fogus

(import 'clojure.lang.ExceptionInfo)

(defn call-cc [f]
  (let [v (promise)
        e (ex-info "cc" {:v v})]
    (try (f #(do (deliver v %) (throw e)))
         (catch ExceptionInfo ex
           (if (identical? ex e)
             @(:v (ex-data ex))
             (throw ex))))))

fogus

;; Datomic example code
(use '[datomic.api :only (db q) :as d])

;; ?answer binds a scalar
(q '[:find ?answer :in ?answer]
   42)

;; of course you can bind more than one of anything
(q '[:find ?last ?first :in ?last ?first]
   "Doe" "John")

fogus

Links for essays ref'd in http://blog.fogus.me/2009/03/11/seven-books/

• On the Criteria to Be Used in Decomposing Systems Into Modules – David Parnas
• A Note On Distributed Computing – Jim Waldo, Geoff Wyant, Ann Wollrath, Sam Kendall
• The Next 700 Programming Languages – P. J. Landin
• Can Programming Be Liberated from the von Neumann Style? – John Backus
• Reflections on Trusting Trust – Ken Thompson
• Lisp: Good News, Bad News, How to Win Big – Richard Gabriel
• An Experimental Evaluation of the Assumption of Independence in Multiversion Programming – John Knight and Nancy Leveson
• [Arguments and Results –

fogus

(ns schema->gen
  "Functions for generating test data from schemas."
  (:require [four.stateful :as four]
            [re-rand :refer [re-rand]]
            [schema.core :as sch]
            [simple-check.generators :as gen]))

(defn ^:private re-randify-regex
  "schema requires ^$ while re-rand forbids them"
  [re]

fogus

(ns tumblrsearch.core
  (:require-macros [cljs.core.async.macros :refer [go]])
  (:require [clojure.browser.repl]
            [cljs.core.async :as async :refer  [put! chan <!]]
            [om.core :as om :include-macros true]
            [om.dom :as dom :include-macros true]
            [figwheel.client :as fw :include-macros true]
            )
  (:import [goog.net Jsonp]
           [goog Uri]

fogus

import re

def markdown_to_bbcode(s):
    links = {}
    codes = []
    def gather_link(m):
        links[m.group(1)]=m.group(2); return ""
    def replace_link(m):
        return "[url=%s]%s[/url]" % (links[m.group(2) or m.group(1)], m.group(1))
    def gather_code(m):

fogus

;; Still haven't found a brief + approachable overview of Clojure 1.7's new Transducers
;; in the particular way I would have preferred myself - so here goes:

;;; Transducers recap
;; * (fn reducer-fn [] [accumulation] [accumulation next-input]) -> val [1].
;; * (fn transducer-fn [reducer-fn]) -> new-reducer-fn.
;; * So a transducer-fn is a reducer-fn middleware[2], and composes like it.
;; * All (numerous!) benefits[4] fall out of this simple +
;;   not-particularly-impressive-looking[3] definition.
;;

fogus

(comment ; Fun with transducers, v2

  ;; Still haven't found a brief + approachable overview of Clojure 1.7's new
  ;; transducers in the particular way I would have preferred myself - so here goes:

  ;;;; Definitions
  ;; Looking at the `reduce` docstring, we can define a 'reducing-fn' as[1]:
  (fn reducing-fn ([]) ([accumulation next-input])) -> new-accumulation

  ;; We choose to define a 'transducing-fn' as:

fogus

; there are some obvious micro optimizations, I left them out for clarity
; the relative ordering of read and writes with volatile and plain array should be thread-safe (if not, point it out)

; @wagjo asked "Have you found use for such concept? Must be pretty slow compared to unchunked one"
; The idea came out of a discussion on transducers so not used for real, yet.
; Once you optimize it (remove the boxing induced by the volatile, switch to unchecked math) there should not be much
; of an overhead.
; When you have one big composed reducing fn (eg several mapping stages) then each item is going to be processed in 
; each stage, each stage of the mapping may evict from the data cache stuff used by previous stages. So you have cache
; misses for each item.

fogus

Found way fewer than I expected with bibliographies. But also way fewer 2009-present books. The select few w/ nice beefy bibliographies:

• The Joy of Clojure (Fogus/Houser)
• The Linux Programming Interface (Kerrisk)
• Systems Performance (Gregg)
• The Art of Multiprocessor Programming (Herlihy/Shavit)
• Machine Learning (Flach)

I counted 8/18 tech books on my shelf since 2009 with bibliographies - way fewer than I'd have guessed. This is even w/ some selection bias towards the type of book that would have a bibliography, I suspect.