For better or for worse. Here's an unfortunate side effect I've noticed: my programs are vastly more complex and efficient than when I graduated from SICP a year ago, which is good, and yet I can't remember the last time I wrote code that was truly beautiful. Code I felt proud to call my code. Whose inner workings I could explain to a child. To me, efficient Python programs conceal so much of how they work, that striving for craftsmanship can feel alienating. It conceals so much. It's like a black box magic trick: in goes the value... (pause) oh, and there's the answer! And the obvious what's happening in between those two points, the less efficient my solution tends to be. The prize winning solutions are often the most opaque, the most dense with imported methods. And my programs look inevitably kind of haphazard and provisional. Like doodles.
My Scheme programs, on the other hand, looked like Swiss clocks. They pleased me. They wouldn't have worked any other way. They molded to the precise, regimented form they had to be. I understood them. They were good.
I like functional programming. I think the wall I'm hitting might be Python. The thought of a little Clojure or Haskell in my life right now sounds like a beach vacation.
This is the reason, why I started to do little side-projects with clojurescript and reagent 
I love the way how programming with reagent is visual, with almost no friction. I just start repl, start browser, open the code, and every time I save file, I see how my program changes :-)
Compared to my work, where it can take me the first hour to get into the zone, and additional 20 minutes each time I need to switch frameworks, it really feels like a vacation :)
Basically, what it comes down to is realizing that a lot of the libraries and frameworks out there are smoke and mirrors: they provide an initial solution to a common problem, but when you start getting into the details of your problem, the problem you are trying to solve, you end up working around their crappy configuration points. In short, you stop coding and start configuring existing code which is poorly designed to solve your problem.
So what I do is I stop using those libraries. I zealously guard my dependencies, only letting in things that are solid, well-designed, mature, and minimally invasive. I use minimalist frameworks, eschewing ORMs. Most of the time I avoid classes, opting instead to use closures and namedtuples. The result, my code is fast, flexible, easy to understand, easy to test. I migrated around 30,000 lines of code from Python 2.7 to 3.4 in an afternoon--my unit tests caught a few issues and once those were fixed I didn't see any regressions in the following months.
I think the wall you're hitting isn't Python, it's the culture and libraries a lot of people use for Python. But there are a lot of people who don't use those things. Next time you think of reaching for pip or Django, stop yourself: do you need that? Maybe it provides a short-term solution to your problem, but in the long run it's neither a beautiful nor efficient way to write code.
I've been bitten by the data-oriented design bug and it has made my experiences with programming so much better. It turns out Python is really good at this style of programming. There are powerful ideas in co-routines and sub-generators that make stream processing minimal and easier to grasp. Simple ideas like decision tables are so easy to implement that I cringe when I see giant state machines serialized across several classes. Implement backtracking with a stack? Why bother -- functions live on a stack and push/pop: yield-from/yield. We can serialize the state of a co-routine... boom, concurrency. Sometimes it's the little things in Python the surprise me the most and are the reason I keep using it.
Avoid classes where you can! Design your programs around your data. Python has plenty of built-in patterns for manipulating data and aggregates. It's sometimes surprising how simple your programs become when you resist the temptation to start modelling your problem as classes.
I would never discourage someone from pursuing Scheme or Lisps in general (Have you seen Hy? Homoiconic front-end to Python's AST). Scheme does encourage thinking about problems as recursive functions. If iteration is a special case of recursion than Python is breaking ground in the same direction just in different clothes.
Maybe check out Gary Bernhardt's code?
Business logic often requires coding lots of small conditions distributed all over the code base of an application. Especially once you hit the maintenance phase.
I have been working professionally with clojure for about a year and haven't had to look at any Java source code.
One of the things that dissuaded me from ruby was the idioms that have surfaced recently. I was tired of submitting pull requests, only to have people tell me there was a "more idiomatic way" to do things, then rewriting things in a way I felt was less clear then what I had originally written.
My solution to that problem was to find a community who's idiomatic ideals more coincided with mine (which happens to be clojure), but I understand not everyone has that sort of luxury.
Certainly there is something for coding in this way. Just as it can hold a certain delight to have an elegant looking watch. There is a good chance of overbuilding when I see this level of coding from colleagues. Myself included.
I program in a functional style in all of the languages that I get paid to use, but I'm always sad about the lack of many useful features.
And the ill-fated sicpinclojure.com site, which looked beautiful and had such great promise, but mysteriously stalled and died.
Looks like vqc below has done quite a few of the exercises. Nice.
Tommy Hall's SICP Distilled seems like the best shot at a complete book now. It's running a bit behind schedule but appears to be in the home stretch. We'll see!
There was a kickstarter campaign for something called SICP Distilled, a while back. However it requires your github login which seemed kind of sketchy and also none of the content works anyway - http://www.sicpdistilled.com/. Maybe someone else knows more?
Anyway I look forward to seeing more chapters on your blog.
Just start with sequences. Lazy sequences, which are so helpful in the expert system database that's built in SICP, are already right there in Clojure without the complications of force and delay. My thought is you could do a lot more with the higher level examples, but a lot of the first half of the book would have to be rethought. (The functional implementation of Conway's Life in O'Reilly's "Clojure Programming" is as good as anything in the first third of SICP, for example; the example of accelerating series convergence from SICP seems less exciting today than it used to, at least to me.)
Clojure most definitely is not. It's not an accident that Clojure's fn is only two characters. It's design as a language encourages anonymous functions. Along with recur there are many fewer cases where the simpler ways to do something require a name.
The fundamental problem of trying to port SICP to other languages is that SICP is not a book about programming in Scheme. It's a book about software engineering, and the points about software engineering are made in ways that can be readily illustrated in Scheme. Cons is used to illustrate engineering ideas, and while those ideas could be illustrated in Clojure, there's an impedance mismatch between cons and the roughly analogous constructs in Clojure. Part of the baby gets thrown out with the bathwater for little advantage...understanding Scheme probably makes someone a better Clojure programmer, while the force fit of SICP into Clojure probably won't.
—Rich Hickey, author, Clojure programming language
I don't want to put words in Rick's mouth, but I imagine that he means that SICP won't help you learn Clojure the language. Not that SICP won't make you a better programmer in Clojure (and all other languages).
Personally I found it helpful to work through the book in scheme (the language used in the book), porting some of the exercises to Clojure and other languages I'm interested in as a supplement.
We are just starting Chapter 3 and at the current rate of progress it will be at least a year before we have completed the entire book!
Anyone interested is welcome to join us :-)
Hope this one gets to cover the whole book.
Some more solutions can be found at https://github.com/gregsexton/SICP-Clojure