This article looks at algorithms to determine where you live based on time zones, email domains, popular names and symbols, and contact IT companies.
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We talk about the real experience of working with the analysis of commit statistics in Git, useful for developers and technical managers. We explain how to use basic console tool commands to display commit activity data, create graphs, and interpret results to evaluate team performance.
In a bureaucratic organization with weak processes and high staff turnover, a new developer was hired whose activities seemed opaque. At first, colleagues perceived him as a competent specialist, but after a few months, suspicions arose about the lack of results of his work. After analyzing the commits, it became clear that activity was almost non-existent, and the employee was simultaneously working at another job and teaching. He was offered a transfer to another department, leaving management without responsibility for the situation.
Moving on to the issue of tools, there is a need for something that goes beyond simple console reports and provides a graphical representation that is convenient for analysis:
A tool for analyzing activity in Git repositories. Generates visualizations and statistics (commit graphs, active hours and days). Suitable for developers who want to track their performance.
A command-line utility for creating column charts with commit distribution by day of the week and hour. A simple and convenient way to display data about commit habits.
A script for quickly retrieving statistics from Git. Shows information about the most active authors, commit frequency, change volumes, and other data. Useful for quick repository analysis.
A macOS app that provides statistics and analysis of Git activity. Offers easy-to-understand graphs and reports to track performance across repositories.
A Linux tool that generates detailed reports on Git activity. Allows you to get statistics on commits, authors, changes, and other parameters.
A Windows utility that analyzes Git repositories and creates graphical reports. It allows you to track user contributions, the distribution of changes over time.
Installing dependencies and packages for various programming languages, especially Python and Ruby, can be a daunting task. Some reports of problems installing complex dependencies are quite helpful, but more often than not, the process is exhausting, especially when you need to install compilers and package managers for languages you don’t use on a daily basis.
A Python utility for generating detailed statistical reports from Git repositories. Analyzes commit, author, and contribution activity over time.
A Python tool that analyzes Git repositories and provides detailed statistics on developer contributions, code changes, and commit history.
A Docker container that provides a convenient interface for collecting and visualizing analytics from Git repositories. Convenient for integration into CI/CD processes.
An analytical tool that allows you to work with Git via SQL queries. Suitable for creating custom reports and complex analysis.
A Python tool for extracting statistics from Git repositories. Allows you to analyze developer contributions, uptime, and other data.
A Ruby utility for visualizing Git repository statistics, including commit graphs, activity by day, and author contributions.
A Python library for creating Git analytics with a focus on change distribution and team performance.
A Python tool for analyzing Git history, specializing in visualizing the evolution of a project.
Create visualizations and activity graphs in Git repositories using artificial intelligence. Allows you to quickly analyze data and generate understandable reports.
A Visual Studio extension that provides basic Git statistics right in your development environment. Shows commit activity, author contributions, and other key data.
A tool for analyzing the productivity of engineering teams. Tracks project progress, identifies blockages, and helps evaluate developer performance.
A platform for analyzing commits in Git. Allows you to evaluate the true productivity of developers by analyzing the volume of changes and contributions to the code.
A platform for improving development processes. Tracks team performance, automates workflows, and provides data for decision-making.
A tool for measuring the performance of engineering teams based on data from Git. Helps identify points for optimizing processes and increasing efficiency.
A tool for measuring engineering performance. Offers reports that help developers and managers optimize team performance and identify problems.
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