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@maciejgryka
maciejgryka / PythonWorker.Dockerfile
Last active March 2, 2021 14:10
A sample Dockerfile for shipping modern Python workers
FROM ubuntu:latest
ENV DEBIAN_FRONTEND=noninteractive
ENV LC_ALL C.UTF-8
ENV LANG C.UTF-8
# install system dependencies
RUN apt-get update && apt-get install -y \
curl \
build-essential \
@stakira
stakira / gfm_table.css
Last active April 6, 2019 02:56
GFM table
body {
text-size-adjust: 100%;
color: #333;
font-family: "Helvetica Neue", Helvetica, "Segoe UI", Arial, sans-serif;
font-size: 16px;
line-height: 1.6;
word-wrap: break-word;
}
@ShivrajRath
ShivrajRath / Basic HTM5 Boilerplate
Last active December 2, 2020 10:05
Basic HTML5 Boilerplate
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="">
<meta name="author" content="">
<link rel="shortcut icon" href="favicon.png">
@dan-blanchard
dan-blanchard / .1.miniconda.md
Last active December 11, 2019 22:38
Quicker Travis builds that rely on numpy and scipy using Miniconda

For ETS's SKLL project, we found out the hard way that Travis-CI's support for numpy and scipy is pretty abysmal. There are pre-installed versions of numpy for some versions of Python, but those are seriously out of date, and scipy is not there are at all. The two most popular approaches for working around this are to (1) build everything from scratch, or (2) use apt-get to install more recent (but still out of date) versions of numpy and scipy. Both of these approaches lead to longer build times, and with the second approach, you still don't have the most recent versions of anything. To circumvent these issues, we've switched to using Miniconda (Anaconda's lightweight cousin) to install everything.

A template for installing a simple Python package that relies on numpy and scipy using Miniconda is provided below. Since it's a common s

@agramfort
agramfort / lowess.py
Last active August 16, 2023 06:19
LOWESS : Locally weighted regression
"""
This module implements the Lowess function for nonparametric regression.
Functions:
lowess Fit a smooth nonparametric regression curve to a scatterplot.
For more information, see
William S. Cleveland: "Robust locally weighted regression and smoothing
scatterplots", Journal of the American Statistical Association, December 1979,