I really like the way NodeJS (and it's browser-side counterparts) handle modules:
var $ = require('jquery');
var config = require('./config.json');
module.exports = function(){};
module.exports = {...}
I am actually rather disappointed by the ES2015 'import' spec which is very similar to the majority of languages.
Out of curiosity, I decided to look for other languages which implement or even support a similar export/import style, but to no avail.
Perhaps I'm missing something, or more likely, my Google Foo isn't up to scratch, but it would be really interesting to see which other languages work in a similar way.
Has anyone come across similar systems?
Or maybe someone can even provide reasons that it isn't used all that often.
It is nearly impossible to properly compare these features. One can only compare their implementation in specific languages. I collected my experience mostly with the language Java and nodejs.
I observed these differences:
You can use require for more than just making other modules available to your module. For example, you can use it to parse a JSON file.
You can use require everywhere in your code, while import is only available at the top of a file.
require actually executes the required module (if it was not yet executed), while import has a more declarative nature. This might not be true for all languages, but it is a tendency.
require can load private dependencies from sub directories, while import often uses one global namespace for all the code. Again, this is also not true in general, but merely a tendency.
Responsibilities
As you can see, the require method has multiple responsibilities: declaring module dependencies and reading data. This is better separated with the import approach, since import is supposed to only handle module dependencies. I guess, what you like about being able to use the require method for reading JSON is, that it provides a really easy interface to the programmer. I agree that it is nice to have this kind of easy JSON reading interface, however there is no need to mix it with the module dependency mechanism. There can just be another method, for example readJson(). This would separate the concerns, so the require method would only be needed for declaring module dependencies.
Location in the Code
Now, that we only use require for module dependencies, it is a bad practice to use it anywhere else than at the top of your module. It just makes it hard to see the module dependencies when you use it everywhere in your code. This is why you can use the import statement only on top of your code.
I don't see the point where import creates a global variable. It merely creates a consistent identifier for each dependency, which is limited to the current file. As I said above, I recommend doing the same with the require method by using it only at the top of the file. It really helps to increase the readability of the code.
How it works
Executing code when loading a module can also be a problem, especially in big programs. You might run into a loop where one module transitively requires itself. This can be really hard to resolve. To my knowledge, nodejs handles this situation like so: When A requires B and B requires A and you start by requiring A, then:
the module system remembers that it currently loads A
it executes the code in A
it remembers that is currently loads B
it executes the code in B
it tries to load A, but A is already loading
A is not yet finished loading
it returns the half loaded A to B
B does not expect A to be half loaded
This might be a problem. Now, one can argue that cyclic dependencies should really be avoided and I agree with this. However, cyclic dependencies should only be avoided between separate components of a program. Classes in a component often have cyclic dependencies. Now, the module system can be used for both abstraction layers: Classes and Components. This might be an issue.
Next, the require approach often leads to singleton modules, which cannot be used multiple times in the same program, because they store global state. However, this is not really the fault of the system but the programmers fault how uses the system in the wrong way. Still, my observation is that the require approach misleads especially new programmers to do this.
Dependency Management
The dependency management that underlays the different approaches is indeed an interesting point. For example Java still misses a proper module system in the current version. Again, it is announced for the next version, but who knows whether this will ever become true. Currently, you can only get modules using OSGi, which is far from easy to use.
The dependency management underlaying nodejs is very powerful. However, it is also not perfect. For example non-private dependencies, which are dependencies that are exposed via the modules API, are always a problem. However, this is a common problem for dependency management so it is not limited to nodejs.
Conclusion
I guess both are not that bad, since each is used successfully. However, in my opinion, import has some objective advantages over require, like the separation of responsibilities. It follows that import can be restricted to the top of the code, which means there is only one place to search for module dependencies. Also, import might be a better fit for compiled languages, since these do not need to execute code to load code.
Related
Different people have told me that in order to improve my Python programming skills, it helps to go and look how existing projects are implemented. But I am struggeling a bit to navigate through the projects and find the parts of the code I'm interested in.
Let's say I'm using butter of the scipy.signal package, and I want to know how it is implemented, so I'm going to scipy's github repo and move to the signal folder. Now, where is the first place I should start looking for the implementation of butter?
I am also a bit confused about what a module/package/class/function is. Is scipy a module? Or a package? And then what is signal? Is there some kind of pattern like module.class.function? (Or another example: matplotlib.pyplot...)
It sounds like you have two questions here. First, how do you find where scipy.signal.butter is implemented? Second, what are the different hierarchical units of Python code (and how do they relate to that butter thing)?
The first one actually has an easy solution. If you follow the link you gave for the butter function, you will see a [source] link just to the right of the function signature. Clicking on that will take you directly to the source of the function in the github repository (pinned to the commit that matches the version of the docs you were reading, which is probably what you want). Not all API documentation will have that kind of link, but when it does it makes things really easy!
As for the second question, I'm not going to fully explain each level, but here are some broad strokes, starting with the most narrow way of organizing code and moving to the more broad ways.
Functions are reusable chunks of code that you can call from other code. Functions have a local namespace when they are running.
Classes are ways of organizing data together with one or more functions. Functions defined in classes are called methods (but not all functions need to be in a class). Classes have a class namespace, and each instance of a class also has its own instance namespace.
Modules are groups of code, often functions or methods (but sometimes other stuff like data too). Each module has a global namespace. Generally speaking, each .py file will create a module when it is loaded. One module can access another module by using an import statement.
Packages are a special kind of module that's defined by a folder foo/, rather than a foo.py file. This lets you organize whole groups of modules, rather than everything being at the same level. Packages can have further sub-packages (represented with nested folders like foo/bar/). In addition to the modules and subpackages that can be imported, a package will also have its own regular module namespace, which will be populated by running the foo/__init__.py file.
To bring this back around to your specific question, in your case, scipy is a top-level package, and scipy.signal is a sub-package within it. The name butter is a function, but it's actually defined in the scipy/signal/_filter_design.py file. You can access it directly from scipy.signal because scipy/signal/__init__.py imports it (and all the other names defined in its module) with from ._filter_design import * (see here).
The design of implementing something in an inner module and then importing it for use in the package's __init__.py file is a pretty common one. It helps modules that would be excessively large to be subdivided, for ease of their developers, while still having a single place to access a big chuck of the API. It is, however, very confusing to work out for yourself, so don't feel bad if you couldn't figure it out yourself. Sometimes you may need to search the repository to find the definition of something, even if you know where you're importing it from.
When I use the path way to import a module, I face a strange problem. The code may look like this:
#[path = "../../models.rs"]
mod models;
This would work. But somebody told me that this way is not recommended. To better understand the Rust import, I have the following questions:
In what situation we should using #[path = "../../xxx.rs"] to import a module?
What are the advantages and disadvantages of this way to import module?
Should we avoid using this way to import module in future?
I searched the Internet, but nobody seem to have these questions.
In what situation we should using #[path = "../../xxx.rs"] to import a module?
It is, as far as I know, never necessary. It could be a way to handle a special situation such as using conditional compilation to import different implementations of a single module, but you can also use pub use to get that effect. For example, the standard library uses both techniques in the same place, for some reason.
What are the advantages and disadvantages of this way to import module?
It lets you place a module's source code in a non-standard location. The disadvantages are that you are placing it in a non-standard location (which may be surprising to readers, including yourself) and that it makes it easy to accidentally duplicate a module.
The second point is the main reason why you hear not to use it: misunderstanding how the module system works leads to people trying to use #[path] to use a module from multiple other modules, and they instead end up duplicating the module, leading to strange errors as the module gets compiled twice in different contexts.
#[path] is an “advanced” feature for special circumstances. It is never necessary to write normal Rust code no matter how many files the code is divided into, and it can be confusing to readers, and therefore it should be avoided unless necessary.
In React, some packages allow you to import Components using either individual assignment: import Card from "#material-ui/core/Card", or via object destructuring: import { Card } from "#material-ui/core".
I read in a Blog that using the object destructuring syntax can have performance ramifications if your environment doesn't have proper tree-shaking functionality. The result being that every component of #material-ui/core is imported, not just the one you wanted.
In what situations could using object destructuring imports cause a decline in application performance and how serious would the impact be? Also, in an environment that does have all the bells and whistles, like the default create-react-app configuration, will using one over the other make any difference at all?
Relying on package internal structure is often discouraged but it's officially valid in Material UI:
import Card from '#material-ui/core/Card';
In order to not depend on this and keep imports shorter, top-level exports can be used
import { Card } from "#material-ui/core"
Both are interchangeable, as long as the setup supports tree-shaking. In case unused top-level exports can be tree-shaken, the second option is preferable. Otherwise the the first option is preferable, it guarantees unused package imports to not be included into the bundle.
create-react-app uses Webpack configuration that supports tree-shaking and can benefit from the second option.
Loading in extra code, such as numerous components from material-ui you may not need, has two primary performance impacts: Download time, and execution time.
Download time is simple: Your JS file(s) are larger, therefore take longer to download, especially over slower connections such as mobile. Properly slimming down your JS using mechanisms like tree shaking is always a good idea.
Execution time is a little less apparent, but also has a similar effect, this time to browsers with less computing power available - again, primarily mobile. Even if the components are never used, the browser must still parse and execute the source and pull it into memory. On your desktop with a powerful processor and plenty of memory you'll probably never notice the difference, but on a slower/older computer or mobile device you may notice a small lag even after the file(s) finish downloading as they are processed.
Assuming your build tooling has properly working tree shaking, my opinion is generally they are roughly equivalent. The build tool will not include the unused components into the compiled JS, so it shouldn't impact either download or execution time.
I'm new to Node.js, but quite like the module system and require().
That being said, coming from a C background, it makes me uneasy seeing the same module being require()'d everywhere. All in all, it leads me to some design choices that deviate from how things are done in C. For example:
Should I require() mongoose in every file that defines a mongoose model? Or inject a mongoose instance into each file that defines a model.
Should I require() my mongoose models in every module that needs them? Or have a model provider that is passed around and used to provide these models.
Ect. For someone who uses dependency injection a lot - my gut C feeling is telling me to require() a module only once, and pass it around as needed. However, after looking at some open-source stuff, this doesn't seem to be Node way of things. require() does make things super easy..
Does it hurt to overuse this mechanism?
require() caches modules when you use it. When you see the same file or module required everywhere it's only being loaded once, and the stored module.exports is being passed around instead. This means that you can use require everywhere and not worry about performance and memory issues.
As cptroot states requiring a module everywhere you need it instead of passing it around as an argument is safe to do and is also much easier. However, you should view any require call as a hardcoded dependency which you can't change easily. E.g. if you want to mock a module for testing these hardcoded dependencies will hurt.
So passing a module instance around as an argument instead of just requiring it again and again reduces the amount of hardcoded dependencies because you inject this dependency now. E.g. in your tests you will benefit from easily injecting a mock instead.
If you go down this road you will want to use a dependency injection container that helps you injecting all your dependencies and get rid of all hardcoded require calls. To choose a dependency injection container appropriate for your project you should read this excellent article. Also check out Fire Up! which I implemented.
I'm working on my 1st Node.js module, and having to do common utility stuff like check types, looping etc.
The native JS for some of this stuff is pretty ugly. Underscore.js makes it more readable and adds a lot of new features too. But if I don't need the new stuff, should I use Underscore or just do it the hard way?
Thanks!
In node.is you can rely on having some ES5 stuff, array iteration functions and utility functions like isArray. In my node modules I never used underscore and had, due to array iteration functions like map, forEach never the need to use underscore or lodash.
I would not avoid a underscore dependency in case I'd really need it. The node.js platform relies on small modules depending on a couple of small modules itself. So why not depend on underscore.
I see no reason to avoid using a module that makes your life easier. And, it just so happens, that underscore.js is the most depended upon package in the npm registry (as of the time of this answer, according to https://npmjs.org/). So yea, no reason to avoid it.
I've never used underscore nor async on real projects. Once you know how to code good javascript it's not necessary to use any helper library. For example, functions that should execute in serie and are asynchronous it's pretty easy to do with a simple "recursive while loop", you don't need to load any library.
But at the end this is a personal preference. Use external libraries if you feel comfortable with them.
Advice: Don't look at the github starts or npm installations to decide which module to use. Being popular doesn't mean being good. I've tried a lot of popular modules and about a 40% of them are just bad/bugged/not really useful. There are a lot of modules that are not popular that are really good. Being popular helps to take a decision but you should not install and use a module just because it's popular.
Underscore does the right thing, which is check for all the native es5 methods first, meaning you won't have much in the way of performance loss on native methods getting replaced with slower non-native versions that basically do the same thing (code here):
var
nativeForEach = ArrayProto.forEach,
nativeMap = ArrayProto.map,
nativeReduce = ArrayProto.reduce,
nativeReduceRight = ArrayProto.reduceRight,
nativeFilter = ArrayProto.filter,
nativeEvery = ArrayProto.every,
nativeSome = ArrayProto.some,
nativeIndexOf = ArrayProto.indexOf,
nativeLastIndexOf = ArrayProto.lastIndexOf,
nativeIsArray = Array.isArray,
nativeKeys = Object.keys,
nativeBind = FuncProto.bind;
Note: prototypes assigned to "Proto" vars earlier.
That said, I'm pretty sure V8 has most if not all of these. Being of client-side dev origins I'd be delighted simply to use the raw naked thing without having to think about how or what library is best for dragging IE kicking and screaming out of the stone age this time, providing the built-in methods aren't as ugly as the DOM API and I would say these aren't.
If underscore does more for you than the above then by all means use it. If it doesn't, I'd consider it a waste of space. All it really does on the browser is give you fallback methods for the older browsers which aren't a going concern in Node. It's light though. I wouldn't object either way if you were on my team and didn't want to write your own versions of something uniquely handled by underscore but would prefer the direct native method names/args, etc. in my own code on the principle of disliking dependencies anywhere I don't need them.
I use underscore in modules that are shared with the browser, not to depend on ES5. Also Underscore has quite a few very useful methods that are not available in ES5, so it would make sense to read their manual page.