Tutorial by Examples: d

Start two named nodes in two terminal windows: >iex --name [email protected] iex([email protected])> >iex --name [email protected] iex([email protected])> Connect two nodes by instructing one node to connect: iex([email protected])> Node.connect :"[email protected]" true The two n...

Start a named process on one IP address: $ iex --name [email protected] --cookie chocolate iex([email protected])> Node.ping :"[email protected]" :pong iex([email protected])> Node.list [:"[email protected]"] Start another named process on a different IP address: $ iex ...

Use the HTML or <audio> element to embed video/audio content in a document. The video/audio element contains one or more video/audio sources. To specify a source, use either the src attribute or the <source> element; the browser will choose the most suitable one. Audio tag example: &...

Code that uses generics has many benefits over non-generic code. Below are the main benefits Stronger type checks at compile time A Java compiler applies strong type checking to generic code and issues errors if the code violates type safety. Fixing compile-time errors is easier than fixing runt...

Install the necessary Python Library via: $ pip install elasticsearch Connect to Elasticsearch, Create a Document (e.g. data entry) and "Index" the document using Elasticsearch. from datetime import datetime from elasticsearch import Elasticsearch # Connect to Elasticsearch using ...

Example uses basic HTTP syntax. Any <#> in the example should be removed when copying it. You can use the _cat APIs to get a human readable, tabular output for various reasons. GET /_cat/health?v <1> The ?v is optional, but it implies that you want "verbose" output. _...

One can select rows and columns of a dataframe using boolean arrays. import pandas as pd import numpy as np np.random.seed(5) df = pd.DataFrame(np.random.randint(100, size=(5, 5)), columns = list("ABCDE"), index = ["R" + str(i) for i in range(5)]) print (...

import pandas as pd import numpy as np np.random.seed(0) tuples = list(zip(*[['bar', 'bar', 'foo', 'foo', 'qux', 'qux'], ['one', 'two', 'one', 'two','one', 'two']])) idx = pd.MultiIndex.from_tuples(tuples, names=['first', 'second']) df = pd.DataFrame(np.random.randn(6, ...

data.table offers a wide range of possibilities to reshape your data both efficiently and easily For instance, while reshaping from long to wide you can both pass several variables into the value.var and into the fun.aggregate parameters at the same time library(data.table) #v>=1.9.6 DT <- ...

The ** operator works similarly to the * operator but it applies to keyword parameters. def options(required_key:, optional_key: nil, **other_options) other_options end options(required_key: 'Done!', foo: 'Foo!', bar: 'Bar!') #> { :foo => "Foo!", :bar => "Bar!" ...

struct Struct<'a> { x: &'a u32, } This specifies that any given instance of Struct has lifetime 'a, and the &u32 stored in x must have a lifetime of at least 'a.

.Net 4.0 type Lazy guarantees thread-safe object initialization, so this type could be used to make Singletons. public class LazySingleton { private static readonly Lazy<LazySingleton> _instance = new Lazy<LazySingleton>(() => new LazySingleton()); public stati...

The * operator can be used to unpack variables and arrays so that they can be passed as individual arguments to a method. This can be used to wrap a single object in an Array if it is not already: def wrap_in_array(value) [*value] end wrap_in_array(1) #> [1] wrap_in_array([1, 2, 3]) ...

Instead of requesting an ILoggerFactory and creating an instance of ILogger explicitly, you can request an ILogger (where T is the class requesting the logger). public class TodoController : Controller { private readonly ILogger _logger; public TodoController(ILogger<TodoController...

Using iris dataset: import sklearn.datasets iris_dataset = sklearn.datasets.load_iris() X, y = iris_dataset['data'], iris_dataset['target'] Data is split into train and test sets. To do this we use the train_test_split utility function to split both X and y (data and target vectors) randomly w...

Different operations with data are done using special classes. Most of the classes belong to one of the following groups: classification algorithms (derived from sklearn.base.ClassifierMixin) to solve classification problems regression algorithms (derived from sklearn.base.RegressorMixin) to so...

For ease of testing, sklearn provides some built-in datasets in sklearn.datasets module. For example, let's load Fisher's iris dataset: import sklearn.datasets iris_dataset = sklearn.datasets.load_iris() iris_dataset.keys() ['target_names', 'data', 'target', 'DESCR', 'feature_names'] You can ...

A Service is a component which runs in the background (on the UI thread) without direct interaction with the user. An unbound Service is just started, and is not bound to the lifecycle of any Activity. To start a Service you can do as shown in the example below: // This Intent will be used to star...

await operator and async keyword come together: The asynchronous method in which await is used must be modified by the async keyword. The opposite is not always true: you can mark a method as async without using await in its body. What await actually does is to suspend execution of the code ...

1) BASIC SIMPLE WAY Database-driven applications often need data pre-seeded into the system for testing and demo purposes. To make such data, first create the seeder class ProductTableSeeder use Faker\Factory as Faker; use App\Product; class ProductTableSeeder extends DatabaseSeeder { pub...