aodin

## gym.py
import os
import pickle
import warnings

import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from tensorflow.keras.callbacks import EarlyStopping
from tensorflow.keras.layers import Dense
from tensorflow.keras.layers import Dropout

## server.py
"""
A standalone version of the server started by `python3 -m http.server`.
Copied from Python 3.9 source.
"""
import contextlib
from functools import partial
import http.server
import os
import socket

## hk_cn_pppgdp.csv

          
            Year
            HK Population
            HK PPPGDP
            HK per capita PPPGDP
            CN Population
            CN PPPGDP
            CN per capita PPPGDP
            HK/CN per capita PPPGDP

            
              1980
              5096000
              34607000000
              6791.0125588697
              987050000
              305579000000
              309.588166759536
              21.9356334899726

            
              1981
              5217000
              41364000000
              7928.69465209891
              1000720000
              351548000000
              351.295067551363
              22.5699003045058

            
              1982
              5297000
              45187000000
              8530.67774211818
              1016540000
              406864000000
              400.243964821847
              21.3136948758622

            
              1983
              5388000
              49781000000
              9239.23533778768
              1030080000
              468460000000
              454.780211245729
              20.3158253356708

            
              1984
              5469000
              56737000000
              10374.2914609618
              1043570000
              559140000000
              535.795394654887
              19.3624125262294

            
              1985
              5539000
              58949000000
              10642.5347535656
              1058510000
              654702000000
              618.512815183607
              17.2066519760086

            
              1986
              5605000
              66814000000
              11920.4281891169
              1075070000
              727324000000
              676.536411582502
              17.6197880631931

            
              1987
              5637000
              77637000000
              13772.7514635444
              1093000000
              832515000000
              761.678865507777
              18.0820974392703

            
              1988
              5712000
              87217000000
              15269.0826330532
              1110260000
              958404000000
              863.224830219948
              17.6884191678808

## matplotlib-whitespace-svg.html
<!DOCTYPE html>
<html>
  <head>
    <meta charset="UTF-8">
    <title>SVG whitespace example</title>
  </head>
  <body>
    <p style="max-width:100px;border:1px solid red">Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.</p>
    <?xml version="1.0" encoding="utf-8" standalone="no"?>
    <!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN"

## quarter.py
import copy
import datetime
import pickle

# Each quarter corresponds to the following month and day combinations:
_q1 = (3, 31)
_q2 = (6, 30)
_q3 = (9, 30)
_q4 = (12, 31)

## onion.sql
CREATE TABLE things_versioned (
    id integer not null,
    name varchar not null,
    version timestamp with time zone default now(),
    PRIMARY KEY (id, version)
)

CREATE VIEW things AS
    SELECT
        DISTINCT ON (id)

## sql_benchmark.go
package main

import (
	"database/sql"
	"encoding/json"
	"log"
	"net/http"
	"os"
	"time"

## sql_results.go
package main

import "database/sql"
import "log"
import _ "github.com/lib/pq"

func main() {
	conn, err := sql.Open("postgres", "user=aaronoellis dbname=bar sslmode=disable")
	if err != nil {
		log.Fatal(err)

## fabfile.py
#!/usr/bin/env python
# vim: ts=4:sw=4:expandtab:autoindent:
import os
import sys
import requests
import filecmp
from fabric.context_managers import hide, settings, prefix
from fabric.api import sudo, task, run, cd, env
from fabric.contrib.console import confirm
from fabric.colors import green

## gamma.jl
# Plotting the Gamma distribution and sample as a normalize histogram

using Distributions
using Gadfly

pdf(d::Gamma, x) = (x ^ (d.α - 1) * e ^ (-x / d.α)) / (d.θ ^ d.α * gamma(d.α))

n = 500

g = Gamma(2., 2.)
	import os
	import pickle
	import warnings

	import numpy as np
	import pandas as pd
	from sklearn.model_selection import train_test_split
	from tensorflow.keras.callbacks import EarlyStopping
	from tensorflow.keras.layers import Dense
	from tensorflow.keras.layers import Dropout
	"""
	A standalone version of the server started by `python3 -m http.server`.
	Copied from Python 3.9 source.
	"""
	import contextlib
	from functools import partial
	import http.server
	import os
	import socket
Year	HK Population	HK PPPGDP	HK per capita PPPGDP	CN Population	CN PPPGDP	CN per capita PPPGDP	HK/CN per capita PPPGDP
1980	5096000	34607000000	6791.0125588697	987050000	305579000000	309.588166759536	21.9356334899726
1981	5217000	41364000000	7928.69465209891	1000720000	351548000000	351.295067551363	22.5699003045058
1982	5297000	45187000000	8530.67774211818	1016540000	406864000000	400.243964821847	21.3136948758622
1983	5388000	49781000000	9239.23533778768	1030080000	468460000000	454.780211245729	20.3158253356708
1984	5469000	56737000000	10374.2914609618	1043570000	559140000000	535.795394654887	19.3624125262294
1985	5539000	58949000000	10642.5347535656	1058510000	654702000000	618.512815183607	17.2066519760086
1986	5605000	66814000000	11920.4281891169	1075070000	727324000000	676.536411582502	17.6197880631931
1987	5637000	77637000000	13772.7514635444	1093000000	832515000000	761.678865507777	18.0820974392703
1988	5712000	87217000000	15269.0826330532	1110260000	958404000000	863.224830219948	17.6884191678808
	<!DOCTYPE html>
	<html>
	<head>
	<meta charset="UTF-8">
	<title>SVG whitespace example</title>
	</head>
	<body>
	<p style="max-width:100px;border:1px solid red">Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.</p>
	<?xml version="1.0" encoding="utf-8" standalone="no"?>
	<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN"
	import copy
	import datetime
	import pickle

	# Each quarter corresponds to the following month and day combinations:
	_q1 = (3, 31)
	_q2 = (6, 30)
	_q3 = (9, 30)
	_q4 = (12, 31)
	CREATE TABLE things_versioned (
	id integer not null,
	name varchar not null,
	version timestamp with time zone default now(),
	PRIMARY KEY (id, version)
	)

	CREATE VIEW things AS
	SELECT
	DISTINCT ON (id)
	package main

	import (
	"database/sql"
	"encoding/json"
	"log"
	"net/http"
	"os"
	"time"
	package main

	import "database/sql"
	import "log"
	import _ "github.com/lib/pq"

	func main() {
	conn, err := sql.Open("postgres", "user=aaronoellis dbname=bar sslmode=disable")
	if err != nil {
	log.Fatal(err)
	#!/usr/bin/env python
	# vim: ts=4:sw=4:expandtab:autoindent:
	import os
	import sys
	import requests
	import filecmp
	from fabric.context_managers import hide, settings, prefix
	from fabric.api import sudo, task, run, cd, env
	from fabric.contrib.console import confirm
	from fabric.colors import green
	# Plotting the Gamma distribution and sample as a normalize histogram

	using Distributions
	using Gadfly

	pdf(d::Gamma, x) = (x ^ (d.α - 1) * e ^ (-x / d.α)) / (d.θ ^ d.α * gamma(d.α))

	n = 500

	g = Gamma(2., 2.)