This is How I Scrape 99% of Sites

Summary

En este video, se explica cómo realizar scraping de datos en sitios web de comercio electrónico, centrándose en la identificación de la API backend que hidrata la información en el frontend. Se muestra el uso de herramientas como la consola de Chrome y técnicas avanzadas para extraer datos en formato JSON, incluyendo la disponibilidad de productos y precios. Además, se mencionan soluciones para evitar bloqueos mediante proxies de alta calidad. El autor demuestra cómo automatizar este proceso utilizando bibliotecas como Curl cffi y Python, con un enfoque en la extracción eficiente y respetuosa de datos públicos.

Takeaways

• 🔍 La clave para realizar scraping exitoso en sitios de e-commerce es encontrar la API del backend que proporciona los datos del frontend.
• 🛠️ Utilizar las herramientas de inspección de red en Chrome, especialmente el filtrado por 'Fetch XHR', es esencial para encontrar respuestas en formato JSON.
• 💡 Es importante no extraer directamente el HTML, sino buscar los puntos finales de la API que entregan los datos necesarios.
• 🌍 El uso de proxies, como los de Proxy Scrape, es crucial para evitar bloqueos al realizar scraping a gran escala.
• 📄 Los proxies residenciales y móviles son ideales para superar las protecciones antibot de los sitios web.
• 📈 La personalización de los parámetros de búsqueda en la API, como el 'start index', permite manipular los resultados de búsqueda de manera eficiente.
• 🧰 Es importante modelar los datos obtenidos utilizando herramientas como Pydantic para organizar y procesar la información de manera efectiva.
• 👨‍💻 Al utilizar bibliotecas como Curl CFFI, se puede evitar el bloqueo por 'TLS fingerprinting' y obtener una respuesta exitosa del servidor.
• ⚙️ Después de obtener los datos de la API, el siguiente paso es integrarlos en el código mediante la automatización con funciones en Python.
• 📊 Es crucial ser considerado con la cantidad de datos extraídos y evitar sobrecargar los servidores para no ser bloqueado.

Q & A

¿Cuál es la técnica principal que se menciona para realizar scraping de sitios web de comercio electrónico?

La técnica principal es identificar el API backend que el sitio utiliza para llenar la interfaz, en lugar de intentar extraer directamente el HTML.

¿Por qué no es recomendable intentar extraer enlaces o datos del HTML de un sitio web?

Porque muchos sitios web cargan datos dinámicamente a través de APIs backend y el HTML por sí solo no contiene toda la información necesaria para el scraping.

¿Qué herramienta se utiliza en Chrome para inspeccionar las solicitudes de red de un sitio web?

Se utiliza la herramienta de 'Inspect' de Chrome, específicamente la pestaña 'Network', filtrando las solicitudes Fetch/XHR y enfocándose en las respuestas JSON.

¿Cuál es el propósito de usar proxies al realizar scraping de datos a gran escala?

Los proxies ayudan a evitar ser bloqueados por los sitios web al permitir rotar direcciones IP o mantener sesiones prolongadas con una IP, lo cual es útil para superar las protecciones antibots.

¿Qué tipo de datos se puede obtener de las respuestas JSON del API de un sitio de comercio electrónico?

Se puede obtener información como disponibilidad del producto, números de SKU, imágenes, precios y metadatos.

¿Cómo se encuentran los códigos de productos para realizar peticiones al API de un sitio web?

Los códigos de productos se pueden obtener navegando por categorías o utilizando la función de búsqueda del sitio web, y luego observando las solicitudes que aparecen en la pestaña de red del navegador.

¿Qué se necesita para superar el bloqueo de solicitudes al API usando 'curl' o 'requests' en Python?

Es necesario usar herramientas como 'curl cffi' para replicar correctamente la huella digital TLS del navegador, lo que ayuda a que las solicitudes parezcan legítimas y no sean bloqueadas.

¿Cómo se puede modelar los datos obtenidos de un API de manera eficiente en Python?

Se pueden utilizar modelos como 'Pydantic' para estructurar los datos en objetos, lo que facilita la manipulación y comprensión de los datos extraídos del API.

¿Por qué es importante usar encabezados como el 'User-Agent' al realizar scraping?

El 'User-Agent' permite que las solicitudes parezcan como si vinieran de un navegador real, lo que puede ayudar a evitar bloqueos o restricciones impuestas por el sitio web.

¿Cuál es el consejo del autor sobre cómo manejar la extracción de datos sin ser bloqueado?

El autor recomienda ser cuidadoso y no hacer demasiadas solicitudes rápidamente, ya que esto podría hacer que el sitio web bloquee la dirección IP. Es mejor extraer solo los datos necesarios de manera controlada.

Outlines

00:00

🛒 Análisis de Scraping para Datos de E-commerce

El autor explica cómo realiza scraping de datos de sitios de e-commerce para el análisis de competidores y productos. Se enfatiza en no extraer directamente el HTML, sino buscar la API backend que proporciona los datos al frontend. Se usan herramientas de inspección en el navegador (Chrome) y se filtran las respuestas JSON relevantes. A medida que los proyectos crecen, es crucial utilizar proxies de alta calidad para evitar bloqueos, destacando el patrocinio del video por parte de Proxy Scrape, un proveedor que ofrece proxies rotativos y sesiones persistentes. El autor explica la importancia de usar proxies geolocalizados o móviles para evitar la detección por sistemas de protección antibots en los sitios web.

05:02

🔍 Cómo Encontrar Datos de Disponibilidad de Productos

El autor detalla el proceso para encontrar la disponibilidad de productos en el backend de una página. Se utiliza el endpoint de disponibilidad de la API y se experimenta con códigos de productos para obtener los datos deseados. El autor muestra cómo encontrar estos códigos en el sitio web, usando la búsqueda de términos como 'botas', y explica cómo identificar las solicitudes API correctas que entregan los productos listados. Además, señala la importancia de manipular parámetros como 'start index' para extraer diferentes páginas de productos y cómo este proceso puede repetirse con otros datos.

10:02

🛠 Ajustes y Configuración de Código para Scraping

Aquí el autor profundiza en el uso de la librería Curl y cómo manejar errores comunes como denegaciones de acceso al intentar hacer solicitudes a las APIs. Explica cómo solucionar problemas de 'fingerprinting' con herramientas como curl_cffi, que simulan las solicitudes como si fueran hechas por un navegador real. Además, menciona la necesidad de manejar las cabeceras adecuadamente y cómo el uso de proxies ayuda a evitar bloqueos. Esta sección sirve como una introducción para integrar estos ajustes en proyectos de scraping más grandes y automatizados.

15:02

💻 Estructuración y Modelado de Datos en Proyectos de Scraping

En esta sección, el autor se centra en la estructuración del proyecto de scraping. Explica cómo usar Python para modelar datos extraídos de las APIs, utilizando herramientas como Pydantic para estructurar la información de productos. Se detalla la creación de sesiones de solicitud usando proxies y cómo estructurar funciones que interactúan con las APIs. El autor demuestra cómo manejar errores y respuestas inesperadas, e introduce un bucle para procesar y extraer los nombres de los productos. Finalmente, anima a los usuarios a seguir el proyecto y personalizar el scraping según sus propias necesidades, haciendo hincapié en el uso de datos públicos de manera ética.

Keywords

💡Web Scraping

Web scraping es el proceso de extraer datos de sitios web automáticamente. En el video, el autor explica cómo utiliza esta técnica para recopilar información de productos y realizar análisis competitivos en sitios de comercio electrónico. El concepto es central al tema, ya que el video se enfoca en cómo realizar scraping de manera eficiente y cómo evitar bloqueos usando proxies.

💡API Backend

Una API backend es la interfaz que un sitio web utiliza para comunicar datos entre su servidor y el front-end. En el video, el autor menciona que la clave para obtener información de un sitio es encontrar la API que utiliza para poblar datos en el front-end. Esta API entrega información en formato JSON, lo cual facilita su extracción para el scraping.

💡Proxies

Los proxies son servidores intermedios que se utilizan para ocultar la dirección IP original al realizar solicitudes en línea. El video explica cómo el uso de proxies de alta calidad, como Proxy Scrape, es fundamental para evitar bloqueos cuando se realizan múltiples solicitudes a un sitio web durante el scraping, especialmente en sitios protegidos con sistemas anti-bot.

💡Fetch XHR

Fetch XHR es una herramienta de Chrome DevTools que permite rastrear las solicitudes de datos que hace un sitio web. El autor utiliza esta función para detectar y analizar las respuestas JSON que el backend del sitio envía al navegador, lo que le permite encontrar información clave como disponibilidad de productos y precios.

💡JSON

JSON (JavaScript Object Notation) es un formato de datos utilizado comúnmente para el intercambio de información entre servidores y clientes web. En el video, el autor menciona que los datos de productos, como la disponibilidad y los precios, son devueltos en formato JSON, lo cual facilita el proceso de scraping.

💡Producto ID

El Product ID es un identificador único asignado a cada producto en un sitio web. Este dato es esencial para acceder a la información detallada del producto desde la API. El autor explica cómo se puede extraer este ID desde la respuesta JSON para obtener datos adicionales como precios y disponibilidad.

💡Antibot Protection

La protección antibot es un sistema implementado por sitios web para evitar que bots realicen solicitudes automatizadas. El autor señala que, al escalar proyectos de scraping, es probable que las solicitudes sean bloqueadas por estas protecciones, y que el uso de proxies como los residenciales o móviles es una solución eficaz para sortear estos bloqueos.

💡Rotación de IP

La rotación de IP implica cambiar periódicamente la dirección IP utilizada para realizar solicitudes a un servidor, lo que ayuda a evitar que un sitio web bloquee las solicitudes. En el video, el autor menciona que Proxy Scrape ofrece opciones de rotación automática de IPs, lo que permite mantener una sesión sin ser bloqueado durante el scraping.

💡TLS Fingerprinting

El TLS Fingerprinting es una técnica utilizada por servidores web para identificar clientes a partir de patrones en la conexión TLS. El autor menciona que el uso de librerías como Curl CFFI puede ayudar a sortear bloqueos que resultan de esta técnica, ya que permite replicar el comportamiento de un navegador real al realizar solicitudes.

💡Pydantic

Pydantic es una librería de Python que permite modelar datos de manera estructurada y validarlos con facilidad. En el video, el autor utiliza Pydantic para crear modelos que representan la estructura de los datos JSON extraídos de la API, facilitando su manejo y procesamiento en el código.

Highlights

The speaker focuses on scraping e-commerce data for competitor analysis and product analysis.

Emphasizes that scraping HTML directly isn't effective; instead, finding the backend API is key.

Demonstrates how to use Chrome's inspect tool to find the API that hydrates a website's frontend.

Introduces the concept of Fetch XHR responses, with a focus on JSON data as the target for scraping.

Stresses the importance of using high-quality proxies, especially when scraping larger projects.

Mentions Proxy Scrape as a preferred proxy provider, offering various proxy types like residential, datacenter, and mobile.

Describes how to extract product availability and stock information from JSON data.

Explains how to manipulate API requests to fetch product data, such as changing product codes.

Covers techniques for locating product IDs on e-commerce sites using search queries.

Demonstrates how to paginate through large search results using API request manipulation.

Introduces modeling of scraped data using tools like Pydantic for better data organization.

Shows how to handle API requests using libraries like `curl_cffi` to bypass bot protection.

Explains how to fingerprint TLS requests to mimic real browser behavior and avoid 403 errors.

Walks through the process of setting up a Python script for automating e-commerce data scraping.

Concludes with advice on scraping responsibly to avoid overwhelming websites and getting blocked.

Transcripts

a large part of the work I do in

scraping is e-commerce data competitor

analysis product analysis and all that

and I want to show you in this video how

I go about scraping almost every single

site that I come up against especially

ones like this so I've covered this

before but what you want to do is you

absolutely don't want to be trying to

pull out links and trying to um you know

scrape the HTML that's just not going to

work I know if you look over my head

here I'll make it a bit bigger I mean

this is just passing HTML for this is

just not going to work what we want to

do is we want to find the backend API

that this site uses to hydrate the front

end to basically populate this data to

find that we want to open up our inspect

tool our tools here in Chrome go to

network I'll try and make this a little

bit

bigger and then we need to start

interrogating the site now the first

thing I always do pretty much is just

sort of scroll around and see what pops

up I'm going to click on Fetch xhr and

it's responses that are Json that we are

going to be interested in uh you can

either move around go to different

categories or click on a product we'll

do just fine when you start to scale up

projects like this one you'll find that

your requests start to get blocked and

that's where you need to start using

high quality proxies and I want to share

with you the proxy provider that I use

and the sponsor of this Video Proxy

scrape proxy scrape gives us access to

high quality secure fast and ethically

sourced proxies that cover residential

Data Center and mobile with rotating and

sticky session options there's 10

million plus proxy SE in the pool to use

or with unlimited concurrent sessions

from countries all over the globe

enabling us to scrape quickly and

efficiently my goto is either geot

targeted residential proxies based on

the location of the website or the

mobile proxies as these are the best

options for passing antibot protection

on sites and with auto rotation or

sticky sessions it's a good first step

to avoid being blocked for the project

we're working on today I'm going to use

the sticky sessions with residential

proxies holding on to a single IP for

about 3 minutes it's still only one line

of code to add to your project and then

we can let proxy scrape handle the rest

from there and also any traffic you

purchase is yours to use whenever you

need as it doesn't ever expire so if

this all sounds good to you go ahead and

check out proxy scrape at the link in

the description below let's get on with

the video so let's go ahead and look at

what we've got here um so here right

away I can see a load of images and a

load of Json data here the one that I'm

interested in straight away says

availability and this has all the

product availability the like you know

the basically the stock numbers and the

SKS etc for this item that's pretty

handy that's very relevant and the other

one is right here which is sort of the

whole product data everything that uh

comes with it so we can see we've got

all the images and stuff like that and

there's there's pricing information in

here metadata if I Collapse these uh we

can see everything coming up pricing

information so this is essentially the

data that I want now I've shown you all

this before in other videos and if this

is new to you then I'll will cover

everything you need to do to get started

with this but what I haven't done before

is I haven't showed you more of a full

project which is what I'm going to go

through through in a minute um the first

thing that I want to do though is we

need to understand the API and the

endpoints and what's happening so I'm

going to go ahead and I'm just going to

copy the request URL for this one which

is the product now we can see that this

is basically essentially just their API

and by hitting it like this we do indeed

get the Json response for this data now

what that means is we could effectively

take a different um

[Music]

product for example uh let's see if I

can grab the data for this one the code

for this one and just put it on the end

here and we're going to get that

information but how do we go about

getting these product codes well there's

another way that we can do this and uh

I'm going to keep this one open so now

I've got the sort of the product link

here and I'm going to open the um the

availability one as well so we can have

all three and have a look where is the

availability here so again here the

availability it's basically very

straightforward so just going to paste

this in here we get the availability

again if I change the product

code it's going to give us the

availability for that product now to

actually find the product IDs well how

would you find them on the website well

you could either go to a category or you

might want to search and this is kind of

where I tend to go for go for to start

with so I might type something like

boots into the search again with this

open on this side you know here we go

431 results this is how I would

typically sort of look to get this

information so if I come over back to

the um the the data here that I had I

need to scroll to the bottom somewhere

around here we're going to find a um a

request wish it wouldn't show me all of

these actually what I'm going to do is

I'm going to delete all this I had all

the other ones and I'm going to search

again just so it comes up at the top

okay so this is it loading up you can

see it's loading up all these products

and this is because these are the the

products that have come from the search

so this endpoint is actually slightly

different it's going to give you

different bits of information we'll we

will cover that the one I'm looking for

is the actual um search one here search

query there we I found it so what this

is is this is like basically hitting the

M the API Endo with the search query

that we gave it and again you know I can

put this in here put this in I wish this

would go away I don't know what this is

for I wish and I can put this in here

and here is the response now I'm going

to just collapse a lot of this

information uh get rid of all of this

cuz we're not that interested in this

information but what we are interested

in if I make this full screen and we

have a good look is we have a view size

a view set size we have the count which

is 431 which was the whole of the search

uh we have the search term and then we

have the items at 48 per page which was

the view size we also have the current

set which I believe uh no there should

be another one start index here we go so

what we can actually do is we can start

to see are any of these parameters

available for us to manipulate so if I

change the start index to 10 what

happens okay that wasn't the right one

um I think it's actually so start index

didn't work so I'm going to change it

and quite often it's just start maybe

okay start is start index okay that's

fine to find that out if you were I mean

you could try and guess it like that but

what you could do is you can uh if we

just come back here and we manually go

to the next page with the uh developer

tools open you would see that and it

would it would be there so if we scroll

down somewhere along here

start is 48 we can see that there so you

can start to do everything that you

would do on the page um and just keep an

eye on the uh the actual Network Tab and

you'll see everything come through so

now that I know that the uh the start

index works oh way too

big we can start to put together

something that's going to give us we can

use to search we can have like the that

we can start we want to start on zero

index I guess yeah and then we can go

through the items so what we have in the

actual items response is somewhere down

here we have a lot of good information

actually and in some cases this is

enough but a lot of cases you do want to

go actually deep into the product itself

we have a product ID so this product is

some kind of kid Superstar boots right

so now we come back to our products part

end point and we hit this in here here's

the product straight away has come back

and it's given us all this information

and the one that I want to look at the

most is the pricing information it's got

a discount all this cool stuff right

here then we can of course go to the

availability one put the product code in

and here's the available availability

and this one has some availability so

you can see that we're starting to work

out how their API works now this is not

that difficult especially if you've

either worked with rest apis before or

built AR apis before but my best device

as I said is just to look through the

website so what I want to do now is to

take this and I want to turn it into

something we can repeat within our code

uh so I'm going to get rid of this at

the moment I don't think I'm going to

need this uh we can always actually we

can always come back to it and I've got

my um terminal open here in a new folder

let's make this a bit bigger and I'm

going to create a virtual

environment like

so I'm going to activate it what I want

to show you now is a couple of

interesting things so I'm going to go

and I'm going to use Curl I'm going to

take this endpoint that we know that

works in our browser we can see it works

there I'm going to paste it here and we

get denied so this is a curl error and

this is basically you know the akin to

you know we can't get this data like

this well let's try it with requests so

let's Import in requests and we'll do

our response is equal to requests.get

let's put the URL in there we're getting

you can see that we we're having issues

here we're not able to stream the data

for whatever reason so I'm going to

change the headers I can't clear this up

can I clear this up we'll do it this way

we're going to change the headers so we

I'll say our headers are equal to

because you know you always want to do a

good user agent right user agent and let

me just grab one my user

agent this one will be fine put that in

here oh uh I need to sanitize and paste

please there we go cool so now we'll

import requests again and we'll do our

response is equal to requests

doget and we'll grab our URL again this

one will be fine put you in there we'll

say our headers is equal to the headers

that we just created which is the user

agent and response. status code

403 now this is because of TLS

fingerprinting I'm going to cover this

much more in a video much more in depth

coming up so if you're interested in

finding out really why this is happening

and what you can do to avoid it and how

you know everything works underneath the

hood you want to subscribe for that

video but essentially what we want to do

is we're going to um I'm going to come

out of this just so I don't get any Nam

space issues actually I don't need to

we'll do um import we'll do uh from Curl

cffi we're going to import in requests

as uh CU Rec curl cffi is going to give

us a more consistent fingerprint that

looks like a real browser so what I can

do now is I can go up to here we don't

need this one we just want this and

instead of using actual requests I'm

going to use Co requests uh CFI request

and I'll do request. status code and I

got 403 because I forgot to do this

impersonate is equal to and we can just

put Chrome in here you don't have to put

the version and now if I do response do

status code we get our 200 our response.

Json is all the data so we basically

needed to uh get our fingerprint sorted

for the um to make the request you

notice I didn't need any cookies I

didn't need any headers I didn't need

anything other than what curl cffi or

other you know TLS fingerprint um sort

of spoofers do there's a few out there

and I will as I said I'll cover that in

a following video so now that I know

that this is going to work what I'm

going to do is I'm going to go into my

we need to activate this one here I'm

going to do pip three and we're going to

use that curl cffi Library three install

curl cffi and I'm going to use uh rich I

always use Rich for printing we're also

going to use pantic because I want to

get it to a point where we have modeled

the data a bit better um so I will

install these I think that should

probably be enough for us in this

instance and I'm going to touch

main.py and we'll make this open here

now I've imported everything that we're

going to need I'm going to look at

modeling my data a little bit closer now

I've done this already but essentially

what I'm going to do is I'm going to

take so from this the products one and

the search one so we can get that

information I haven't done the

availability one but you can add that

one on nice and easy now that you know

the the end point here so we're going to

model this information I'm basically

just going to take what I want from here

and create a pantic model with it so the

first one is the search item which I'm

going to have the product ID the model

ID price sale price and the display name

and the rating so that's all comes from

that search endpoint and then the same

thing I'm going to have with the search

response which means I can easily find

out and manipulate what page and count

Etc like this so we can see the search

term the count uh of total items for

that search and the start index which I

tolded about earlier and then the items

is the list of search items then I've

modeled the item detail um which is the

the information that I was after before

so I've just basically put the product

description and the pricing information

in as d dictionaries rather than

modeling them because this is quite

Dynamic this data I found some products

they don't have all of this information

so it was easier just to do it like this

again with the product description so

it's up to you but basically what I'm

saying is model your data from here I

creating a new session now I gave I

created a function for this because

initially I thought maybe I would want

to expand on this project and then be

able to import this new session function

from into a different uh you know

different different file or different

part of the project so all I'm saying is

I'm creating a session I'm using

request. session and again this is K

cffi so we have this impersonate here

and I also am importing my proxy now I

talked about sticky proxies earlier and

that's what I'm going to be using here

it's not actually essential to do so

with this specific site but there are

sites that will be um that will sort of

match your fingerprint or your request

with the IP address and if it starts to

different

it starts to get flagged that's a lot

less common though so this should be

fine and now I'm going to model a

function that's going to go ahead and

query the search API we need our session

which we're going to create our query

string and our start number and I've

just put in the an F string into the URL

here to do that and then I'm going to

basically just get the data from here we

want to put in something to handle if we

get a bad response so basically I've put

request uh for status which is going to

throw me an exception if we get anything

that isn't a 200 response basically

going to let me know if we're starting

to get blocked um I'm not too fond of

this I think there's probably a more

elegant way of handling it but this will

work just fine for now then we are

basically taking the response data and

uh pushing it into our model our search

response model we're unpacking it and

I'm unpacking from the raw and item list

which is essentially this piece of here

so raw I'm going to go to this one and

then this one here and then I'm going to

unpack everything that fits into my

models like so again it's up to you how

you model your data and then I'm going

to return the search which is a type of

the search response model I'm going to

do exactly the same now for the detail

API very very similar we're going to put

the item. product ID and this is why I

like to use models with my data because

now look I can clearly see in this

function that this takes in the search

item and then we use the item ID as to

to put into our URL rather than just

having you know the whatever piece of

data from a dictionary I find this much

much easier to see request raise for

State raise for status again and the

same thing we're going to push our

response Json into our item detail model

we're going to return that out and

here's our main function we're going to

create a new session we're going to go

and put a search term in here so again

this is our session that we're giving it

the search query parameter which I

Define in the other function is hoodie

start index I put as one that should

probably be zero but you get the idea

I'm just going to Loop through all of

these and we're going to print out the

name of the product as we go through so

I've got it to this point here I wanted

to show you up to here because this is

kind of like the main part of getting

the data which is absolutely the hardest

part of web scraping and then sort of

understanding how you can go through and

figure out how the sites backend apis

work and then manipulate them slightly

to get the information that you're after

once you've got that data it's entirely

up to you what you're going to do with

it I mean you could collect more here

you probably want to do the availability

etc etc so I'm going to save this and

I'm going to come over here and I'm

going to run P Main and we should

hopefully start to see some of the

product names coming through so I've

searched for hoodie and we're now this

is the information that's coming back so

I'm just looping through the um products

that were on that first search page I it

was 48 and I'm querying their API as if

I was a browser like I showed you on

this page here and just pulling the data

out so this is the absolute best and

easiest way to get data from websites

like this website owners and site

designers will find it very very

difficult to protect their backend API

in such a way that their front end can

still access it just by the nature of it

it happens a lot now it's not always

going to be as easy as this but you will

be surprised how often it is the only

thing I will say is that if you're going

to do this you're going to be able to

pull a lot of data quite quickly so I

would always say you know be be be

consider it and don't hammer it if you

hammer it you're probably going to get

blocked they'll find out anyway but pull

the data that you need it's all publicly

available data I'm not doing anything

there I'm not using any API Keys here

I'm not using anything that I shouldn't

do this is all publicly available data

I'm just pulling it in the most

convenient and easy way to easy easy

fashion as possible so hopefully you got

the idea and you can mimic this now with

your own uh projects Etc if you've

enjoyed this video I'd really appreciate

like comment subscribe it makes a whole

load of difference to me uh it really

does check out the patreon I always post

stuff early on there or consider uh

joining uh the Youtube uh the Youtube

channel down below as well um there's

another video right here which if you

watch this one now you'll continue my

watch time across YouTube and they will

promote my channel more thanks bye