Functional programming languages are just complicated versions of normal program languages

Functional programming languages, while offering distinct paradigms, can often be perceived as unnecessarily complex extensions of traditional, imperative programming languages. This complexity arises from their unique principles and abstractions, which deviate significantly from the straightforward, procedural approach that many programmers are accustomed to.

Firstly, functional programming emphasizes immutability and statelessness, which, although beneficial for certain applications, complicates common tasks. For instance, managing state or handling I/O operations often requires intricate workarounds, such as monads in Haskell, which can obscure program logic rather than simplify it. In contrast, imperative languages allow direct manipulation of state, making these operations intuitive and straightforward.

Secondly, the heavy reliance on higher-order functions and recursion instead of loops can make functional code difficult to read and understand, especially for those trained in traditional programming paradigms. Concepts like lambda calculus and currying, while powerful, introduce an abstract layer that demands a steeper learning curve. This complexity can hinder productivity and make debugging a more challenging task, as tracing through nested function calls can be less intuitive than following a linear flow of commands.

Moreover, while functional languages like Lisp, Haskell, and Scala provide powerful abstractions, they often require a shift in mindset that can be cumbersome for teams accustomed to object-oriented or procedural languages. This shift involves not only learning new syntax but also adopting a new way of thinking about problems, which can be a barrier to entry and slow down the development process.

Furthermore, the emphasis on mathematical purity and declarative programming in functional languages can lead to overengineering. Developers might spend significant time ensuring their code adheres to functional principles, even when such rigor is unnecessary for the task at hand. This can detract from practical problem-solving and lead to bloated, overly complex codebases.

In conclusion, while functional programming languages offer powerful tools for specific problems, they often complicate everyday programming tasks compared to their imperative counterparts. This complexity, driven by their distinctive paradigms and abstractions, can make them seem like unnecessarily complicated versions of more familiar programming languages, thus making them less accessible and practical for general use.

Your argument highlights the theoretical benefits of functional programming, but the practical complexities can't be overlooked. While pure functions and immutability indeed provide predictability, these concepts introduce a layer of abstraction that can be challenging for many developers to grasp, especially those transitioning from imperative backgrounds. The need to wrap everything in functions, often leading to deeply nested structures, can make code harder to read and maintain, contradicting the supposed simplicity.

Concurrency is undoubtedly a strong point for functional languages, yet the abstraction of state management often requires developers to engage with elaborate constructs like monads or actor models. These constructs, while powerful, are not intuitive and obscure the program’s flow, complicating the development process for those who are not deeply versed in functional paradigms.

The mathematical foundation of functional programming, while rigorous, can alienate programmers who are not mathematically inclined. Concepts like lambda calculus and advanced type systems, though beneficial for preventing certain errors, add an intellectual overhead that can slow down the development process, particularly in environments where rapid prototyping and iteration are crucial.

Higher-order functions and code reuse through patterns like map, filter, and reduce do offer elegant solutions, but they also require developers to think in terms of function composition rather than straightforward loops. This shift in thinking can be cumbersome and unintuitive for those who have built their skills around procedural or object-oriented paradigms.

Moreover, while the paradigm shift is potentially beneficial, it is not always necessary. For many common programming tasks, especially those that don't involve heavy concurrency or require a high degree of mathematical precision, imperative languages provide a more pragmatic and accessible solution. They allow developers to implement solutions quickly without the need to engage with the abstract complexities inherent to functional programming.

In conclusion, while functional programming languages offer certain advantages, particularly in specific domains, they are not inherently simpler. The complexity arises not from their capabilities but from the need to adopt and internalize a fundamentally different way of thinking about programming. This makes them seem like more complicated versions of traditional languages to many practitioners, who find that the theoretical benefits do not always translate into practical productivity improvements.

You've highlighted some significant strengths of functional programming, particularly its ability to manage state and concurrency issues more effectively than imperative languages. However, the perception that functional languages are complicated versions stems from the practical realities many developers face.

While immutability and pure functions indeed reduce certain types of bugs, they introduce complexities elsewhere. The requirement to structure code around these principles can lead to convoluted solutions for simple state management tasks, which are straightforward in imperative languages. This abstraction layer, while beneficial in preventing some errors, makes the code less accessible and harder to understand for those new to the paradigm.

Your point about the initial learning curve being offset by long-term benefits is valid, but it assumes that all developers have the time and resources to make this investment. In many environments, rapid delivery and iterative development are prioritized over long-term maintainability, making the immediate complexity of functional programming a significant barrier.

Real-world examples like WhatsApp and Jane Street illustrate that functional programming excels in specific domains where reliability and concurrency are critical. However, these examples do not necessarily reflect the broader programming landscape, where the simplicity and familiarity of imperative languages often provide sufficient robustness and a lower barrier to entry.

Regarding rapid prototyping, while functional languages may lead to fewer runtime errors due to strong type systems, the complexity of understanding these systems and the necessity to conceptualize solutions functionally can slow down the initial stages of development. In contrast, imperative languages allow developers to focus on solving the problem at hand without navigating additional layers of abstraction.

Functional programming languages, while offering elegant solutions to certain problems, can be perceived as more complicated because they require a paradigm shift that is not universally necessary or beneficial. They represent a different approach, not inherently superior, but suited to specific types of problems and environments. For many everyday programming tasks, the practical simplicity of imperative languages makes them the more accessible and efficient choice.