PyPy
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bbfreeze
Numba
PyInstaller
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PyOxidizer
asciinema
Plotly
D3.js
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PlotlyPlotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.
Based on our record, Plotly should be more popular than PyPy. It has been mentiond 34 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
There are quite a few JITs: JIT-compiler for Python https://pypy.org/ Python enhancement proposal for JIT in CPython https://peps.python.org/pep-0744/ And there are several JIT-compilers for various subsets of Python, usually with focus on numerical code and often with GPU support, for example Numba https://numba.pydata.org/numba-doc/dev/user/jit.html Taichi Lang https://github.com/taichi-dev/taichi. - Source: Hacker News / 6 months ago
Gains than using either compiler alone. This uses the PyPy JIT framework to speed up a RISC-V simulator. https://pypy.org/ https://github.com/pydrofoil/pydrofoil Pydrofoil: A fast RISC-V emulator generated from the Sail model, using PyPy's JIT. - Source: Hacker News / over 1 year ago
"On average, PyPy is 4.4 times faster than CPython 3.7." https://pypy.org/. - Source: Hacker News / over 1 year ago
If you're going the pure Python route, don't forget to try PyPy[1], an alternative JITed implementation of the language. A seriously underrated project, IMHO. Most time it speeds up execution by a factor of 2x-4x, but improvements of about two orders of magnitude are not unheard of. See for example [2]. Numeric, long-running code shoud suit PyPy optimizations well. [1] https://pypy.org/ [2]... - Source: Hacker News / over 1 year ago
Python: My Python-foo is limited, so I only ported the last problem (a simple while loop) and ran it with PyPy. It takes a bit less of time:. - Source: dev.to / about 2 years ago
Let's dive into some practical examples. First, you'll need to set up your environment with the right tools. I recommend using pandas for data manipulation and plotly for visualization. - Source: dev.to / 4 months ago
Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / over 1 year ago
Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / over 1 year ago
In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / over 1 year ago
How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / about 2 years ago
cx_Freeze - cx_Freeze is a set of scripts and modules for freezing Python scripts into executables in much the...
D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.
bbfreeze - create stand-alone executables from python scripts
RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...
Numba - Numba gives you the power to speed up your applications with high performance functions written...
Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.