datoviz
lisa
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datoviz | lisa | |
---|---|---|
4 | 6 | |
492 | 198 | |
1.2% | 1.0% | |
4.6 | 9.7 | |
9 months ago | 8 days ago | |
C | Jupyter Notebook | |
MIT License | Apache License 2.0 |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
datoviz
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Looking for a library for plotting a big amount of geometrical data
Maybe Datoviz or Dear PyGui?
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What tools are missing in Python?
Datoviz looks promising in this regard.
lisa
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Parca Agent rewrites eBPF in-kernel C code in Rust (using Aya-rs)
This is to replace the current flow purely based on pandas dataframe and offline trace.dat parsing used in LISA: https://github.com/ARM-software/lisa (collecting a trace.dat is nice for debugging but limits to small durations, and pandas does not allow running computations in constant memory, which is an issue for very big traces)
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Languages with integrated dependency injection
The module added by this PR seems to be a pretty good fit: https://github.com/ARM-software/lisa/pull/1722
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What tools are missing in Python?
I made that thing taking some vague inspiration from SML module system: https://github.com/ARM-software/lisa/pull/1722/files
Regarding dependency injection you can have a look at that (I've not merged it yet but I consider it basically final): https://github.com/ARM-software/lisa/pull/1722/files
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The pipe-operator to python |>
import builtins from operator import add import functools # These functions can be found at: # https://github.com/ARM-software/lisa/blob/master/lisa/utils.py#L147 # Note: my implementation of curry() seems to be broken wrt named parameters (or for parameters with defaults, haven't looked at the details) for some reason but for this example it does not matter from lisa.utils import compose, curry def even(x): return x % 2 == 0 # The builtin functions don't have a signature, which will upset curry() so we # redefine it here def map(f, iterable): return builtins.map(f, iterable) def filter(f, iterable): return builtins.filter(f, iterable) # Swapped init and iterable to be curry-friendly def reduce(f, init, iterable): return functools.reduce(f, iterable, init) def pipeline(*items): # Add a currying layer so that we spare the user the need to do it return compose(*(curry(f)(*args) for (f, *args) in items)) # x = filter(even, list) |> map(lambda x: x+1) |> reduce(+) f = pipeline( (filter, even), (map, lambda x: x+1), (reduce, add, 0), ) l = [1,2,3,4] x = f(l) print(x)
What are some alternatives?
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
rife-ncnn-vulkan - RIFE, Real-Time Intermediate Flow Estimation for Video Frame Interpolation implemented with ncnn library
kompute - General purpose GPU compute framework built on Vulkan to support 1000s of cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases. Backed by the Linux Foundation.
gatling - Hydra-enabled GPU path tracer that supports MaterialX and MDL
PortableGL - An implementation of OpenGL 3.x-ish in clean C
DearPyGui - Dear PyGui: A fast and powerful Graphical User Interface Toolkit for Python with minimal dependencies
PyInstaller - Freeze (package) Python programs into stand-alone executables
parca-agent - eBPF based always-on profiler auto-discovering targets in Kubernetes and systemd, zero code changes or restarts needed!
blazon - A python library for assuring data structure and format via schemas like JSON Schema
turbo-django - Unmaintained // An early stage integration of Hotwire Turbo with Django
awesome-functional-python - A curated list of awesome things related to functional programming in Python.