You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


February 17, 2020











We can find the concept of generic types across many languages such as Java, C#. Naturally, they found their way into TypeScript. In this article, we discuss their purpose and provide various examples. We also discuss naming conventions for generics that we can stumble upon.

Introducing TypeScript Generics

One of the qualities that we strive for when developing software is the reusability of our components. The above also applies to TypeScript, as the types of our data are also subject to change. With Generics, we can write code that can adapt to a variety of types as opposed to enforcing them.

There is a high chance that you’ve already encountered generics. They are a common approach present, for example, in React.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 import { ChangeEvent , useState , useCallback } from 'react' ; function useInputManagement ( ) { const [ value , setValue ] = useState ( '' ) ; const handleChange = useCallback ( ( event : ChangeEvent < HTMLInputElement > ) = > { setValue ( event . target . value ) ; } , [ ] ) ; return { value , handleChange } }

The above example uses a custom React hook. If you want to know more on how to design custom hooks, check out The Facade pattern and applying it to React Hooks

We can use generics to create highly reusable classes, types, interfaces, and functions.

The most basic example is the one with the identity function that we can find in the official documentation. Let’s inspect it closely:

1 2 3 function identity ( argument : number ) : number { return argument ; }

The above function returns the argument that we pass to it. Unfortunately, it means that we need to create a function for every return type. That, unfortunately, does not meet the criteria of reusability.

To improve the above code, we can introduce a type variable. To declare a type variable, we need to append it to the name of our function by writing function identity<T>.

Now, we are free to use it within our function:

1 2 3 function identity < T > ( argument : T ) : T { return argument ; }

Above, we indicate that the type of the argument and the return type of the identity function should be the same.

The most straightforward way to use the above function is to pass the desired type when calling it:

1 identity < string > ( 'Hello world!' ) ;

TypeScript is a bit smarter, though. Instead of explicitly setting T to a string, we can let the compiler figure out the type on its own:

1 identity ( 'Hello world!' ) ;

Arrow functions

We can also do the above with the use of arrow functions:

1 const identity = < T > ( argument : T ) : T = > argument ;

The only issue is with the .tsx files. The above code results in the following error:

Parsing error: JSX element ‘T’ has no corresponding closing tag

The easiest way to fix this issue is to add a trailing comma:

1 const identity = < T , > ( argument : T ) : T = > argument ;

A more real-life example

The promise-based Fetch API is powerful and flexible, but might not work as you might expect, coming from libraries like axios.

If you want to know more about the above API, check out Comparing working with JSON using the XHR and the Fetch API

One of the things that we can do is always reject promises when the request fails. On success, we might want to call the json() function to extract the data.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 function request < T > ( url : string , options ? : RequestInit ) : Promise < T > { return fetch ( url , options , ) . then ( ( response ) = > { if ( ! response . ok ) { return Promise . reject ( ) ; } return response . json ( ) ; } ) ; }

The json method might throw an error in some cases, for example when there is no body in the response. It would be a good idea to make the above example more bug-proof. The RequestInit is a built-in interface used for the options of the fetch function.

1 2 3 4 5 interface User { id : number ; name : string ; email : string ; }

1 2 3 4 request < User [ ] > ( 'https://jsonplaceholder.typicode.com/users' ) . then ( ( users ) = > { console . log ( ` There are $ { users . length } users ` ) ; } ) ;

There are a few interesting things happening above. When we pass a type to the request function, we pass it further to have a return type of Promise<T>. The Promise is a built-in interface that is also generic.

By calling request<User[]>('https://jsonplaceholder.typicode.com/users') we indicate that our promise resolves with an array of users.

Generic interfaces and classes

Aside from using built-in generic interfaces such as Promise, we can surely create our own.

1 2 3 4 interface KeyValuePair < K , V > { key : K ; value : V ; }

1 2 3 4 const keyValuePair: KeyValuePair < string , string > = { key : 'name' , value : 'John' }

As you can see above, our generics can have more than just a single type variable.

We can create generic classes with the same level of success.

1 2 3 4 5 6 7 8 class KeyValuePair < K , V > { public key: K ; public value: V ; constructor ( key : K , value : V ) { this . key = key ; this . value = value ; } }

1 const keyValuePair = new KeyValuePair ( 'name' , 'John' ) ;

Generic constraints

Making our types very flexible is not always the most suitable approach. Consider this simple example:

1 2 3 function getEmailDomain < T > ( entity : T ) { return entity . email . split ( '@' ) . pop ( ) ; }

Property ’email’ does not exist on type ‘T’

Above, we want to extract the email property from the entity. Unfortunately, we can’t be sure if it exists.

To deal with the above issue, we can put a constraint on the T type variable.

1 2 3 interface WithEmail { email : string ; }

1 2 3 function getEmailDomain < T extends WithEmail > ( entity : T ) { return entity . email . split ( '@' ) . pop ( ) ; }

While the getName is still generic, it now has a constraint: the type that we pass to it needs to extend the HasName interface.

1 2 3 4 request < User > ( 'https://jsonplaceholder.typicode.com/users/1' ) . then ( ( user ) = > { console . log ( ` The email domain that user has is $ { getEmailDomain ( user ) } ` ) ; } ) ;

If you want to read more about interfaces such as the one above, check out the Interface segregation principle from Applying SOLID principles to your TypeScript code.

If we attempt to pass an argument that does not meet the above constraints, we encounter an error.

Naming convention

Generics are a popular solution that derives from languages like Java and C#. Since it originated from the above languages, it also inherits their naming conventions. Let’s look into the Java Tutorials from the Oracle:

By convention, type parameter names are single, uppercase letters. This stands in sharp contrast to the variable naming conventions that you already know about, and with good reason: Without this convention, it would be difficult to tell the difference between a type variable and an ordinary class or interface name. The most commonly used type parameter names are: E – Element (used extensively by the Java Collections Framework)

K – Key

N – Number

T – Type

V – Value

S,U,V etc. – 2nd, 3rd, 4th types

The above convention seems to be the most popular, also within the TypeScript community. Official documentation for C# and TypeScript also uses it. But are the above arguments still valid?

Modern IDEs do a good job of preventing you from mistaking a type variable for an ordinary variable. The more variables we introduce, the easier it is to mistake them due to one-character naming.

Other developers also stumbled upon the above issue. The Google Java Style Guide allows multi-character names, that end with a capital letter T.

Each type variable is named in one of two styles: A single capital letter, optionally followed by a single numeral (such as E , T , X , T2 )

, , , ) A name in the form used for classes (see Section 5.2.2, Class names), followed by the capital letter T (examples: RequestT , FooBarT ).

I don’t like one-character variable names. If the most popular convention is wrong, maybe we should shy away from it.

There seems to be a bit of discussion going on about the naming of the type variables. For example, there are quite a few comments on this article by Tim Boudreau. I like the approach suggested by Erwin Mueller with merely appending the word Type.

1 Map < KeyType , ValueType >

Summary

In this article, we’ve gone through the generics in TypeScript. This includes generic functions, classes, and interfaces. We’ve also examined some examples of how and when to use them. We’ve also touched on a very important subject: the naming convention.

I’m looking forward to hearing about your personal opinion on them. Feel free to let me know in the comments.