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@mgaitan
mgaitan / awesome-algorithmic-trading-with-python.md
Last active August 30, 2021 04:13
@anshoomehra
anshoomehra / parsing10k.ipynb
Last active November 25, 2025 00:38
How to Parse 10-K Report from EDGAR (SEC)
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@benjamincharity
benjamincharity / autonomous.txt
Last active February 5, 2026 02:46
Instructions on how to reset the autonomous desk. This fixes a problem where the desk will not lower (also reportedly fixes incorrectly reported heights).
> Thank you for reaching out to Autonomous! I am sorry to hear that you are having some trouble with your SmartDesk
> but I will be glad to assist. It sounds like your system needs a "hard reset" can I please have you follow these
> steps thoroughly.
Reset Steps:
1. Unplug the desk for 20 seconds. Plug it back in. Wait a full 20 seconds.
2. Press the up and down buttons until the desk lowers all the way and beeps or 20 seconds pass.
3. Release both buttons.
4. Press the down buttons until the desk beeps one more time or 20 seconds pass.
@biboudis
biboudis / schools.md
Last active October 20, 2024 08:11
PL Summer Schools forall in 2016!
@debasishg
debasishg / gist:8172796
Last active February 11, 2026 21:34
A collection of links for streaming algorithms and data structures

General Background and Overview

  1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
  2. Models and Issues in Data Stream Systems
  3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
  4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
  5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t
@allyourcode
allyourcode / lib.cc
Created August 29, 2013 00:03
pimpl C++ design pattern. main.cc has the definition of class K, but not that of K::Impl. test.cc has the definition of K::Impl (as well as that of K); thus, it has access to all of the internals without resorting to such hacks as friend. Besides testability, another benefit is that move semantics can be implemented very easily. In fact, I can't…
#include "lib.h"
#include <stdio.h>
class K::Impl {
public:
Impl(int i) : i_(i) {}
virtual ~Impl() {}