
ConstellationDev
CodeMap4AI
Sourcegraph
Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
AI coding agents waste most of their context window grepping files and guessing at code structure. Constellation gives them a persistent, team-wide knowledge graph of your codebase (symbol search, dependency graphs, impact analysis) delivered via MCP so every token goes toward reasoning, not discovery.
ConstellationDev
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In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
Numbers are useful, but sometimes itโs easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 8 months ago
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
CodeMap4AI - AI tools guess less when they see the full picture. CodeMap4AI builds a structured map of your codebase. Try it free.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Sourcegraph - Sourcegraph is a free, self-hosted code search and intelligence server that helps developers find, review, understand, and debug code. Use it with any Git code host for teams from 1 to 10,000+.
NumPy - NumPy is the fundamental package for scientific computing with Python