Computational Geometry in Python: From Theory to Application

When people think computational geometry, in my experience, they typically think one of two things:

  1. Wow, that sounds complicated.
  2. Oh yeah, convex hull.

In this post, I’d like to shed some light on computational geometry, starting with a brief overview of the subject before moving into some practical advice based on my own experiences (skip ahead if you have a good handle on the subject).

What’s all the fuss about?

While convex hull computational geometry algorithms are typically included in an introductory algorithms course, computational geometry is a far richer subject that rarely gets sufficient attention from the average developer/computer scientist (unless you’re making games or something).

Theoretically intriguing…

From a theoretical standpoint, the questions in computational geometry are often exceedingly interesting; the answers, compelling; and the paths by which they’re reached, varied. These qualities alone make it a field worth studying, in my opinion.

For example, consider the Art Gallery Problem: We own an art gallery and want to install security cameras to guard our artwork. But we’re under a tight budget, so we want to use as few cameras as possible. How many cameras do we need?

When we translate this to computational geometric notation, the ‘floor plan’ of the gallery is just a simple polygon. And with some elbow grease, we can prove that n/3 cameras is always sufficient for a polygon on nvertices, no matter how messy it is. The proof itself uses dual graphs, some graph theory, triangulations, and more.

Here, we see a clever proof technique and a result that is curious enough to be appreciated on its own. But if theoretical relevance isn’t enough for you…

And important in-practice

As I mentioned earlier, game development relies heavily on the application of computational geometry (for example, collision detection often relies on computing the convex hull of a set of objects); as do geographic information systems (GIS), which are used for storing and performing computations on geographical data; and robotics, too (e.g., for visibility and planning problems).

Why’s it so tough?

Let’s take a fairly straightforward computational geometry problem: given a point and a polygon, does the point lie inside of the polygon? (This is called the point-in-polygon, or PIP problem.)

PIP does a great job of demonstrating why computational geometry can be (deceptively) tough. To the human eye, this isn’t a hard question. We see the following diagram and it’s immediately obvious to us that the point is in the polygon:

This point-in-polygon problem is a good example of computational geometry in one of its many applications.

Even for relatively complicated polygons, the answer doesn’t elude us for more than a second or two. But when we feed this problem to a computer, it might see the following:

poly = Polygon([Point(0, 5), Point(1, 1), Point(3, 0),
Point(7, 2), Point(7, 6), Point(2, 7)])
point = Point(5.5, 2.5)

What is intuitive to the human brain does not translate so easily to computer language.

More abstractly (and ignoring the need to represent these things in code), the problems we see in this discipline are very hard to rigorize (‘make rigorous’) in a computational geometry algorithm. How would we describe the point-in-polygon scenario without using such tautological language as ‘A point is inside a polygon if it is inside the polygon’? Many of these properties are so fundamental and so basic that it is difficult to define them concretely.

How would we describe the point-in-polygon scenario without using such tautological language as 'it's inside the polygon if it's inside the polygon'?

Difficult, but not impossible. For example, you could rigorize point-in-polygon with the following definitions:

  • A point is inside a polygon if any infinite ray beginning at the point intersects with an odd number of polygon edges (known as the even-odd rule).
  • A point is inside a polygon if it has a non-zero winding number (defined as the number of times that the curve defining the polygon travels around the point).

Unless you’ve had some experience with computational geometry, these definitions probably won’t be a part of your existing vocabulary. And perhaps that’s emblematic of how computational geometry can push you to think differently.

Introducing CCW

Now that we have a sense for the importance and difficulty of computational geometry problems, it’s time to get our hands wet.

At the backbone of the subject is a deceptively powerful primitive operation: counterclockwise, or ‘CCW’ for short. (I’ll warn you now: CCW will pop up again and again.)

CCW takes three points A, B, and C as arguments and asks: do these three points compose a counterclockwise turn (vs. a clockwise turn)? In other words, is A -> B -> C a counterclockwise angle?

For example, the green points are CCW, while the red points are not:

This computational geometry problem requires points both clockwise and counterclockwise.

Why CCW Matters

CCW gives us a primitive operation on which we can build. It gives us a place to start rigorizing and solving computational geometry problems.

To give you a sense for its power, let’s consider two examples.

Determining Convexity

The first: given a polygon, can you determine if it’s convex? Convexity is an invaluable property: knowing that your polygons are convex often lets you improve performance by orders of magnitude. As a concrete example: there’s a fairly straightforward PIP algorithm that runs in Log(n) time for convex polygons, but fails for many concave polygons.

Intuitively, this gap makes sense: convex shapes are ‘nice’, while concave shapes can have sharp edges jutting in and out—they just don’t follow the same rules.

A simple (but non-obvious) computational geometry algorithm for determining convexity is to check that every triplet of consecutive vertices is CCW. This takes just a few lines of Python geometry code (assuming that the points are provided in counterclockwise order—if points is in clockwise order, you’ll want all triplets to be clockwise):

class Polygon(object):
def isConvex(self):
for i in range(self.n):
# Check every triplet of points
A = self.points[i % self.n]
B = self.points[(i + 1) % self.n]
C = self.points[(i + 2) % self.n]
if not ccw(A, B, C):
return False
return True

Try this on paper with a few examples. You can even use this result to define convexity. (To make things more intuitive, note that a CCW curve from A -> B -> C corresponds to an angle of less than 180º, which is a widely taught way to define convexity.)

Line Intersection

As a second example, consider line segment intersection, which can also be solved using CCW alone:

def intersect(a1, b1, a2, b2):
"""Returns True if line segments a1b1 and a2b2 intersect."""
return ccw(a1, b1, a2) != ccw(a1, b1, b2) and ccw(a2, b2, a1) != ccw(a2, b2, b1)

Why is this the case? Line segment intersection can also be phrased as: given a segment with endpoints A and B, do the endpoints C and D of another segment lie on the same side of AB? In other words, if the turns from A -> B -> C and A -> B -> D are in the same direction, the segments can’t intersect. When we use this type of language, it becomes clear that such a problem is CCW’s bread and butter.

A Rigorous Definition

Now that we have a taste for the importance of CCW, let’s see how it’s computed. Given points A, B, and C:

def ccw(A, B, C):
"""Tests whether the turn formed by A, B, and C is ccw"""
return (B.x - A.x) * (C.y - A.y) > (B.y - A.y) * (C.x - A.x)

To understand where this definition comes from, consider the vectors AB and BC. If we take their cross product, AB x BC, this will be a vector along the z-axis. But in which direction (i.e, +z or -z)? As it turns out, if the cross product is positive, the turn is counterclockwise; otherwise, it’s clockwise.

This definition will seem unintuitive unless you have a really good understanding of linear algebra, the right-hand rule, etc. But that’s why we have abstraction—when you think CCW, just think of its intuitive definition rather than its computation. The value will be immediately clear.

My Dive Into Computational Geometry and Programming Using Python

Over the past month, I’ve been working on implementing several computational geometry algorithms in Python. As I’ll be drawing on them throughout the next few sections, I’ll take a second to describe my computational geometry applications, which can be found on GitHub.

Note: My experience is admittedly limited. As I’ve been working on this stuff for months rather than years, take my advice with a grain of salt. That said, I learned much in those few months, so I hope these tips prove useful.

Read the full article in Toptal Engineering blog 

Top Ten Front-End Design Rules For Developers

As front-end developers, our job is, essentially, to turn designs into reality via code. Understanding, and being competent in, design is an important component of that. Unfortunately, truly understanding front-end design is easier said than done. Coding and aesthetic design require some pretty different skill sets. Because of that, some front-end devs aren’t as proficient in the design aspect as they should be, and as a result, their work suffers.

My goal is to give you some easy-to-follow rules and concepts, from one front-end dev to another, that will help you go from start to finish of a project without messing up what your designers worked so hard on (or possibly even allowing you to design your own projects with decent results).

Of course, these rules won’t take you from bad to magnificent in the time it takes to read one article, but if you apply them to your work, they should make a big difference.

Do Stuff In A Graphics Program

It’s truly rare that you complete a project, and go from start to finish while maintaining every single aesthetic mutation in the design files. And, unfortunately, designers aren’t always around to run to for a quick fix.

Therefore, there always comes a point in any front-end job where you end up having to make some aesthetic-related tweaks. Whether it’s making the checkmark that shows when you check the checkbox, or making a page layout that the PSD missed, front-enders often end up handling these seemingly minor tasks. Naturally, in a perfect world this wouldn’t be the case, but I have yet to find a perfect world, hence we need to be flexible.

A good front-end developer has to use professional graphics tools. Accept no substitute.

A good front-end developer has to use professional graphics tools. Accept no substitute.

For these situations, you should always use a graphics program for mockups. I don’t care which tool you choose: Photoshop, Illustrator, Fireworks, GIMP, whatever. Just don’t just attempt to design from your code. Spend a minute launching a real graphics program and figuring out how it should look, then go to the code and make it happen. You may not be an expert designer, but you’ll still end up with better results.

Match the Design, Don’t Try To Beat It

Your job is not to impress with how unique your checkmark is; your job is to match it to the rest of the design.

Those without a lot of design experience can easily be tempted to leave their mark on the project with seemingly minor details. Please leave that to the designers.

Developers have to match the original front-end design as closely as possible.

Developers have to match the original front-end design as closely as possible.

Instead of asking “Does my checkmark look amazing?” you should be asking, “How well does my checkmark match the design?”

Your focus should always be on working with the design, not on trying to outdo it.

Typography Makes All the Difference

You’d be surprised to know how much of the end look of a design is influenced by typography. You’d be just as surprised to learn how much time designers spend on it. This is not a “pick-it-and-go” endeavor, some serious time and effort goes into it.

If you end up in a situation where you actually have to choose typography, you should spend a decent amount of time doing so. Go online and research good font pairings. Spend a few hours trying those pairings and making sure you end up with the best typography for the project.

Is this font right for your project? When in doubt, consult a designer.

Is this font right for your project? When in doubt, consult a designer.

If you’re working with a design, then make sure you follow the designer’s typography choices. This doesn’t just mean choosing the font, either. Pay attention to the line spacing, letter spacing, and so on. Don’t overlook how important it is to match the typography of the design.

Also, make sure you use the right fonts in the correct spot. If the designer uses Georgia for headers only and Open Sans for body, then you shouldn’t be using Georgia for body and Open Sans for headers. Typography can make or break aesthetics easily. Spend enough time making sure you are matching your designer’s typography. It will be time well spent.

Front-end Design Doesn’t Tolerate Tunnel Vision

You’ll probably be making small parts of the overall design.

Tunnel vision is a common pitfall for front-end developers. Don’t focus on a single detail, always look at the big picture.

Tunnel vision is a common pitfall for front-end developers. Don’t focus on a single detail, always look at the big picture.

An example I’ve been going with is making the checkmark for a design that includes custom checkboxes, without showing them checked. It’s important to remember that the parts you are making are small parts of an overall design. Make your checks as important as a checkmark on a page should look, no more, no less. Don’t get tunnel vision about your one little part and make it something it shouldn’t be.

In fact, a good technique for doing this is to take a screenshot of the program so far, or of the design files, and design within it, in the context in which it will be used. That way, you really see how it affects other design elements on the page, and whether it fits its role properly.

Relationships And Hierarchy

Pay special attention to how the design works with hierarchy. How close are the titles to the body of text? How far are they from the text above them? How does the designer seem to be indicating which elements/titles/text bodies are related and which aren’t? They’ll commonly do these things by boxing related content together, using varying white space to indicate relationships, using similar or contrasting colors to indicate related/unrelated content, and so on.

A good front-end developer will respect design relationships and hierarchy. A great developer will understand them.

A good front-end developer will respect design relationships and hierarchy. A great developer will understand them.

It’s your job to make sure that you recognize the ways in which the design accomplishes relationships and hierarchy and to make sure those concepts are reflected in the end product (including for content that was not specifically designed, and/or dynamic content). This is another area (like typography) where it pays to take extra time to make sure you’re doing a good job.

Be Picky About Whitespace And Alignment

This is a great tip for improving your designs and/or better implementing the designs of others: If the design seems to be using spacings of 20 units, 40 units, etc., then make sure every spacing is a multiple of 20 units.

This is a really drop-dead simple way for someone with no eye for aesthetics to make a significant improvement quickly. Make sure your elements are aligned down to the pixel, and that the spacing around every edge of every element is as uniform as possible. Where you can’t do that (such as places where you need extra space to indicate hierarchy), make them exact multiples of the spacing you’re using elsewhere, for example two times your default to create some separation, three times to create more, and so on.

Do your best to understand how the designer used whitespace and follow those concepts in your front-end build.

Do your best to understand how the designer used whitespace and follow those concepts in your front-end build.

A lot of devs achieve this for specific content in the design files, but when it comes to adding/editing content, or implementing dynamic content, the spacing can go all over the place because they didn’t truly understand what they were implementing.

Do your best to understand how the designer used whitespace and follow those concepts in your build. And yes, spend time on this. Once you think your work is done, go back and measure the spacing to ensure you have aligned and uniformly spaced everything as much as possible, then try out the code with lots of varying content to make sure it’s flexible.

If You Don’t Know What You’re Doing, Do Less

I’m not one of those people that thinks every project should use minimalist design, but if you’re not confident in your design chops and you need to add something, then less is more.

Less is more. If your designer did a good job to begin with, you should refrain from injecting your own design ideas.

Less is more. If your designer did a good job to begin with, you should refrain from injecting your own design ideas.

The designer took care of the main stuff; you only need to do minor fillers. If you’re not very good at design, then a good bet is to do as minimal amount as you can to make that element work. That way, you’re injecting less of your own design into the designer’s work, and affecting it as little as possible.

Let the designer’s work take center stage and let your work take the back seat.

Time Makes Fools Of Us All

I’ll tell you a secret about designers: 90 percent (or more) of what they actually put down on paper, or a Photoshop canvas, isn’t that great.

They discard far more than you ever see. It often takes many revisions and fiddling with a design to get it to the point where they’d even let the guy in the next cubicle see their work, never mind the actual client. You usually don’t go from a blank canvas to good design in one step; there’s a bunch iterations in between. People rarely make good work until they understand that and allow for it in their process.

If you think the design can be improved upon, consult your designer. It’s possible they already tried a similar approach and decided against it.

If you think the design can be improved upon, consult your designer. It’s possible they already tried a similar approach and decided against it.

So how do you implement this? One important method is taking time between versions. Work until it looks like something you like then put it away. Give it a few hours (leaving it overnight is even better), then open it up again and take a look. You’ll be amazed at how different it looks with fresh eyes. You’ll quickly pick out areas for improvement. They’ll be so clear you’ll wonder how you possibly missed them in the first place.

In fact, one of the better designers I’ve known takes this idea a lot further. He would start by making three different designs. Then, he’d wait at least 24 hours, look at them again and throw them all out and start from scratch on a fourth. Next, he’d allow a day between each iteration as it got better and better. Only when he opened it up one morning, and was totally happy, or at least, as close as a designer ever gets to totally happy, would he send it to the client. This was the process he used for every design he made, and it served him very well.

I don’t expect you to take it that far, but it does highlight how helpful time without “eyes on the design” can be. It’s an integral part of the design process and can make improvements in leaps and bounds.

Pixels Matter

You should do everything in your power to match the original design in your finished program, down to the last pixel.

Front-end developers should try to match the original design down to the last pixel.

Front-end developers should try to match the original design down to the last pixel.

In some areas you can’t be perfect. For example, your control over letter-spacing might not be quite as precise as that of the designer’s, and a CSS shadow might not exactly match a Photoshop one, but you should still attempt to get as close as possible. For many aspects of the design, you really can get pixel-perfect precision. Doing so can make a big difference in the end result. A pixel off here and there doesn’t seem like much, but it adds up and affects the overall aesthetic much more than you’d think. So keep an eye on it.

There are a number of [tools] that help you compare original designs to end results, or you can just take screenshots and paste them into the design file to compare each element as closely as possible. Just lay the screenshot over the design and make it semi-transparent so that you can see the differences. Then you know how much adjustment you have to make to get it spot on.

Get Feedback

It’s hard to gain an “eye for design.” It’s even harder to do it on your own. You should seek the input of othersto really see how you can make improvements.

I am not suggesting you grab your neighbor and ask for advice, I mean you should consult real designers and let them critique your work and offer suggestions.

Let designers critique your work. Put their criticism to good use and don’t antagonize them.

Let designers critique your work. Put their criticism to good use and don’t antagonize them.

It takes some bravery to do so, but in the end it is one of the most powerful things you can do to improve the project in the short-term, and to improve your skill level in the long run.

Even if all you have to fine tune is a simple checkmark, there are plenty of people willing to help you. Whether it’s a designer friend, or an online forum, seek out qualified people and get their feedback.

Build a long-lasting, productive relationship with your designers. It’s vital for useful feedback, quality, and execution.

Build a long-lasting, productive relationship with your designers. It’s vital for useful feedback, quality, and execution.

It may sound time consuming, and may cause friction between you and your designers, but in the big scheme of things, it’s worth it. Good front-end developers rely on valuable input from designers, even when it’s not something they like to hear.

Therefore, it’s vital to build and maintain a constructive relationship with your designers. You’re all in the same boat, so to get the best possible results you have to collaborate and communicate every step of the way. The investment in building bonds with your designers is well worth it, as it will help everyone do a better job and execute everything on time.


To summarize, here is a short list of design tips for front-end developers:

  • Design in a graphics program. Don’t design from code, not even the small stuff.
  • Match the design. Be conscious of the original design and don’t try to improve it, just match it.
  • Typography is huge. The time you spend making sure it’s right should reflect its importance.
  • Avoid tunnel vision. Make sure your additions stand out only as much as they should. They’re not more important just because you designed them.
  • Relationships and hierarchy: Understand how they work in the design so that you can implement them properly.
  • Whitespace and alignment are important. Make them accurate to the pixel and make them evenly throughout anything you add.
  • If you’re not confident in your skills, then make your additions as minimally styled as you can.
  • Take time between revisions. Come back later to see your design work with fresh eyes.
  • Pixel-perfect implementation is important wherever possible.
  • Be brave. Seek out experienced designers to critique your work.

Not every front-end developer is going to be a fantastic designer, but every front-end dev should at least becompetent in terms of design.

You need to understand enough about design concepts to identify what’s going on, and to properly apply the design to your end product. Sometimes, you can get away with blind copying if you’ve got a thorough designer (and if you’re detail oriented enough to truly copy it pixel for pixel).

However, in order to make large projects shine across many variations of content, you need some understanding of what’s going through the designer’s head. You don’t merely need to see what the design looks like, you need to know why it looks the way it does, and that way you can be mindful of technical and aesthetic limitations that will affect your job.

So, even as a front-end developer, part of your regular self-improvement should always include learning more about design. 

The original article was written by BRYAN GREZESZAK - FREELANCE SOFTWARE ENGINEER @ TOPTAL and can be read here.

Clean Code and The Art of Exception Handling

Exceptions are as old as programming itself. Back in the days when programming was done in hardware, or via low-level programming languages, exceptions were used to alter the flow of the program, and to avoid hardware failures. Today, Wikipedia defines exceptions as:

anomalous or exceptional conditions requiring special processing – often changing the normal flow of program execution…

And that handling them requires:

specialized programming language constructs or computer hardware mechanisms.

So, exceptions require special treatment, and an unhandled exception may cause unexpected behavior. The results are often spectacular. In 1996, the famous Ariane 5 rocket launch failure was attributed to an unhandled overflow exception. History’s Worst Software Bugs contains some other bugs that could be attributed to unhandled or miss-handled exceptions.

Over time, these errors, and countless others (that were, perhaps, not as dramatic, but still catastrophic for those involved) contributed to the impression that exceptions are bad.

The results of improperly handling exceptions have led us to believe that exceptions are always bad.

But exceptions are a fundamental element of modern programming; they exist to make our software better. Rather than fearing exceptions, we should embrace them and learn how to benefit from them. In this article, we will discuss how to manage exceptions elegantly, and use them to write clean code that is more maintainable.

Exception Handling: It’s a Good Thing

With the rise of object-oriented programming (OOP), exception support has become a crucial element of modern programming languages. A robust exception handling system is built into most languages, nowadays. For example, Ruby provides for the following typical pattern:

rescue SpecificError => e
retry if some_condition_met?

There is nothing wrong with the previous code. But overusing these patterns will cause code smells, and won’t necessarily be beneficial. Likewise, misusing them can actually do a lot of harm to your code base, making it brittle, or obfuscating the cause of errors.

The stigma surrounding exceptions often makes programmers feel at a loss. It’s a fact of life that exceptions can’t be avoided, but we are often taught they must be dealt with swiftly and decisively. As we will see, this is not necessarily true. Rather, we should learn the art of handling exceptions gracefully, making them harmonious with the rest of our code.

Following are some recommended practices that will help you embrace exceptions and make use of them and their abilities to keep your code maintainableextensible, and readable:

  • maintainability: Allows us to easily find and fix new bugs, without the fear of breaking current functionality, introducing further bugs, or having to abandon the code altogether due to increased complexity over time.
  • extensibility: Allows us to easily add to our code base, implementing new or changed requirements without breaking existing functionality. Extensibility provides flexibility, and enables a high level of reusability for our code base.
  • readability: Allows us to easily read the code and discover it’s purpose without spending too much time digging. This is critical for efficiently discovering bugs and untested code.

These elements are the main factors of what we might call cleanliness or quality, which is not a direct measure itself, but instead is the combined effect of the previous points, as demonstrated in this comic:

"WTFs/m" by Thom Holwerda, OSNews

With that said, let’s dive into these practices and see how each of them affects those three measures.

Note: We will present examples from Ruby, but all of the constructs demonstrated here have equivalents in the most common OOP languages.

Always create your own ApplicationError hierarchy

Most languages come with a variety of exception classes, organized in an inheritance hierarchy, like any other OOP class. To preserve the readability, maintainability, and extensibility of our code, it’s a good idea to create our own subtree of application-specific exceptions that extend the base exception class. Investing some time in logically structuring this hierarchy can be extremely beneficial. For example:

class ApplicationError < StandardError; end
# Validation Errors
class ValidationError < ApplicationError; end
class RequiredFieldError < ValidationError; end
class UniqueFieldError < ValidationError; end
# HTTP 4XX Response Errors
class ResponseError < ApplicationError; end
class BadRequestError < ResponseError; end
class UnauthorizedError < ResponseError; end
# ...

Example of an application exception hierarchy.

Having an extensible, comprehensive exceptions package for our application makes handling these application-specific situations much easier. For example, we can decide which exceptions to handle in a more natural way. This not only boosts the readability of our code, but also increases the maintainability of our applications and libraries (gems).

From the readability perspective, it’s much easier to read:

rescue ValidationError => e

Than to read:

rescue RequiredFieldError, UniqueFieldError, ... => e

From the maintainability perspective, say, for example, we are implementing a JSON API, and we have defined our own ClientError with several subtypes, to be used when a client sends a bad request. If any one of these is raised, the application should render the JSON representation of the error in its response. It will be easier to fix, or add logic, to a single block that handles ClientErrors rather than looping over each possible client error and implementing the same handler code for each. In terms of extensibility, if we later have to implement another type of client error, we can trust it will already be handled properly here.

Moreover, this does not prevent us from implementing additional special handling for specific client errors earlier in the call stack, or altering the same exception object along the way:

# app/controller/pseudo_controller.rb
def authenticate_user!
fail AuthenticationError if token_invalid? || token_expired?
User.find_by(authentication_token: token)
rescue AuthenticationError => e
report_suspicious_activity if token_invalid?
raise e
def show
rescue ClientError => e

As you can see, raising this specific exception didn’t prevent us from being able to handle it on different levels, altering it, re-raising it, and allowing the parent class handler to resolve it.

Two things to note here:

  • Not all languages support raising exceptions from within an exception handler.
  • In most languages, raising a new exception from within a handler will cause the original exception to be lost forever, so it’s better to re-raise the same exception object (as in the above example) to avoid losing track of the original cause of the error. (Unless you are doing this intentionally).

Never rescue Exception

That is, never try to implement a catch-all handler for the base exception type. Rescuing or catching all exceptions wholesale is never a good idea in any language, whether it’s globally on a base application level, or in a small buried method used only once. We don’t want to rescue Exception because it will obfuscate whatever really happened, damaging both maintainability and extensibility. We can waste a huge amount of time debugging what the actual problem is, when it could be as simple as a syntax error:

# main.rb
def bad_example
rescue Exception
# elsewhere.rb
def i_might_raise_exception!
retrun do_a_lot_of_work!

You might have noticed the error in the previous example; return is mistyped. Although modern editors provide some protection against this specific type of syntax error, this example illustrates how rescue Exception does harm to our code. At no point is the actual type of the exception (in this case a NoMethodError) addressed, nor is it ever exposed to the developer, which may cause us to waste a lot of time running in circles.

Never rescue more exceptions than you need to

The previous point is a specific case of this rule: We should always be careful not to over-generalize our exception handlers. The reasons are the same; whenever we rescue more exceptions than we should, we end up hiding parts of the application logic from higher levels of the application, not to mention suppressing the developer’s ability to handle the exception his or herself. This severely affects the extensibility and maintainability of the code.

If we do attempt to handle different exception subtypes in the same handler, we introduce fat code blocks that have too many responsibilities. For example, if we are building a library that consumes a remote API, handling a MethodNotAllowedError (HTTP 405), is usually different from handling an UnauthorizedError(HTTP 401), even though they are both ResponseErrors.

As we will see, often there exists a different part of the application that would be better suited to handle specific exceptions in a more DRY way.

So, define the single responsibility of your class or method, and handle the bare minimum of exceptions that satisfy this responsibility requirement. For example, if a method is responsible for getting stock info from a remote a API, then it should handle exceptions that arise from getting that info only, and leave the handling of the other errors to a different method designed specifically for these responsibilities:

def get_info
response = HTTP.get(STOCKS_URL + "#{@symbol}/info")
fail AuthenticationError if response.code == 401
fail StockNotFoundError, @symbol if response.code == 404
return JSON.parse response.body
rescue JSON::ParserError

Here we defined the contract for this method to only get us the info about the stock. It handles endpoint-specific errors, such as an incomplete or malformed JSON response. It doesn’t handle the case when authentication fails or expires, or if the stock doesn’t exist. These are someone else’s responsibility, and are explicitly passed up the call stack where there should be a better place to handle these errors in a DRY way.

Resist the urge to handle exceptions immediately

This is the complement to the last point. An exception can be handled at any point in the call stack, and any point in the class hierarchy, so knowing exactly where to handle it can be mystifying. To solve this conundrum, many developers opt to handle any exception as soon as it arises, but investing time in thinking this through will usually result in finding a more appropriate place to handle specific exceptions.

One common pattern that we see in Rails applications (especially those that expose JSON-only APIs) is the following controller method:

# app/controllers/client_controller.rb
def create
@client =[:client])
render json: @client
render json: @client.errors

(Note that although this is not technically an exception handler, functionally, it serves the same purpose, since only returns false when it encounters an exception.)

Read the full post in Toptal Engineering blog 

Ruby vs. Python

Toptal freelance experts Damir Zekic and Amar Sahinovic argue the merits of Ruby versus Python, covering everything from speed to performance. Listen to the podcast and weigh in by voting on the superior language and commenting in the thread below. Listen to them debate here