet has tons of features that are essential in comprehensive performance investigations. Four aspects define the design of these features: simplicity, automation, reliability, and friendliness. A lot of hand-written benchmarks produce wrong numbers that lead to incorrect business decisions. BenchmarkDotNet protects you from most of the benchmarking pitfalls and allows you to achieve high measurement precision. -
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AIQuant
AI-powered platform for quantitative trading
...Stock trading strategies: large models, factor mining, traditional strategies, machine learning, deep learning, reinforcement learning, graph networks, high-frequency trading, etc. Resource summary: network-wide resource summary, practical cases, paper interpretation, and code implementation. -
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CausalImpact
An R package for causal inference in time series
...It uses Bayesian modeling to fit a structural time series to the pre-period and extrapolate a counterfactual prediction for the post period, then compares observed vs predicted to infer the causal effect. The package supports plotting, summary tables, and verbal narratives for interpretive reports. -
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whylogs
The open standard for data logging
...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 simple mean, median, and standard deviation measures), the number of missing values, and a wide range of configurable custom metrics. By capturing these summary statistics, we are able to accurately represent the data and enable all of the use cases described in the introduction. -
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see
Visualisation toolbox for beautiful and publication-ready figures
see is an R package that serves as the visualization component of the easystats ecosystem, providing plotting utilities to produce publication-ready visualizations of statistical model parameters, diagnostics, predictions, and performance metrics. It works in conjunction with other easystats packages (such as parameters, performance, modelbased, bayestestR, etc.) to convert model outputs or summary objects into visual forms (dot-and-whisker plots, diagnostic plots, residual plots, etc.). It includes themes, scales, geoms for ggplot2, and custom color palettes to make visual summaries more informative and attractive. -
14
Coverage.jl
Take Julia code coverage and memory allocation results, do useful thin
Julia can track how many times, if any, each line of your code is run. This is useful for measuring how much of your code base your tests actually test, and can reveal the parts of your code that are not tested and might be hiding a bug. You can use Coverage.jl to summarize the results of this tracking or to send them to a service like Coveralls.io or Codecov.io. Julia can track how much memory is allocated by each line of your code. This can reveal problems like type instability, or... -
15
Stack Wallet
Stack Wallet, a multicoin, cryptocurrency wallet
...Designed for both desktop and mobile environments, it aims to provide a unified experience for crypto users who prefer open-source transparency. The project focuses on security-conscious workflows and user autonomy rather than custodial convenience. In summary, Stack Wallet is positioned as a privacy-respecting, multi-asset wallet for users who want direct ownership and management of their crypto holdings. -
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Jekyll SEO Tag
Plugin to add metadata tags for search engines and social networks
A Jekyll plugin to add metadata tags for search engines and social networks to better index and display your site's content. While you could theoretically add the necessary metadata tags yourself, Jekyll SEO Tag provides a battle-tested template of crowdsourced best practices. Jekyll SEO tag is designed to output machine-readable metadata for search engines and social networks to index and display. If you're looking for something to analyze your Jekyll site's structure and content (e.g.,... -
17
broom
Convert statistical analysis objects from R into tidy format
broom is part of the tidymodels ecosystem that converts statistical model outputs (e.g. from lm, glm, t.test, lme4, etc.) into tidy tibbles — standardized data frames — using functions tidy(), glance(), and augment(). These are easier to manipulate, visualize, and report programmatically. -
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Elyra
Elyra extends JupyterLab with an AI centric approach
Elyra is a set of AI-centric extensions to JupyterLab Notebooks. The Elyra Getting Started Guide includes more details on these features. A version-specific summary of new features is located on the releases page. -
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Traccar
Traccar GPS Tracking System
The Traccar software offers exceptional performance and stability, whether it is installed on Windows, Linux, or any other platform. The server can be hosted on-premise or in the cloud, and we provide various hosted options with professional support. Traccar stands out among GPS tracking systems on the market by supporting a vast array of protocols and device models. Whether you prefer low-cost, no-name GPS trackers or high-end, quality brands, Traccar enables you to choose from a wide... -
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GoldenCheetah
Performance Software for Cyclists, Runners, Triathletes and Coaches
Analyze using summary metrics like BikeStress, TRIMP, or RPE. Extract insight via models like Critical Power and W'bal. Track and predict performance using models like Banister and PMC. Optimize aerodynamics using Virtual Elevation. Train indoors with ANT and BTLE trainers. Upload and Download with many cloud services including Strava, Withings, and Today's Plan. -
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performance
Models' quality and performance metrics (R2, ICC, LOO, AIC, BF, ...)
performance is part of the easystats ecosystem and offers model quality assessment tools for R. It computes metrics like R², RMSE, ICC, and conducts diagnostics such as overdispersion, zero‑inflation, convergence, and singularity checks, complementing model workflows with comprehensive evaluation. -
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Presubmit
Context-aware AI reviewer for Pull Requests
Optimize your code review process with Presubmit's AI Code Reviewer catches bugs, suggests improvements, and provides a meaningful summary - all before human reviewers take their first look. -
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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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Miniflux 2
Minimalist and opinionated feed reader
Miniflux is a minimalist and opinionated feed reader. The page layout, fonts, and colors are chosen to be readable on a screen. The most important thing is the content. Do you have feeds that display only a summary? Fetch the original article automatically. I suppose you don't like bloated software? Miniflux focuses on simplicity. Less is more! Be productive, use the keyboard shortcuts to navigate through the application. Scan quickly your unread items with the lightweight user interface. Miniflux is compiled statically without external dependencies, drop the binary on your server and you are done. ... -
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AgentOps
Python SDK for agent monitoring, LLM cost tracking, benchmarking, etc.
Industry-leading developer platform to test and debug AI agents. We built the tools so you don't have to. Visually track events such as LLM calls, tools, and multi-agent interactions. Rewind and replay agent runs with point-in-time precision. Keep a full data trail of logs, errors, and prompt injection attacks from prototype to production. Native integrations with the top agent frameworks.