habibutsu

'''
Requirements:
    geographiclib==1.46.3
    pyproj==1.9.5.1
    geopy==1.11.0
    git+https://github.com/xoolive/geodesy@c4eb611cc225908872715f7558ca6a686271327a
    geo-py==0.4
'''
from math import radians, sin, cos, asin, sqrt, pi, atan, atan2, fabs
from time import time

habibutsu

function metersToPixelsAtMaxZoom(latitude, radius){
    // ~0.075m/px (meters per pixel)
    return radius / 0.075 / Math.cos(latitude * Math.PI / 180)
}
map.addSource("point", {
    type: 'FeatureCollection',
    features: [
        {
            "type": "Feature",
            "geometry": {

habibutsu

init:
	pip install msgpack-python==0.4.8
	go get gopkg.in/vmihailenco/msgpack.v2

run:
	go run main.go

habibutsu

IMAGE_TAG=2017-04-10

data/${IMAGE_TAG}-raspbian-jessie-lite.img:
	mkdir -p data
	wget \
		-O data/${IMAGE_TAG}-raspbian-jessie-lite.zip \
		http://director.downloads.raspberrypi.org/raspbian_lite/images/raspbian_lite-${IMAGE_TAG}/${IMAGE_TAG}-raspbian-jessie-lite.zip
	unzip data/${IMAGE_TAG}-raspbian-jessie-lite.zip -d ./data

data/kernel-arm.img:

habibutsu

# Remove unused docker images
docker rmi $(docker images | grep "<none>"| awk -F' ' '{print $3}')
docker rmi $(docker images -aq --filter dangling=true)

# Remove orphaned docker volumes
docker volume rm $(docker volume ls -qf dangling=true)

# Remove dead containers
docker ps --filter status=dead -aq | xargs -r docker rm -v

habibutsu

import Html exposing (text)

import Json.Decode

type alias Car =
  { sensor1: Int
  , sensor2: Int
  }

type DrivingMode

habibutsu

import io
import logging
import math

import cv2
import numpy as np
import matplotlib.pyplot as plt

from tqdm import tqdm

habibutsu

import itertools
import random
import sys
import operator
import functools
import types
import math

import numpy as np

habibutsu

import io
from http import HTTPStatus
from urllib.request import Request, urlopen
from urllib.error import HTTPError


class RemoteFile(io.IOBase):
    '''
        Example of usage
        

habibutsu

Управление памятью в Python

Организация памяти

Память в Python организована в несколько уровней.

• Слой 3 (Уровень ядра) - предназначен для non-object данных самого интерпрeтатора
• Слой 2 - выделение памяти под объекты
• Слой 1 - PyMem_ API