ericxyan

TICK Stack

Solution for collecting, storing, visualizing and alerting on time-series data at scale. All components of the platform are designed to work together seamlessly.

• Telegraf: Collects time-series data from a variety of sources
• InfluxDB:
• Chronograf: Visualizes and graphs
• Kapacitor: Alerting, ETL and detects anomalies in time-series data

Why Influx?

• Open Source - MIT
• Integrated - Data collection, storage, visualization and alerting

jnhuynh

.
├── index.ios.js
├── js
│   ├── actions
│   │   ├── ChatServerActionCreators.js
│   │   └── ChatThreadActionCreators.js
│   ├── components
│   │   ├── ChatScreen
│   │   │   ├── index.js

boopathi

Settings

1. Create a project in XCode with the default settings
   • iOS > Application > Single View Application
   • Language: Swift
2. Under project General settings, add ReactKit to Linked Framework and Libraries
   • + > Add Other... and choose /path/to/react-native/ReactKit/ReactKit.xcodeproj
3. Now ReactKit would have been imported. Link it by choosing it from the list.
   • + > lib.ReactKit.a
4. Under project Build Settings,

masahirompp

/// <reference path="../tsd/tsd.d.ts" />

import mongoose = require('mongoose');
import passport = require('passport');

interface IUser extends mongoose.Document {
  provider: string;
  id: string;
  authorId: string;
  displayName: string;

RockingRolli

from rest_framework.authentication import TokenAuthentication
from .models import MongoToken
from rest_framework import exceptions


class MongoTokenAuthentication(TokenAuthentication):
    model = MongoToken

    def authenticate_credentials(self, key):
        try:

k33g

<div id="demo">
    <h1>{{bob.fields.firstName}} {{bob.fields.lastName}}</h1>
</div>

<ul id="humans-list">
    <li v-repeat="humans">
        {{fields.firstName}} {{fields.lastName}}
    </li>
</ul>

addyosmani

CSS Layout Debugger

A tweet-sized debugger for visualizing your CSS layouts. Outlines every DOM element on your page a random (valid) CSS hex color.

One-line version to paste in your DevTools

Use $$ if your browser aliases it:

~ 108 byte version

lucasmcastro

>>> from pymongo import MongoClient
>>> import datetime
post = {"author": "Mike","text": "My first blog post!","tags": ["mongodb", "python", "pymongo"], "date": datetime.datetime.utcnow()}
>>> uri = "mongodb://pyladies:[email protected]:27167/series4ladies"
>>> client = MongoClient(uri)
>>> client
MongoClient('dbh16.mongolab.com', 27167)
>>> client.series4ladies
Database(MongoClient('dbh16.mongolab.com', 27167), u'series4ladies')
>>> db = client.series4ladies

scottmcarthur

/// <reference path="angular.d.ts" />
/// <reference path="angular-resource.d.ts" />

interface IEmployee extends ng.resource.IResource<IEmployee>
{
    id: number;
    firstName : string;
    lastName : string;
}
interface IEmployeeResource extends ng.resource.IResourceClass<IEmployee>

max-mapper

// data comes from here http://stat-computing.org/dataexpo/2009/the-data.html
// download 1994.csv.bz2 and unpack by running: cat 1994.csv.bz2 | bzip2 -d > 1994.csv
// 1994.csv should be ~5.2 million lines and 500MB
// importing all rows into leveldb took ~50 seconds on my machine

// there are two main techniques at work here:
// 1: never create JS objects, leave the data as binary the entire time (binary-split does this)
// 2: group lines into 16 MB batches, to take advantage of leveldbs batch API (byte-stream does this)

var level = require('level')