How to Create Full Text Search using Laravel 8 Scout Algolia

Laravel 8 scout full-text search tutorial; In a web application, a Full-text search feature is exorbitantly helpful for site users to traverse through content-rich web and mobile applications.

This comprehensive tutorial will explain how to profoundly integrate full-text search in a Laravel application using the Laravel Scout algolia library. We will gradually raise the curtain from every step that is essential to share on creating a full-text search using laravel scout algolia;

Adding or implementing Algolia in Laravel has become super easy, and that has been made possible by Laravel Scout. Laravel scout offers a powerful scout package that amplifies the integration of full-text search directly through your model.

Laravel Scout renders a simple, driver-based solution for implementing a full-text search to your Eloquent models. Utilizing model observers, Scout automatically retains your search indexes in sync with your Eloquent records.

Scout comes with Algolia and MeiliSearch drivers; nevertheless, writing custom drivers has never been easy, not just that you can freely extend Scout with your custom search implementations.

Laravel 8 Algolia Full Text Search Example

  • Step 1: Create New Laravel Project
  • Step 2: Update Database Details in ENV
  • Step 3: Install Laravel Scout & Algolia Packages
  • Step 4: Set Up Algolia in Laravel
  • Step 5: Set Up Model and Migration
  • Step 6: Set Up Controller
  • Step 7: Create Routes
  • Step 8: Configure Blade View
  • Step 9: Run Laravel Project

#laravel #web-development #php

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Buddha Community

How to Create Full Text Search using Laravel 8 Scout Algolia

I am Developer

1597475640

Laravel 7 Full Text Search MySQL

Here, I will show you how to create full text search in laravel app. You just follow the below easy steps and create full text search with mysql db in laravel.

Laravel 7 Full Text Search Mysql

Let’s start laravel full-text search implementation in laravel 7, 6 versions:

  1. Step 1: Install Laravel New App
  2. Step 2: Configuration DB .evn file
  3. Step 3: Run Migration
  4. Step 4: Install Full Text Search Package
  5. Step 5: Add Fake Records in DB
  6. Step 6: Add Routes,
  7. Step 7: Create Controller
  8. Step 8: Create Blade View
  9. Step 9: Start Development Server

https://www.tutsmake.com/laravel-full-text-search-tutorial/

#laravel full text search mysql #laravel full text search query #mysql full text search in laravel #full text search in laravel 6 #full text search in laravel 7 #using full text search in laravel

Easter  Deckow

Easter Deckow

1655630160

PyTumblr: A Python Tumblr API v2 Client

PyTumblr

Installation

Install via pip:

$ pip install pytumblr

Install from source:

$ git clone https://github.com/tumblr/pytumblr.git
$ cd pytumblr
$ python setup.py install

Usage

Create a client

A pytumblr.TumblrRestClient is the object you'll make all of your calls to the Tumblr API through. Creating one is this easy:

client = pytumblr.TumblrRestClient(
    '<consumer_key>',
    '<consumer_secret>',
    '<oauth_token>',
    '<oauth_secret>',
)

client.info() # Grabs the current user information

Two easy ways to get your credentials to are:

  1. The built-in interactive_console.py tool (if you already have a consumer key & secret)
  2. The Tumblr API console at https://api.tumblr.com/console
  3. Get sample login code at https://api.tumblr.com/console/calls/user/info

Supported Methods

User Methods

client.info() # get information about the authenticating user
client.dashboard() # get the dashboard for the authenticating user
client.likes() # get the likes for the authenticating user
client.following() # get the blogs followed by the authenticating user

client.follow('codingjester.tumblr.com') # follow a blog
client.unfollow('codingjester.tumblr.com') # unfollow a blog

client.like(id, reblogkey) # like a post
client.unlike(id, reblogkey) # unlike a post

Blog Methods

client.blog_info(blogName) # get information about a blog
client.posts(blogName, **params) # get posts for a blog
client.avatar(blogName) # get the avatar for a blog
client.blog_likes(blogName) # get the likes on a blog
client.followers(blogName) # get the followers of a blog
client.blog_following(blogName) # get the publicly exposed blogs that [blogName] follows
client.queue(blogName) # get the queue for a given blog
client.submission(blogName) # get the submissions for a given blog

Post Methods

Creating posts

PyTumblr lets you create all of the various types that Tumblr supports. When using these types there are a few defaults that are able to be used with any post type.

The default supported types are described below.

  • state - a string, the state of the post. Supported types are published, draft, queue, private
  • tags - a list, a list of strings that you want tagged on the post. eg: ["testing", "magic", "1"]
  • tweet - a string, the string of the customized tweet you want. eg: "Man I love my mega awesome post!"
  • date - a string, the customized GMT that you want
  • format - a string, the format that your post is in. Support types are html or markdown
  • slug - a string, the slug for the url of the post you want

We'll show examples throughout of these default examples while showcasing all the specific post types.

Creating a photo post

Creating a photo post supports a bunch of different options plus the described default options * caption - a string, the user supplied caption * link - a string, the "click-through" url for the photo * source - a string, the url for the photo you want to use (use this or the data parameter) * data - a list or string, a list of filepaths or a single file path for multipart file upload

#Creates a photo post using a source URL
client.create_photo(blogName, state="published", tags=["testing", "ok"],
                    source="https://68.media.tumblr.com/b965fbb2e501610a29d80ffb6fb3e1ad/tumblr_n55vdeTse11rn1906o1_500.jpg")

#Creates a photo post using a local filepath
client.create_photo(blogName, state="queue", tags=["testing", "ok"],
                    tweet="Woah this is an incredible sweet post [URL]",
                    data="/Users/johnb/path/to/my/image.jpg")

#Creates a photoset post using several local filepaths
client.create_photo(blogName, state="draft", tags=["jb is cool"], format="markdown",
                    data=["/Users/johnb/path/to/my/image.jpg", "/Users/johnb/Pictures/kittens.jpg"],
                    caption="## Mega sweet kittens")

Creating a text post

Creating a text post supports the same options as default and just a two other parameters * title - a string, the optional title for the post. Supports markdown or html * body - a string, the body of the of the post. Supports markdown or html

#Creating a text post
client.create_text(blogName, state="published", slug="testing-text-posts", title="Testing", body="testing1 2 3 4")

Creating a quote post

Creating a quote post supports the same options as default and two other parameter * quote - a string, the full text of the qote. Supports markdown or html * source - a string, the cited source. HTML supported

#Creating a quote post
client.create_quote(blogName, state="queue", quote="I am the Walrus", source="Ringo")

Creating a link post

  • title - a string, the title of post that you want. Supports HTML entities.
  • url - a string, the url that you want to create a link post for.
  • description - a string, the desciption of the link that you have
#Create a link post
client.create_link(blogName, title="I like to search things, you should too.", url="https://duckduckgo.com",
                   description="Search is pretty cool when a duck does it.")

Creating a chat post

Creating a chat post supports the same options as default and two other parameters * title - a string, the title of the chat post * conversation - a string, the text of the conversation/chat, with diablog labels (no html)

#Create a chat post
chat = """John: Testing can be fun!
Renee: Testing is tedious and so are you.
John: Aw.
"""
client.create_chat(blogName, title="Renee just doesn't understand.", conversation=chat, tags=["renee", "testing"])

Creating an audio post

Creating an audio post allows for all default options and a has 3 other parameters. The only thing to keep in mind while dealing with audio posts is to make sure that you use the external_url parameter or data. You cannot use both at the same time. * caption - a string, the caption for your post * external_url - a string, the url of the site that hosts the audio file * data - a string, the filepath of the audio file you want to upload to Tumblr

#Creating an audio file
client.create_audio(blogName, caption="Rock out.", data="/Users/johnb/Music/my/new/sweet/album.mp3")

#lets use soundcloud!
client.create_audio(blogName, caption="Mega rock out.", external_url="https://soundcloud.com/skrillex/sets/recess")

Creating a video post

Creating a video post allows for all default options and has three other options. Like the other post types, it has some restrictions. You cannot use the embed and data parameters at the same time. * caption - a string, the caption for your post * embed - a string, the HTML embed code for the video * data - a string, the path of the file you want to upload

#Creating an upload from YouTube
client.create_video(blogName, caption="Jon Snow. Mega ridiculous sword.",
                    embed="http://www.youtube.com/watch?v=40pUYLacrj4")

#Creating a video post from local file
client.create_video(blogName, caption="testing", data="/Users/johnb/testing/ok/blah.mov")

Editing a post

Updating a post requires you knowing what type a post you're updating. You'll be able to supply to the post any of the options given above for updates.

client.edit_post(blogName, id=post_id, type="text", title="Updated")
client.edit_post(blogName, id=post_id, type="photo", data="/Users/johnb/mega/awesome.jpg")

Reblogging a Post

Reblogging a post just requires knowing the post id and the reblog key, which is supplied in the JSON of any post object.

client.reblog(blogName, id=125356, reblog_key="reblog_key")

Deleting a post

Deleting just requires that you own the post and have the post id

client.delete_post(blogName, 123456) # Deletes your post :(

A note on tags: When passing tags, as params, please pass them as a list (not a comma-separated string):

client.create_text(blogName, tags=['hello', 'world'], ...)

Getting notes for a post

In order to get the notes for a post, you need to have the post id and the blog that it is on.

data = client.notes(blogName, id='123456')

The results include a timestamp you can use to make future calls.

data = client.notes(blogName, id='123456', before_timestamp=data["_links"]["next"]["query_params"]["before_timestamp"])

Tagged Methods

# get posts with a given tag
client.tagged(tag, **params)

Using the interactive console

This client comes with a nice interactive console to run you through the OAuth process, grab your tokens (and store them for future use).

You'll need pyyaml installed to run it, but then it's just:

$ python interactive-console.py

and away you go! Tokens are stored in ~/.tumblr and are also shared by other Tumblr API clients like the Ruby client.

Running tests

The tests (and coverage reports) are run with nose, like this:

python setup.py test

Author: tumblr
Source Code: https://github.com/tumblr/pytumblr
License: Apache-2.0 license

#python #api 

I am Developer

1617089618

Laravel 8 Tutorial for Beginners

Hello everyone! I just updated this tutorial for Laravel 8. In this tutorial, we’ll go through the basics of the Laravel framework by building a simple blogging system. Note that this tutorial is only for beginners who are interested in web development but don’t know where to start. Check it out if you are interested: Laravel Tutorial For Beginners

Laravel is a very powerful framework that follows the MVC structure. It is designed for web developers who need a simple, elegant yet powerful toolkit to build a fully-featured website.

Recommended:-Laravel Try Catch

#laravel 8 tutorial #laravel 8 tutorial crud #laravel 8 tutorial point #laravel 8 auth tutorial #laravel 8 project example #laravel 8 tutorial for beginners

I am Developer

1599536794

Laravel 8 New Features | Release Notes - Tuts Make

In this post, i will show you what’s new in laravel 8 version.

#What’s new in Laravel 8?

  • 1 - Change Path Of Default Models Directory
  • 2 - Removed Controllers Namespace Prefix
  • 3 - Enhancements on php artisan serve
  • 4 - Enhanced Rate Limiting
  • 5 - Enhanced on Route Caching
  • 6 - Update on Pagination Design
  • 8 - Dynamic Blade Componenets
  • 7 - Update Syntax for Closure Based Event Listeners
  • 8 - Queueable Model Event Listeners
  • 9 - Maintenance mode: secret access
  • 10 - Maintenance mode: pre-rendered page
  • 11 - Queued job batching
  • 12 - Queue backoff()
  • 13 - Laravel Factory

https://www.tutsmake.com/laravel-8-new-features-release-notes/

#laravel 8 features #laravel 8 release date #laravel 8 tutorial #news - laravel 8 new features #what's new in laravel 8 #laravel 8 release notes

Hollie  Ratke

Hollie Ratke

1597989600

Text Analysis Within a Full-Text Search Engine

Full-Text Search refers to techniques for searching text content within a document or a collection of documents that hold textual content. A Full-Text search engine examines all the textual content within documents as it tries to match a single search term or several terms, text analysis being a pivotal component.

You’ve probably heard of the most well-known Full-Text Search engine: Lucene with Elasticsearch built on top of it. Couchbase’s Full-Text Search (FTS) Engine is powered by Bleve, and this article will showcase the various ways to analyze text within this engine.

Bleve is an open-sourced text indexing and search library implemented in Go, developed in-house at Couchbase.

Couchbase’s FTS engine supports indexes that subscribe to data residing within a Couchbase Server and indexes data that it ingests from the server. It’s a distributed system – meaning it can partition data across multiple nodes in a cluster and searches involve scattering the request and gathering responses from across all nodes within the cluster before responding to the application.

The FTS engine distributes documents ingested for an index across a configurable number of partitions and these partitions could reside across multiple nodes within a cluster. Each partition follows the same set of rules that the FTS index is configured with – to analyze and index text into the full-text search database.

The text analysis component of a Full-Text search engine is responsible for breaking down the raw text into a list of words – which we’ll refer to as tokens. These tokens are more suitable for indexing in the database and searching.

Couchbase’s FTS Engine handles text indexing for JSON documents. It builds an index for the content that is analyzed and stores into the database – the index along with all the relevant metadata needed to link the tokens generated to the original documents within which they reside.

An Inverted index is the data structure chosen to index the tokens generated from text, to make search queries faster. This index links every token generated to documents that contain the token.

For example, take the following documents …

The inverted index for the tokens generated from the 2 documents above would resemble this…

Here’s a diagram highlighting the components of the full-text search engine …

A Text Analyzer

The components of a text analyzer can broadly be classified into 2 categories:

  • Tokenizer
  • Filters

Couchbase’s engine further categorizes filters into:

  • Character filters
  • Token filters

Before we dive into the function of each of these components, here’s an overview of a text analyzer …

Tokenizer

A tokenizer is the first component to which the documents are subjected to. As the name suggests, it breaks the raw text into a list of tokens. This conversion will depend on a rule-set defined for the tokenizer.

Stock tokenizers…

Take this sample text for an example: “_this is my email ID: _abhi123@cb.com

A couple of configurable tokenizers…

  • Exception … This tokenizer allows the user to enter exception patterns (regular expressions) over the stock tokenizers.
  • Regexp … This tokenizer extracts text that matches the pattern (a regular expression) as tokens.

For example:

#json #couchbase #search #go #text analysis #full-text search #bleve #full-text #full-text-indexing