hrbrmstr

#!/usr/bin/awk -f

# This program is a copy of guff, a plot device. https://github.com/silentbicycle/guff
# My copy here is written in awk instead of C, has no compelling benefit.
# Public domain. @thingskatedid

# Run as awk -v x=xyz ... or env variables for stuff?
# Assumptions: the data is evenly spaced along the x-axis

# TODO: moving average

hrbrmstr

#!/bin/bash

gdb -p "$1" -batch -ex 'set {short}$rip = 0x050f' -ex 'set $rax=231' -ex 'set $rdi=0' -ex 'cont'

hrbrmstr

hrbrmstr

1. choose a simple linux image

For example alpine, it's only about 5MB.

2. set timezone if necessary

RUN apk add --no-cache tzdata
ENV TZ America/New_York

hrbrmstr

// XPath CheatSheet
// To test XPath in your Chrome Debugger: $x('/html/body')
// http://www.jittuu.com/2012/2/14/Testing-XPath-In-Chrome/


// 0. XPath Examples.
// More: http://xpath.alephzarro.com/content/cheatsheet.html


'//hr[@class="edge" and position()=1]'                // every first hr of 'edge' class

hrbrmstr

get_page <- function(page_num = 1) {

  # this is to be kind to the web site
  # it does not have a robots.txt so this should be the default wait 
  # time between requests since the desires of the scraper are not
  # greater than that of the site owner and you'd be abusing
  # their resources if you did not put a delay in between requests
  Sys.sleep(5) 
    

hrbrmstr

;
WITH CTE AS 
(
  SELECT
    *,
    ROW_NUMBER() OVER (PARTITION BY [product_id], shop_code 
  ORDER BY
    [doc_date]) - ROW_NUMBER() OVER (PARTITION BY [product_id], shop_code, mark_1 

hrbrmstr

library(rvest)
library(dplyr)

pg <- read_html("https://bidplus.gem.gov.in/bidresultlists")

blocks <- html_nodes(pg, ".block")

items_and_quantity <- html_nodes(blocks, xpath=".//div[@class='col-block' and contains(., 'Item(s)')]")

items <- html_nodes(items_and_quantity, xpath=".//strong[contains(., 'Item(s)')]/following-sibling::span") %>% html_text(trim=TRUE)

hrbrmstr

Since cognitive processes are challenging for Python programmers, this is pretty much what the (not great idiom in) the appropriately-acronym'd BS 4 text => get_text() does (https://github.com/wention/BeautifulSoup4/blob/03a2b3a9d1fc5877212d9d382a512663f24c887d/bs4/element.py#L846-L854). There are FAR BETTER WAYS to get text than this, but I would not expect Python things to grok that.

hrbrmstr

library(httr)
library(rvest)
library(readxl)
library(tidyverse)

doe <- read_html("https://www.oe.netl.doe.gov/OE417_annual_summary.aspx")

dir.create("~/Data/doe-cache-dir", showWarnings = FALSE)

html_nodes(doe, xpath=".//a[contains(., 'XLS')]") %>%