Add Retries to Your API Calls

Whether you’re making API calls from Node.js or in the browser, connection failures are going to happen eventually. Some request errors are valid. Maybe the endpoint was wrong or the client sent the wrong data. Other times you can be sure that the error is the result of a problem with the connection to the server or one of the many hops in-between. While API and web service monitoring can inform you about the problem, a more active solution can take care of it for you.

To fix this, you can improve your HTTP request library by adding intelligent retry functionality. This kind of remediation is crucial to ensuring your API calls are successful. Some libraries, like got support retrying failed requests out of the box, while others like axios require a separate plugin. If your preferred library doesn’t support them, this article is for you. We’ll explore adding status-code-specific retries to a request, making them incrementally longer with a technique called “back-off”, and more.

#tutorial #api #node.js

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Top 10 API Security Threats Every API Team Should Know

As more and more data is exposed via APIs either as API-first companies or for the explosion of single page apps/JAMStack, API security can no longer be an afterthought. The hard part about APIs is that it provides direct access to large amounts of data while bypassing browser precautions. Instead of worrying about SQL injection and XSS issues, you should be concerned about the bad actor who was able to paginate through all your customer records and their data.

Typical prevention mechanisms like Captchas and browser fingerprinting won’t work since APIs by design need to handle a very large number of API accesses even by a single customer. So where do you start? The first thing is to put yourself in the shoes of a hacker and then instrument your APIs to detect and block common attacks along with unknown unknowns for zero-day exploits. Some of these are on the OWASP Security API list, but not all.

Insecure pagination and resource limits

Most APIs provide access to resources that are lists of entities such as /users or /widgets. A client such as a browser would typically filter and paginate through this list to limit the number items returned to a client like so:

First Call: GET /items?skip=0&take=10 
Second Call: GET /items?skip=10&take=10

However, if that entity has any PII or other information, then a hacker could scrape that endpoint to get a dump of all entities in your database. This could be most dangerous if those entities accidently exposed PII or other sensitive information, but could also be dangerous in providing competitors or others with adoption and usage stats for your business or provide scammers with a way to get large email lists. See how Venmo data was scraped

A naive protection mechanism would be to check the take count and throw an error if greater than 100 or 1000. The problem with this is two-fold:

1. For data APIs, legitimate customers may need to fetch and sync a large number of records such as via cron jobs. Artificially small pagination limits can force your API to be very chatty decreasing overall throughput. Max limits are to ensure memory and scalability requirements are met (and prevent certain DDoS attacks), not to guarantee security.
2. This offers zero protection to a hacker that writes a simple script that sleeps a random delay between repeated accesses.

skip = 0
while True:    response = requests.post('https://api.acmeinc.com/widgets?take=10&skip=' + skip),                      headers={'Authorization': 'Bearer' + ' ' + sys.argv[1]})    print("Fetched 10 items")    sleep(randint(100,1000))    skip += 10

How to secure against pagination attacks

To secure against pagination attacks, you should track how many items of a single resource are accessed within a certain time period for each user or API key rather than just at the request level. By tracking API resource access at the user level, you can block a user or API key once they hit a threshold such as “touched 1,000,000 items in a one hour period”. This is dependent on your API use case and can even be dependent on their subscription with you. Like a Captcha, this can slow down the speed that a hacker can exploit your API, like a Captcha if they have to create a new user account manually to create a new API key.

Insecure API key generation

Most APIs are protected by some sort of API key or JWT (JSON Web Token). This provides a natural way to track and protect your API as API security tools can detect abnormal API behavior and block access to an API key automatically. However, hackers will want to outsmart these mechanisms by generating and using a large pool of API keys from a large number of users just like a web hacker would use a large pool of IP addresses to circumvent DDoS protection.

How to secure against API key pools

The easiest way to secure against these types of attacks is by requiring a human to sign up for your service and generate API keys. Bot traffic can be prevented with things like Captcha and 2-Factor Authentication. Unless there is a legitimate business case, new users who sign up for your service should not have the ability to generate API keys programmatically. Instead, only trusted customers should have the ability to generate API keys programmatically. Go one step further and ensure any anomaly detection for abnormal behavior is done at the user and account level, not just for each API key.

Accidental key exposure

APIs are used in a way that increases the probability credentials are leaked:

1. APIs are expected to be accessed over indefinite time periods, which increases the probability that a hacker obtains a valid API key that’s not expired. You save that API key in a server environment variable and forget about it. This is a drastic contrast to a user logging into an interactive website where the session expires after a short duration.
2. The consumer of an API has direct access to the credentials such as when debugging via Postman or CURL. It only takes a single developer to accidently copy/pastes the CURL command containing the API key into a public forum like in GitHub Issues or Stack Overflow.
3. API keys are usually bearer tokens without requiring any other identifying information. APIs cannot leverage things like one-time use tokens or 2-factor authentication.

If a key is exposed due to user error, one may think you as the API provider has any blame. However, security is all about reducing surface area and risk. Treat your customer data as if it’s your own and help them by adding guards that prevent accidental key exposure.

How to prevent accidental key exposure

The easiest way to prevent key exposure is by leveraging two tokens rather than one. A refresh token is stored as an environment variable and can only be used to generate short lived access tokens. Unlike the refresh token, these short lived tokens can access the resources, but are time limited such as in hours or days.

The customer will store the refresh token with other API keys. Then your SDK will generate access tokens on SDK init or when the last access token expires. If a CURL command gets pasted into a GitHub issue, then a hacker would need to use it within hours reducing the attack vector (unless it was the actual refresh token which is low probability)

Exposure to DDoS attacks

APIs open up entirely new business models where customers can access your API platform programmatically. However, this can make DDoS protection tricky. Most DDoS protection is designed to absorb and reject a large number of requests from bad actors during DDoS attacks but still need to let the good ones through. This requires fingerprinting the HTTP requests to check against what looks like bot traffic. This is much harder for API products as all traffic looks like bot traffic and is not coming from a browser where things like cookies are present.

Stopping DDoS attacks

The magical part about APIs is almost every access requires an API Key. If a request doesn’t have an API key, you can automatically reject it which is lightweight on your servers (Ensure authentication is short circuited very early before later middleware like request JSON parsing). So then how do you handle authenticated requests? The easiest is to leverage rate limit counters for each API key such as to handle X requests per minute and reject those above the threshold with a 429 HTTP response. There are a variety of algorithms to do this such as leaky bucket and fixed window counters.

Incorrect server security

APIs are no different than web servers when it comes to good server hygiene. Data can be leaked due to misconfigured SSL certificate or allowing non-HTTPS traffic. For modern applications, there is very little reason to accept non-HTTPS requests, but a customer could mistakenly issue a non HTTP request from their application or CURL exposing the API key. APIs do not have the protection of a browser so things like HSTS or redirect to HTTPS offer no protection.

How to ensure proper SSL

Test your SSL implementation over at Qualys SSL Test or similar tool. You should also block all non-HTTP requests which can be done within your load balancer. You should also remove any HTTP headers scrub any error messages that leak implementation details. If your API is used only by your own apps or can only be accessed server-side, then review Authoritative guide to Cross-Origin Resource Sharing for REST APIs

Incorrect caching headers

APIs provide access to dynamic data that’s scoped to each API key. Any caching implementation should have the ability to scope to an API key to prevent cross-pollution. Even if you don’t cache anything in your infrastructure, you could expose your customers to security holes. If a customer with a proxy server was using multiple API keys such as one for development and one for production, then they could see cross-pollinated data.

#api management #api security #api best practices #api providers #security analytics #api management policies #api access tokens #api access #api security risks #api access keys

Public ASX100 APIs: The Essential List

We’ve conducted some initial research into the public APIs of the ASX100 because we regularly have conversations about what others are doing with their APIs and what best practices look like. Being able to point to good local examples and explain what is happening in Australia is a key part of this conversation.

Method

The method used for this initial research was to obtain a list of the ASX100 (as of 18 September 2020). Then work through each company looking at the following:

1. Whether the company had a public API: this was found by googling “[company name] API” and “[company name] API developer” and “[company name] developer portal”. Sometimes the company’s website was navigated or searched.
2. Some data points about the API were noted, such as the URL of the portal/documentation and the method they used to publish the API (portal, documentation, web page).
3. Observations were recorded that piqued the interest of the researchers (you will find these below).
4. Other notes were made to support future research.
5. You will find a summary of the data in the infographic below.

Data

With regards to how the APIs are shared:

• Documentation is where just the Swagger/OpenAPI docs are hosted somewhere. e.g. https://api.linkgroup.com/member/docs/index
• Portal is where an interactive portal has been developed. e.g. https://dev.telstra.com/
• The web page is where the company has a single page that isn’t interactive explaining their Public APIs. e.g. https://www.bendigoadelaide.com.au/banking-products-api.asp

#api #api-development #api-analytics #apis #api-integration #api-testing #api-security #api-gateway

An API-First Approach For Designing Restful APIs | Hacker Noon

I’ve been working with Restful APIs for some time now and one thing that I love to do is to talk about APIs.

So, today I will show you how to build an API using the API-First approach and Design First with OpenAPI Specification.

First thing first, if you don’t know what’s an API-First approach means, it would be nice you stop reading this and check the blog post that I wrote to the Farfetchs blog where I explain everything that you need to know to start an API using API-First.

Preparing the ground

Before you get your hands dirty, let’s prepare the ground and understand the use case that will be developed.

Tools

If you desire to reproduce the examples that will be shown here, you will need some of those items below.

• NodeJS
• OpenAPI Specification
• Text Editor (I’ll use VSCode)
• Command Line

Use Case

To keep easy to understand, let’s use the Todo List App, it is a very common concept beyond the software development community.

#api #rest-api #openai #api-first-development #api-design #apis #restful-apis #restful-api

Variables Globales De Python: Cómo Definir Un Ejemplo De Variable Glob

En este artículo, aprenderá los conceptos básicos de las variables globales.

Para empezar, aprenderá cómo declarar variables en Python y qué significa realmente el término 'ámbito de variable'.

Luego, aprenderá las diferencias entre variables locales y globales y comprenderá cómo definir variables globales y cómo usar la globalpalabra clave.

¿Qué son las variables en Python y cómo se crean? Una introducción para principiantes

Puede pensar en las variables como contenedores de almacenamiento .

Son contenedores de almacenamiento para almacenar datos, información y valores que le gustaría guardar en la memoria de la computadora. Luego puede hacer referencia a ellos o incluso manipularlos en algún momento a lo largo de la vida del programa.

Una variable tiene un nombre simbólico y puede pensar en ese nombre como la etiqueta en el contenedor de almacenamiento que actúa como su identificador.

El nombre de la variable será una referencia y un puntero a los datos almacenados en su interior. Por lo tanto, no es necesario recordar los detalles de sus datos e información; solo necesita hacer referencia al nombre de la variable que contiene esos datos e información.

Al dar un nombre a una variable, asegúrese de que sea descriptivo de los datos que contiene. Los nombres de las variables deben ser claros y fácilmente comprensibles tanto para usted en el futuro como para los otros desarrolladores con los que puede estar trabajando.

Ahora, veamos cómo crear una variable en Python.

Al declarar variables en Python, no necesita especificar su tipo de datos.

Por ejemplo, en el lenguaje de programación C, debe mencionar explícitamente el tipo de datos que contendrá la variable.

Entonces, si quisiera almacenar su edad, que es un número entero, o inttipo, esto es lo que tendría que hacer en C:

#include <stdio.h>
 
int main(void)
{
  int age = 28;
  // 'int' is the data type
  // 'age' is the name 
  // 'age' is capable of holding integer values
  // positive/negative whole numbers or 0
  // '=' is the assignment operator
  // '28' is the value
}

Sin embargo, así es como escribirías lo anterior en Python:

age = 28

#'age' is the variable name, or identifier
# '=' is the assignment operator
#'28' is the value assigned to the variable, so '28' is the value of 'age'

El nombre de la variable siempre está en el lado izquierdo y el valor que desea asignar va en el lado derecho después del operador de asignación.

Tenga en cuenta que puede cambiar los valores de las variables a lo largo de la vida de un programa:

my_age = 28

print(f"My age in 2022 is {my_age}.")

my_age = 29

print(f"My age in 2023 will be {my_age}.")

#output

#My age in 2022 is 28.
#My age in 2023 will be 29.

Mantienes el mismo nombre de variable my_age, pero solo cambias el valor de 28a 29.

¿Qué significa el alcance variable en Python?

El alcance de la variable se refiere a las partes y los límites de un programa de Python donde una variable está disponible, accesible y visible.

Hay cuatro tipos de alcance para las variables de Python, que también se conocen como la regla LEGB :

• local ,
• Encerrando ,
• globales ,
• Incorporado .

En el resto de este artículo, se centrará en aprender a crear variables con alcance global y comprenderá la diferencia entre los alcances de variables locales y globales.

Cómo crear variables con alcance local en Python

Las variables definidas dentro del cuerpo de una función tienen alcance local , lo que significa que solo se puede acceder a ellas dentro de esa función en particular. En otras palabras, son 'locales' para esa función.

Solo puede acceder a una variable local llamando a la función.

def learn_to_code():
    #create local variable
    coding_website = "freeCodeCamp"
    print(f"The best place to learn to code is with {coding_website}!")

#call function
learn_to_code()


#output

#The best place to learn to code is with freeCodeCamp!

Mire lo que sucede cuando trato de acceder a esa variable con un alcance local desde fuera del cuerpo de la función:

def learn_to_code():
    #create local variable
    coding_website = "freeCodeCamp"
    print(f"The best place to learn to code is with {coding_website}!")

#try to print local variable 'coding_website' from outside the function
print(coding_website)

#output

#NameError: name 'coding_website' is not defined

Plantea un NameErrorporque no es 'visible' en el resto del programa. Solo es 'visible' dentro de la función donde se definió.

Cómo crear variables con alcance global en Python

Cuando define una variable fuera de una función, como en la parte superior del archivo, tiene un alcance global y se conoce como variable global.

Se accede a una variable global desde cualquier parte del programa.

Puede usarlo dentro del cuerpo de una función, así como acceder desde fuera de una función:

#create a global variable
coding_website = "freeCodeCamp"

def learn_to_code():
    #access the variable 'coding_website' inside the function
    print(f"The best place to learn to code is with {coding_website}!")

#call the function
learn_to_code()

#access the variable 'coding_website' from outside the function
print(coding_website)

#output

#The best place to learn to code is with freeCodeCamp!
#freeCodeCamp

¿Qué sucede cuando hay una variable global y local, y ambas tienen el mismo nombre?

#global variable
city = "Athens"

def travel_plans():
    #local variable with the same name as the global variable
    city = "London"
    print(f"I want to visit {city} next year!")

#call function - this will output the value of local variable
travel_plans()

#reference global variable - this will output the value of global variable
print(f"I want to visit {city} next year!")

#output

#I want to visit London next year!
#I want to visit Athens next year!

En el ejemplo anterior, tal vez no esperaba ese resultado específico.

Tal vez pensaste que el valor de citycambiaría cuando le asignara un valor diferente dentro de la función.

Tal vez esperabas que cuando hice referencia a la variable global con la línea print(f" I want to visit {city} next year!"), la salida sería en #I want to visit London next year!lugar de #I want to visit Athens next year!.

Sin embargo, cuando se llamó a la función, imprimió el valor de la variable local.

Luego, cuando hice referencia a la variable global fuera de la función, se imprimió el valor asignado a la variable global.

No interfirieron entre sí.

Dicho esto, usar el mismo nombre de variable para variables globales y locales no se considera una buena práctica. Asegúrese de que sus variables no tengan el mismo nombre, ya que puede obtener algunos resultados confusos cuando ejecute su programa.

Cómo usar la globalpalabra clave en Python

¿Qué sucede si tiene una variable global pero desea cambiar su valor dentro de una función?

Mira lo que sucede cuando trato de hacer eso:

#global variable
city = "Athens"

def travel_plans():
    #First, this is like when I tried to access the global variable defined outside the function. 
    # This works fine on its own, as you saw earlier on.
    print(f"I want to visit {city} next year!")

    #However, when I then try to re-assign a different value to the global variable 'city' from inside the function,
    #after trying to print it,
    #it will throw an error
    city = "London"
    print(f"I want to visit {city} next year!")

#call function
travel_plans()

#output

#UnboundLocalError: local variable 'city' referenced before assignment

Por defecto, Python piensa que quieres usar una variable local dentro de una función.

Entonces, cuando intento imprimir el valor de la variable por primera vez y luego reasignar un valor a la variable a la que intento acceder, Python se confunde.

La forma de cambiar el valor de una variable global dentro de una función es usando la globalpalabra clave:

#global variable
city = "Athens"

#print value of global variable
print(f"I want to visit {city} next year!")

def travel_plans():
    global city
    #print initial value of global variable
    print(f"I want to visit {city} next year!")
    #assign a different value to global variable from within function
    city = "London"
    #print new value
    print(f"I want to visit {city} next year!")

#call function
travel_plans()

#print value of global variable
print(f"I want to visit {city} next year!")

Utilice la globalpalabra clave antes de hacer referencia a ella en la función, ya que obtendrá el siguiente error: SyntaxError: name 'city' is used prior to global declaration.

Anteriormente, vio que no podía acceder a las variables creadas dentro de las funciones ya que tienen un alcance local.

La globalpalabra clave cambia la visibilidad de las variables declaradas dentro de las funciones.

def learn_to_code():
   global coding_website
   coding_website = "freeCodeCamp"
   print(f"The best place to learn to code is with {coding_website}!")

#call function
learn_to_code()

#access variable from within the function
print(coding_website)

#output

#The best place to learn to code is with freeCodeCamp!
#freeCodeCamp

Conclusión

¡Y ahí lo tienes! Ahora conoce los conceptos básicos de las variables globales en Python y puede distinguir las diferencias entre las variables locales y globales.

Espero que hayas encontrado útil este artículo.

Comenzará desde lo básico y aprenderá de una manera interactiva y amigable para principiantes. También construirá cinco proyectos al final para poner en práctica y ayudar a reforzar lo que ha aprendido.

¡Gracias por leer y feliz codificación!

Fuente: https://www.freecodecamp.org/news/python-global-variables-examples/

#python 

Python Global Variables – How to Define a Global Variable Example

In this article, you will learn the basics of global variables.

To begin with, you will learn how to declare variables in Python and what the term 'variable scope' actually means.

Then, you will learn the differences between local and global variables and understand how to define global variables and how to use the global keyword.

What Are Variables in Python and How Do You Create Them? An Introduction for Beginners

You can think of variables as storage containers.

They are storage containers for holding data, information, and values that you would like to save in the computer's memory. You can then reference or even manipulate them at some point throughout the life of the program.

A variable has a symbolic name, and you can think of that name as the label on the storage container that acts as its identifier.

The variable name will be a reference and pointer to the data stored inside it. So, there is no need to remember the details of your data and information – you only need to reference the variable name that holds that data and information.

When giving a variable a name, make sure that it is descriptive of the data it holds. Variable names need to be clear and easily understandable both for your future self and the other developers you may be working with.

Now, let's see how to actually create a variable in Python.

When declaring variables in Python, you don't need to specify their data type.

For example, in the C programming language, you have to mention explicitly the type of data the variable will hold.

So, if you wanted to store your age which is an integer, or int type, this is what you would have to do in C:

#include <stdio.h>
 
int main(void)
{
  int age = 28;
  // 'int' is the data type
  // 'age' is the name 
  // 'age' is capable of holding integer values
  // positive/negative whole numbers or 0
  // '=' is the assignment operator
  // '28' is the value
}

However, this is how you would write the above in Python:

age = 28

#'age' is the variable name, or identifier
# '=' is the assignment operator
#'28' is the value assigned to the variable, so '28' is the value of 'age'

The variable name is always on the left-hand side, and the value you want to assign goes on the right-hand side after the assignment operator.

Keep in mind that you can change the values of variables throughout the life of a program:

my_age = 28

print(f"My age in 2022 is {my_age}.")

my_age = 29

print(f"My age in 2023 will be {my_age}.")

#output

#My age in 2022 is 28.
#My age in 2023 will be 29.

You keep the same variable name, my_age, but only change the value from 28 to 29.

What Does Variable Scope in Python Mean?

Variable scope refers to the parts and boundaries of a Python program where a variable is available, accessible, and visible.

There are four types of scope for Python variables, which are also known as the LEGB rule:

• Local,
• Enclosing,
• Global,
• Built-in.

For the rest of this article, you will focus on learning about creating variables with global scope, and you will understand the difference between the local and global variable scopes.

How to Create Variables With Local Scope in Python

Variables defined inside a function's body have local scope, which means they are accessible only within that particular function. In other words, they are 'local' to that function.

You can only access a local variable by calling the function.

def learn_to_code():
    #create local variable
    coding_website = "freeCodeCamp"
    print(f"The best place to learn to code is with {coding_website}!")

#call function
learn_to_code()


#output

#The best place to learn to code is with freeCodeCamp!

Look at what happens when I try to access that variable with a local scope from outside the function's body:

def learn_to_code():
    #create local variable
    coding_website = "freeCodeCamp"
    print(f"The best place to learn to code is with {coding_website}!")

#try to print local variable 'coding_website' from outside the function
print(coding_website)

#output

#NameError: name 'coding_website' is not defined

It raises a NameError because it is not 'visible' in the rest of the program. It is only 'visible' within the function where it was defined.

How to Create Variables With Global Scope in Python

When you define a variable outside a function, like at the top of the file, it has a global scope and it is known as a global variable.

A global variable is accessed from anywhere in the program.

You can use it inside a function's body, as well as access it from outside a function:

#create a global variable
coding_website = "freeCodeCamp"

def learn_to_code():
    #access the variable 'coding_website' inside the function
    print(f"The best place to learn to code is with {coding_website}!")

#call the function
learn_to_code()

#access the variable 'coding_website' from outside the function
print(coding_website)

#output

#The best place to learn to code is with freeCodeCamp!
#freeCodeCamp

What happens when there is a global and local variable, and they both have the same name?

#global variable
city = "Athens"

def travel_plans():
    #local variable with the same name as the global variable
    city = "London"
    print(f"I want to visit {city} next year!")

#call function - this will output the value of local variable
travel_plans()

#reference global variable - this will output the value of global variable
print(f"I want to visit {city} next year!")

#output

#I want to visit London next year!
#I want to visit Athens next year!

In the example above, maybe you were not expecting that specific output.

Maybe you thought that the value of city would change when I assigned it a different value inside the function.

Maybe you expected that when I referenced the global variable with the line print(f" I want to visit {city} next year!"), the output would be #I want to visit London next year! instead of #I want to visit Athens next year!.

However, when the function was called, it printed the value of the local variable.

Then, when I referenced the global variable outside the function, the value assigned to the global variable was printed.

They didn't interfere with one another.

That said, using the same variable name for global and local variables is not considered a best practice. Make sure that your variables don't have the same name, as you may get some confusing results when you run your program.

How to Use the global Keyword in Python

What if you have a global variable but want to change its value inside a function?

Look at what happens when I try to do that:

#global variable
city = "Athens"

def travel_plans():
    #First, this is like when I tried to access the global variable defined outside the function. 
    # This works fine on its own, as you saw earlier on.
    print(f"I want to visit {city} next year!")

    #However, when I then try to re-assign a different value to the global variable 'city' from inside the function,
    #after trying to print it,
    #it will throw an error
    city = "London"
    print(f"I want to visit {city} next year!")

#call function
travel_plans()

#output

#UnboundLocalError: local variable 'city' referenced before assignment

By default Python thinks you want to use a local variable inside a function.

So, when I first try to print the value of the variable and then re-assign a value to the variable I am trying to access, Python gets confused.

The way to change the value of a global variable inside a function is by using the global keyword:

#global variable
city = "Athens"

#print value of global variable
print(f"I want to visit {city} next year!")

def travel_plans():
    global city
    #print initial value of global variable
    print(f"I want to visit {city} next year!")
    #assign a different value to global variable from within function
    city = "London"
    #print new value
    print(f"I want to visit {city} next year!")

#call function
travel_plans()

#print value of global variable
print(f"I want to visit {city} next year!")

Use the global keyword before referencing it in the function, as you will get the following error: SyntaxError: name 'city' is used prior to global declaration.

Earlier, you saw that you couldn't access variables created inside functions since they have local scope.

The global keyword changes the visibility of variables declared inside functions.

def learn_to_code():
   global coding_website
   coding_website = "freeCodeCamp"
   print(f"The best place to learn to code is with {coding_website}!")

#call function
learn_to_code()

#access variable from within the function
print(coding_website)

#output

#The best place to learn to code is with freeCodeCamp!
#freeCodeCamp

Conclusion

And there you have it! You now know the basics of global variables in Python and can tell the differences between local and global variables.

I hope you found this article useful.

You'll start from the basics and learn in an interactive and beginner-friendly way. You'll also build five projects at the end to put into practice and help reinforce what you've learned.

Thanks for reading and happy coding!

Source: https://www.freecodecamp.org/news/python-global-variables-examples/

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