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(comment
"just testin")(def db
{:name ::db
:compile (fn [router-data router-opts]
(fn [handler]
(fn [request]
(handler (assoc request :db (:db router-data))))))})zsawd(def foo :foo);; clojure -Sdeps '{:deps {dawran6/emoji {:mvn/version "0.1.4"}}}'
(require '[emoji.core :as e])
(e/emojify "Clojure is awesome :thumbsup:")
;; => "Clojure is awesome 👍"
(e/demojify "Clojure is awesome 👍")
;; => "Clojure is awesome :thumbsup:"
;; Emojify everything
(e/emojify-all "pen pineapple apple pen")
;; => "pen 🍍 🍎 pen"with open('Data/File.csv', 'r') as fi:
r = fi.readlines()# github/tallguyjenks
library(readxl)
library(tidyverse)
library(chron)
library(rmarkdown)
library(knitr)
ggplot(data = df) +
geom_bar(filter(df, Year == params$curYear,
SentToHQQM == "Y",
Inst != "R1"),
mapping = aes(x = Inst, fill = Inst)) +
xlab('2019 Emails By Inst') +
ylab('Count') +
facet_wrap(~ Month, ncol = 4) +
coord_flip() +
scale_x_discrete(limits = rev(levels(df$Inst))) +
ggtitle('2019 Received Emails to HQ by Inst Faceted by Month') +
theme(plot.title = element_text(hjust = 0.5))'~~ Comments ~~'
'~~~~~~~~~~~~~~'
' github/tallguyjenks '
'~~~~~~~~~~~~~~'
sub helloWorld
dim message as string
message = "Hello World!"
msgbox(message)
end subsub helloWorld
dim message as string
msgbox(message)
end subconsole.log("this is a great site");;; clojure -Sdeps '{:deps {dawran6/emoji {:mvn/version "0.1.2"}}}'
(require '[emoji.core :as e])
(e/->emoji "smile")
;; => "😄"installed = set()
processing = set()
def install(x):
if x in installed:return
if x in processing: raise Exception("cyclic dependency")
processing.add(x)
dependencies = get_dependencies(x)
for d in dependencies:
install(d)
installed.add(x)
processing.remove(x)
print(x)
def get_dependencies(x):
return pkgs.get(x, [])
if __name__ == '__main__':
# question. note the order is arbitrary
pkgs = dict()
pkgs[4]= [5]
pkgs[2]= [4,5]
pkgs[1]= [2,3,4,5]
for p in pkgs.keys():
install(p)installed = set()
processing = set()
def install(x):
if x in installed:return
if x in processing: raise Exception("cyclic dependency")
processing.add(x)
dependencies = get_dependencies(x)
for d in dependencies:
install(d)
installed.add(x)
processing.remove(x)
print(x)
def get_dependencies(x):
return pkgs.get(x, [])
if __name__ == '__main__':
# question. note the order is arbitrary
pkgs = dict()
pkgs[4]= [5]
pkgs[2]= [4,5]
pkgs[1]= [2,3,4,5]
for p in pkgs.keys():
install(p)clear is kind, and unclear is unkind. Brene Brown'''
when using n samples to estimate population std,
we will put (n-1) in the denominator:
population_std = sqrt( sample_sum_of_err_sq / (n-1))
i.e.,
population_var * (n-1) = sample_sum_of_err_sq
i.e.,
-1 = sample_sum_of_err_sq / population_var - n
This simulation is to evidence the -1 in the statistic sense
'''
import random
N = 10000 # population size
n = 30 # sample size
num_of_simulation = 500
def sum_of_err_sq(samples):
N = len(samples)
mean = sum(samples) / N
errsq = [(e - mean) ** 2 for e in samples]
return sum(errsq)
def get_bias():
samples = random.sample(population, n)
sample_sum_of_err_sq = sum_of_err_sq(samples)
# true_var * (n-1) = sample_sum_of_err_sq
# n-1 = sample_sum_of_err_sq / true_var
# -1 = sample_sum_of_err_sq / true_var - n
return sample_sum_of_err_sq / population_var - n # ~= -1
def bias_avg_gen(iteration: int):
n = 0
bias_avg = 0
while n < iteration:
bias_new = get_bias()
bias_sum = (bias_avg * n + bias_new)
n += 1
bias_avg = bias_sum / n
yield bias_avg
if __name__ == '__main__':
population = [random.random() for _ in range(N)] # any population works
population_var = sum_of_err_sq(population) / N
for i, bias_avg in enumerate(bias_avg_gen(num_of_simulation)):
print(i, bias_avg)(defn newton
[f fprime tol max-iteration x]
(if (<= max-iteration 0)
nil
(let [y (f x)
yprime (fprime x)
x-new (- x (/ y yprime))]
(if (<= (Math/abs(- x-new x)) (* tol (Math/abs x-new)))
x-new
(newton f fprime tol (dec max-iteration) x-new)))))
(newton #(- (* % %) 2) #(* 2 %) 0.00000001 20 100)
;; => 1.4142135623730951import secrets
import string
alphabet = string.ascii_letters + string.digits
print(''.join(secrets.choice(alphabet) for i in range(16)));; https://stackoverflow.com/questions/32511405/how-would-time-ago-function-implementation-look-like-in-clojure
(defn time-ago [epoch-second]
(let [units [{:name "second" :limit 60 :in-second 1}
{:name "minute" :limit 3600 :in-second 60}
{:name "hour" :limit 86400 :in-second 3600}
{:name "day" :limit 604800 :in-second 86400}
{:name "week" :limit 2629743 :in-second 604800}
{:name "month" :limit 31556926 :in-second 2629743}
{:name "year" :limit Long/MAX_VALUE :in-second 31556926}]
diff (t/in-seconds (t/interval (c/from-epoch epoch-second) (t/now)))]
(if (< diff 5)
"just now"
(let [unit (first (drop-while #(or (>= diff (:limit %))
(not (:limit %)))
units))]
(-> (/ diff (:in-second unit))
Math/floor
int
(#(str % " " (:name unit) (when (> % 1) "s") " ago")))))))
from flask import Flask
app = Flask(__name__)
@app.route('/')
def hello_world():
return 'Hello, World!'(ns server
(:require [coast]))
(defn home [request]
(coast/ok "You're coasting on clojure"))
(def routes (coast/routes [:get "/" ::home]))
(def app (coast/app {:routes routes}))
(coast/server app {:port 1337})print("Hello World")console.log("Hello World");(println "Hello World!")