1.ozeranskii / httptap
Rich-powered CLI that breaks each HTTP request into DNS, connect, TLS, wait, and transfer phases with waterfall timelines, compact summaries, or metrics-only output.
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33 repositories by Attention Score · Aug 5, 2026 – Nov 2, 2026 (UTC)
Rich-powered CLI that breaks each HTTP request into DNS, connect, TLS, wait, and transfer phases with waterfall timelines, compact summaries, or metrics-only output.
The interactive graphing library for Python :sparkles:
PyGWalker: Turn your dataframe into an interactive UI for visual analysis
3D visualization and mesh analysis for science and engineering
Investigate malicious Windows logon by visualizing and analyzing Windows event log
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
napari: a fast, interactive, multi-dimensional image viewer for python
Vizro is a low-code toolkit for building high-quality data visualization apps.
Fast data visualization and GUI tools for scientific / engineering applications
git-cola: The highly caffeinated Git GUI
PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer
Main repository for Vispy
Python library that makes it easy for data scientists to create charts.
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
A Python package to visualise neuroanatomical data in atlas space
Automatically visualize your pandas dataframe via a single print! 📊 💡
Visual analysis and diagnostic tools to facilitate machine learning model selection.
A python module for scientific analysis of 3D data based on VTK and Numpy
Realtime Web Apps and Dashboards for Python and R
Entity Relation Diagrams generation tool
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
Visualize large time series data with plotly.py
Sequential model-based optimization with a `scipy.optimize` interface
An intuitive library to add plotting functionality to scikit-learn objects.
Python+Numpy+OpenGL: fast, scalable and beautiful scientific visualization
Main yt repository
Reconquer the canvas: beautiful Tikz figures without clunky Tikz code
MCP server for spatial transcriptomics analysis through natural language interfaces.
An awesome iTerm2 backend for Matplotlib, so you can plot directly in your terminal.
Visualization Package for NetworkX
Modern, interactive charts for Jupyter notebooks with Apache ECharts