lxe

Receive GOES-16 and GOES-17 Images with a Raspberry Pi and RTL-SDR dongle

Also see the original Pieter Noordhuis's guide

Hardware

You need:

1. Raspberry Pi Model B (or B+) with a MicroSD Card $35-40
2. An RTL-SDR dongle:

Jpoliachik

- (BOOL)application:(UIApplication *)application didFinishLaunchingWithOptions:(NSDictionary *)launchOptions {
  
	// 1. init window
	self.window = [[UIWindow alloc] initWithFrame:[UIScreen mainScreen].bounds];
	UIViewController *rootViewController = [UIViewController new];

	// 2. backgroundView using LaunchScreen.xib
	UIView *backgroundView = [[[NSBundle mainBundle] loadNibNamed:@"LaunchScreen" owner:self options:nil] firstObject];
	backgroundView.frame = self.window.bounds;
	

pudquick

# Banner-style (default)
from Foundation import NSUserNotification, NSUserNotificationCenter
def notify(title, subtitle, text):
    notification = NSUserNotification.alloc().init()
    notification.setTitle_(str(title))
    notification.setSubtitle_(str(subtitle))
    notification.setInformativeText_(str(text))
    notification.setSoundName_("NSUserNotificationDefaultSoundName")
    NSUserNotificationCenter.defaultUserNotificationCenter().scheduleNotification_(notification)

dypsilon

Frontend Development

Attention: the list was moved to

https://github.com/dypsilon/frontend-dev-bookmarks

This page is not maintained anymore, please update your bookmarks.

---

HeshamMegid

#import <Foundation/Foundation.h>
#import "Contact.h"

@interface AddressBookManager : NSObject

+ (NSString *)nameForContactWithPhoneNumber:(NSString *)phoneNumber;
+ (UIImage *)photoForContactWithPhoneNumber:(NSString *)phoneNumber;

@end

jgeewax

# -*- coding: utf-8 -*-

"""
	A real simple app for using webapp2 with auth and session.

	It just covers the basics. Creating a user, login, logout and a decorator for protecting certain handlers.

	PRE-REQUIREMENTS:

	Set at secret_key in webapp2 config:

chrishamant

#!/usr/bin/env python
"""Split large file into multiple pieces for upload to S3.

S3 only supports 5Gb files for uploading directly, so for larger CloudBioLinux
box images we need to use boto's multipart file support.

This parallelizes the task over available cores using multiprocessing.

Usage:
  s3_multipart_upload.py <file_to_transfer> <bucket_name> [<s3_key_name>]

sontek

#!/usr/bin/env python
import os
import random
import time
import platform

snowflakes = {}

try:
    # Windows Support

astanin

#!/usr/bin/env python
"""Compare two aligned images of the same size.

Usage: python compare.py first-image second-image
"""

import sys

from scipy.misc import imread
from scipy.linalg import norm