GitHub - anishathalye/git-remote-dropbox: A transparent bridge between Git and Dropbox - use a Dropbox (shared) folder as a Git remote! 🎁You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session. You switched accounts on another tab or window. Reload to refresh your session. Dismiss alert
Introduction to the Modeling and Analysis of Complex Systems - Milne Open Textbooks
Keep up to date on Introduction to Modeling and Analysis of Complex Systems at http://bingweb.binghamton.edu/~sayama/textbook/! Introduction to the Modeling and Analysis of Complex Systems introduces students to mathematical/computational modeling and analysis developed in the emerging interdisciplinary field of Complex Systems Science. Complex systems are systems made of a large number of microsc
System F をHaskellとPythonで実装した - -
無事夏休みに突入して時間ができたので再びTaPLを読み始めました．半年触っていなくても進行，保存の証明が書けるあたり，春の自分はずいぶんしっかりと勉強していたようです．春は22章の型再構築まで読んでいたので，ひとまず23章のSystem Fから読んでサクッと実装しました．Pythonが書きたかったので，パーサーだけHaskellで書いてそれ以外をPythonで書くというよく分からない構成で実装していますが，いろいろと学びがあったのでそれを記していきます． System Fとは 変数，抽象，適用からなる単純型付きラムダ計算に型抽象と型適用を加えて拡張した計算体型のことを指します．パラメータ化した型による計算ができることから多相ラムダ計算とも呼ばれます．この体型のみでは基本型が存在せず型の具体化が十分にできないので，Bool型の構文を追加してそれらしい操作ができるようにしています．単純型付きラ
Python metaclasses · Ivan Smirnov
A brief excurse into Python metaclasses outlining the common use cases, notable differences in Python 2.x/3.x syntax and providing a few examples. Same way as classes control instance creation and let us define instance behaviour in the form of instance methods and magic methods, metaclasses in Python can do all that and a little more for class objects. The simplest way to deal with metaclasses is
Raymond Hettinger - Beyond PEP 8 -- Best practices for beautiful intelligible code - PyCon 2015
"Speaker: Raymond Hettinger Distillation of knowledge gained from a decade of Python consulting, Python training, code reviews, and serving as a core developer. Learn to avoid some of the hazards of the PEP 8 style guide and learn what really matters for creating beautiful intelligible code. Slides can be found at: https://speakerdeck.com/pycon2015 and https://github.com/PyCon/2015-slides"
Working with maps in Python
Kristoffer over at rpsychologist.com wrote a really nice tutorial on getting up to speed with maps in R. It looked something like this. Felt a little left out, so I decided to make a port in Python. You can follow along below or if you prefer this as an Jupyter Notebook that you can download and run on our local machine. To start with you need the packages numpy and matplotlib basemap. The latter
Gradient Descent with Backpropagation – Δ ℚuantitative √ourney – ∑ My experiences in learning quantitative applications
A beginner tutorial to understand the theoretical and implementation details of gradient descent by backpropagation using Python.Assumptions/Recommendations: I assume you know matrix/vector math, introductory calculus (differentiation, basic understanding of partial derivatives), how basic feedforward neural nets work and know how to compute the output of a 2-layer neural net, and basic python/num
Dataflow Engine
overview A CAD program like Antimony has to keep track of many small pieces of data. For example, a 2D point has x and y coordinates: One of the major design decisions in Antimony is that every datum is a piece of code. This means we can put arbitrary expressions into the point's coordinates. Object properties are also free to refer to each other, with the graph acting as a local namespace. Given
How to Create NBA Shot Charts in Python
%matplotlib inline import requests import matplotlib.pyplot as plt import pandas as pd import seaborn as sns Getting the data¶Getting the data from stats.nba.com is pretty straightforward. While there isn't a a public API provided by the NBA, we can actually access the API that the NBA uses for stats.nba.com using the requests library. This blog post by Greg Reda does a great job on explaining how
GitHub - billpmurphy/hask: Haskell language features and standard libraries in pure Python.
Hask is a pure-Python, zero-dependencies library that mimics most of the core language tools from Haskell, including: Full Hindley-Milner type system (with typeclasses) that will typecheck any function decorated with a Hask type signature Easy creation of new algebraic data types and new typeclasses, with Haskell-like syntax Pattern matching with case expressions Automagical function currying/part
Profiling in Python
Here at HumanGeo we use a lot of Python, and it is tons of fun. Python is a great language for writing beautiful and functional code amazingly fast, and it is most definitely my favorite language to use both privately and professionally. However, even though it is a wonderful language, Python can be painfully slow. Luckily, there are some amazing tools to help profile your code so that you can kee
Ibis: Python Data Analysis Productivity Framework
An open source dataframe library that works with any data system Use the same API for nearly 20 backends Fast local dataframes with embedded DuckDB (default), Polars, or DataFusion Iterate locally and deploy remotely by changing a single line of code Compose SQL and Python dataframe code, bridging the gap between data engineering and data science Ibis: the portable Python dataframe library Ibis of
Black Hat Python: Building a UDP Scanner
When it comes to the reconnaissance of some target network, the start point is undoubtedly on host discovering. This task might come together with the ability to sniff and parse the packets flying through the network. A few weeks ago, I talked about how to use Wireshark for packet sniffing, but what if you don't have Wireshark available to monitor a network traffic? Again, Python comes with severa
solving multi-core Python
tl;dr Let's exploit multiple cores by fixing up subinterpreters, exposing them in Python, and adding a mechanism to safely share objects between them. This proposal is meant to be a shot over the bow, so to speak. I plan on putting together a more complete PEP some time in the future, with content that is more refined along with references to the appropriate online resources. Feedback appreciated!
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Creating a Pluto flyby using unaligned New Horizons images - Matt's Ramblings
Isaac Slavitt: Speeding up non-vectorizable code with Cython
Bokken - Home Page
GitHub - inconvergent/differential-line: a generative algorithm
GitHub - jkbrzt/cointrol: ฿ Bitcoin trading bot with a real-time dashboard for Bitstamp.
GitHub - ryankiros/skip-thoughts: Sent2Vec encoder and training code from the paper "Skip-Thought Vectors"
