Guilherme Marthe GuiMarthe

Linting your code, the vanilla way

You may want a linter plugin to lint your code in Vim but you probably don't need it. At least try the built-in way before jumping on the plugin bandwagon.

Defining `makeprg`

autocmd FileType <filetype> setlocal makeprg=<external command>

This autocommand tells Vim to use <external command> when invoking :make % in a <filetype> buffer. You can add as many similar lines as needed for other languages.

If You've Never Used Sklearn's Pipeline Constructor...You're Doing It Wrong

How To Use sklearn Pipelines, FeatureUnions, and GridSearchCV With Your Own Transformers

By Emily Gill and Amber Rivera

What's a Pipeline and Why Use One?

The Pipeline constructor from sklearn allows you to chain transformers and estimators together into a sequence that functions as one cohesive unit. For example, if your model involves feature selection, standardization, and then regression, those three steps, each as it's own class, could be encapsulated together via Pipeline.

Benefits: readability, reusability and easier experimentation.

Debug zsh startup time

Inject profiling code

At the beginning of your .zshrc add following: zmodload zsh/zprof

and at the end add: zprof

This will load zprof mod and display what your shell was doing durung your initialization.

https://twitter.com/snookca/status/1073299331262889984?s=21

‪“‬In what way is JS any more maintainable than CSS? How does writing CSS in JS make it any more maintainable?”

‪Happy to chat about this. There’s an obvious disclaimer that there’s a cost to css-in-js solutions, but that cost is paid specifically for the benefits it brings; as such it’s useful for some usecases, and not meant as a replacement for all workflows. ‬

‪(These conversations always get heated on twitter, so please believe that I’m here to converse, not to convince. In return, I promise to listen to you too and change my opinions; I’ve had mad respect for you for years and would consider your feedback a gift. Also, some of the stuff I’m writing might seem obvious to you; I’m not trying to tell you if all people of some of the details, but it might be useful to someone else who bumps into this who doesn’t have context)‬

So the big deal about css-in-js (cij) is selectors.

	_BUCKET_NAME="foo.example.com"

	_POLICY=$(cat <<EOT
	{
	"Version":"2012-10-17",
	"Statement":[{
	"Sid":"PublicReadForGetBucketObjects",
	"Effect":"Allow",
	"Principal": "*",
	"Action":["s3:GetObject"],

	library(sp)
	library(rgdal)
	library(rgeos)
	library(raster)
	library(ggplot2)

	# Lê um shapefile com UFs do Brasil - http://www.usp.br/nereus/?dados=brasil
	uf <- readOGR("../_temp/ufe.shp",encoding="UTF-8",stringsAsFactors = FALSE)
	uf_centroides <- gCentroid(uf,byid = TRUE)
	ufs = gSimplify(uf,tol=0.01)

	### JHW 2018
	import numpy as np
	import umap



	# This code from the excellent module at:
	# https://stackoverflow.com/questions/4643647/fast-prime-factorization-module

	import random

	library(tidyverse)
	library(RecordLinkage)
	df <- data.frame(name = c("Agent Peggy Carter", "Peggy Carter", "Outro Nome"),
	sum = 1:3) %>%
	mutate_if(is.factor, as.character)

	# Comparando sempre o nome anterior
	df %>%
	mutate(dist = levenshteinSim(name, lag(name, default = "")),
	final_name = ifelse(dist > 0.5, lag(name), name)) %>%

	import pandas as pd
	import datetime
	from datetime import datetime as dt
	from dateutil.relativedelta import *

	class TimeBasedCV(object):
	'''
	Parameters
	----------
	train_period: int