Environment
URL: Stage: <dev/staging/qa/prod> (if applicable)
{ | |
"location": { | |
"name": "Nederland", | |
"region": "Colorado", | |
"country": "United States of America", | |
"lat": 39.96, | |
"lon": -105.5, | |
"tz_id": "America/Denver", | |
"localtime_epoch": 1608142276, | |
"localtime": "2020-12-16 11:11" |
URL: Stage: <dev/staging/qa/prod> (if applicable)
export const calculateLoadTimes = () => { | |
// Check performance support | |
if (performance === undefined) { | |
return []; | |
} | |
// Get a list of "resource" performance entries | |
const resources = performance.getEntriesByType("resource"); | |
if (resources === undefined || resources.length <= 0) { | |
return []; |
Packing version 98c8d04-master | |
Deploying to Scrapy Cloud project "373200" | |
Deploy log last 3 lines: | |
{"message": "500 Server Error: Internal Server Error for url: https://kumo-builder-prod.dc21.scrapinghub.com:2376/v1.27/auth", "error": "internal_error"} | |
from sklearn.ensemble import RandomForestClassifier | |
clf = RandomForestClassifier() | |
target_variable = 'does-make-more-than-50k' | |
columns = ['age', 'education', 'hours-worked-per-week'] | |
clf.fit(df[columns], df[target_variable]) |
version: '3.3' | |
services: | |
db: | |
image: mysql:5.7 | |
volumes: | |
- dbdata:/var/lib/mysql | |
restart: always | |
environment: | |
MYSQL_ROOT_PASSWORD: somewordpress |
" Generated by Color Theme Generator at Sweyla | |
" http://sweyla.com/themes/seed/690000/ | |
set background=dark | |
hi clear | |
if exists("syntax_on") | |
syntax reset | |
endif |
" Generated by Color Theme Generator at Sweyla | |
" http://sweyla.com/themes/seed/690000/ | |
set background=dark | |
hi clear | |
if exists("syntax_on") | |
syntax reset | |
endif |
#!/usr/bin/env bash | |
# make sure the user running this script has permission to run docker | |
docker ps > /dev/null | |
# remove "<none>" images | |
docker rmi -f $(docker images | grep none | awk '{ print $3 }') | |
# cleanup exited containers | |
docker rm -f $(docker ps -f status=exited -q) |
from __future__ import print_function | |
import numpy as np | |
np.random.seed(1337) # for reproducibility | |
from keras.preprocessing import sequence | |
from keras.models import Sequential | |
from keras.layers import Dense, Flatten | |
from keras.layers import Embedding | |
from keras.layers import AveragePooling1D | |
from keras.datasets import imdb |