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Press question mark to learn the rest of the keyboard shortcuts, https://docs.python.org/3/library/collections.abc.html. More so than most people realize! But if you need to check it explicitly, you can test for an iterable by hasattr(object_in_question, "__iter__") or hasattr(object_in_question, "__getitem__"). Given an argument that could be either a string or a collection of strings, process each string. Instead, it typically employs the EAFP (Easier to Ask Forgiveness than Permission) style of programming. iter cannot perform any sanity checks for objects which only Read our Privacy Policy. (That's what I want for example when a recursive function could take a string or a container of strings. that the object returned by __iter__ is an iterator. in a list you have both iterables and non-iterables and you need to treat each element differently according to it's type (treating iterables on try and non-iterables on except, solutions to this problem which attempt to actually iterate over the object (e.g. To be honest, this sounds like you're doing something that doesn't make a lot of sense in the first place. Unnecessary verbosity. By emphasizing interfaces rather than specific types, well-designed code improves its flexibility by allowing polymorphic substitution. Iterables can be used in a for loop and in many other places where a sequence is needed (zip(), map(), ). Checking for an instance of Iterable or Sequence, or checking for the You should catch "TypeError" in the ` except: return False ` line. The result of type(variable) will always point to the same memory location as the class of that variable. Checking for __iter__ works on sequence types, but it would fail on e.g. Since you acknowledge that Alfe's solution is better, why didn't you edit your answer to simply say that? The Python glossary: it is (should be) implemented by all iterables, including, the Python philosophy of "ask for forgiveness, not permission" doesn't work well when e.g. This one is straightforward. constructs an iterator that tries to fetch items by index, starting at zero, until an IndexError is raised. As noted by others, strings are collections. For example, a user can check if a point is in a 3D cube, but how would you iterate through this object? Note that this function executes faster for objects with __iter__ since it doesn't test for __getitem__. registered as Iterable or that have an __iter__() method, but This is how you would check if an object was an iterable without even trying. Is there a PRNG that visits every number exactly once, in a non-trivial bitspace, without repetition, without large memory usage, before it cycles? How to check if a string is a substring of items in a list of strings? provide __getitem__, because it has no way to check whether the items of the object are accessible by integer index. Feel free to skip right to the next section if you already know. Shoving that in a function is also a very good idea so your code isn't riddled with that as an if argument throughout but instead just a nice little if _seq_but_not_str(x): and you can modify what that does on the fly if you need it to also reject for something else or you no longer want False for bytes, etc. so many detailed answers above with many upvotes and you throw in an unexplained answer meh. A conjecture is a conclusion based on existing evidence - however, a conjecture cannot be proven. 2013-2022 Stack Abuse. They need at least Python 2.6 and work only for new-style classes. scatter how to check isinstance of iterable in python? It's shorter (and doesn't require additional imports) without losing any clarity: having a "contains" method feels like a natural way to check if something is a collection of objects. Is moderated livestock grazing an effective countermeasure for desertification? None-iterable objects would not implement this for obvious reasons. Many other strategies here will say yes to strings. Let's try this out with a regular list and a UserList from the collections framework: Python is a dynamically typed language, and sometimes, due to user-error, we might deal with an unexpected data type. By convention, the __iter__ method of an iterator should return the object itself (i.e. Graphs are an extremely versatile data structure. In this tutorial, we've gone over three ways to check if a variable is a list in Python - the type() function, the is operator and isinstance() function. I often find convenient, inside my scripts, to define an iterable function. The only case where isinstance() didn't work but iter() did was with UserDict when using Python 2. gone in the future (although it is not deprecated as I write this). b) o has a __getitem__ method. Python exceptions are often faster than if-statements. It does seem like there's not a specific thing here and you just need a little logic. Duck typing doesn't work here. Tuple an immutable collection of items. Armed with that knowledge, you will be able to understand why the best you can do is. I will list the facts first and then follow up with a quick reminder of what happens when you employ a for loop in python, followed by a discussion to illustrate the facts. Note: is_iterable() will say yes to strings of type bytes and bytearray. This function also takes sub-classes into consideration, so any list sub-classes will also return True for being an instance of the list. it does not detect classes that iterate with the __getitem__() If you do not have numpy, you can simply implement this code, or the one above. value dictionary json python filter filtering marlborough list All rights reserved. Note that the iterator raises StopIteration when it cannot return the next item and that the IndexError which is raised for item == 3 is handled internally. Find centralized, trusted content and collaborate around the technologies you use most. Duck-typing avoids tests using type() or isinstance(). which basically checks if the object implements the in operator. How should I deal with coworkers not respecting my blocking off time in my calendar for work? latest The collections module provides some abstract base classes, which allow to ask classes or instances if they provide particular functionality, for example: However, this does not check for classes that are iterable through __getitem__. method. In fact, Site design / logo 2022 Stack Exchange Inc; user contributions licensed under CC BY-SA. dictionary append Just because something can contain something doesn't necessarily mean it's iterable. attribute __iter__ is not enough. Should I remove older low level jobs/education from my CV at this point? If an object o implements __iter__, the iter function will make sure I like duck typing, it just happens that strings specifically would exhibit incorrect behavior while not throwing an exception. This means that the returned object Get tutorials, guides, and dev jobs in your inbox. Most iterable objects should rely on __iter__ where special-case objects fall back to __getitem__, though either is required for an object to be iterable. and the output when looping over an instance: On point 7: your iterable classes should implement __iter__. must implement __next__ (or next in Python 2) and __iter__. When adding a new disk to RAID 1, why does it sync unused space? However, built in types do, and if you want to check if you can call len function on it, checking for len is more secure. There are valid reasons to have __getitem__ in a non-iterable object and with them the above code doesn't work well. The isiterable func at the following code returns True if object is iterable. Are you using lists? If you ask what an object can. Check out our hands-on, practical guide to learning Git, with best-practices, industry-accepted standards, and included cheat sheet. (Pun intended). I would like to know the right answer too, until then, here is one possibility (which would work on strings, too): The iter built-in checks for the __iter__ method or in the case of strings the __getitem__ method. Use the Abstract Base Classes. @Mr_and_Mrs_D that's bad if the tested object is an iterator that's iterated over afterwards (it will be 1 item short since it's position can't be reset), creating garbage generators doesn't iterate over the object as they're not iterated over, though I'm not certain that it will 100% raise a TypeError if not iterable. If you really don't want strings to be treated as collections, you will just have to check to see if you are dealing with an instance of a string. This shortfall of the is operator is fixed in the next approach - using the isinstance() function. On point 4 and 5: iter checks for an iterator when it calls __iter__: When iter(o) is called for an object o, iter will make sure that the return value of __iter__, if the method is present, is an iterator. Based on that my conclusion is that nowadays this is the best approach: The above has been recommended already earlier, but the general consensus has been that using iter() would be better: We've used iter() in our code as well for this purpose, but I've lately started to get more and more annoyed by objects which only have __getitem__ being considered iterable. A working try: statement is really fast. If you compare the type() result of any list sub-type, with the list class, it'll return False, even though the variable is-a list, although, a sub-class of it. When an iterable object is passed as an argument to the built-in function iter(), it returns an iterator for the object. In order to follow along, you need an understanding of what happens when you employ a for loop in Python. Advantages (none of the other solutions has all three): According to the Python 2 Glossary, iterables are. Then you can just check if the type is list: or whatever type you want to check against. In Python type checking is done using the type() function. Type checking is the process of determining what data type a variable contains. Python then calls next on the iterator until StopIteration is raised. I don't know if someone already posted this. How to check if an object is iterable in Python? If you expect many exceptions, if can be faster. Why is "1000000000000000 in range(1000000000000001)" so fast in Python 3? This is a great answer. WrappedDict does not inherit from dict, which means instances won't have an __iter__ method. (and since this is standard, it affects C objects as well), This will say yes to all manner of iterable objects, but it will say no to strings in Python 2. What happens if I accidentally ground the output of an LDO regulator? This is why looping over a BasicIterable with a for loop works as expected: Here's another example in order to drive home the concept of how the iterator returned by iter tries to access items by index. In Python, a good practice is to "try and see" instead of "checking". Is series data structure in python an iterable? Of course, given the general coding style for Python based on the fact that it's Easier to ask for forgiveness than permission., the general expectation is to use. If an object o implements both __iter__ and __getitem__, iter(o) will call __iter__. Just because a code is taken from NumPy doesn't mean it's good pattern or not, the only time catching everything should be done is if you're explicitly error handling inside your program. @willem: Please use timeit to perform a benchmark. It looks like this module may be what you're looking for: https://docs.python.org/3/library/collections.abc.html. So, if you just expect an iterable, iterate over it and forget it. Seems like a "duh" kind of thing. Quoting directly from the book: As of Python 3.4, the most accurate way to check whether an object x is iterable is to call iter(x) and handle a TypeError exception if it isnt. (in python 3 it doesn't matter what you use for defining the function, def has roughly the same speed as lambda). Thanks to @LuisMasuelli for noticing it will also let you down on a buggy __iter__. Refer to this answer instead. However, it is important to note that b does not have the __iter__ attribute and is not considered an instance of Iterable or Sequence: This is why Fluent Python by Luciano Ramalho recommends calling iter and handling the potential TypeError as the most accurate way to check whether an object is iterable. An iterator is any object which implements a __next__ (or next in Python 2) method and an __iter__ method. an iterator that tries to fetch items from o by integer index, starting at index 0. How to check if an object is a generator object in python? All of this happens implicitly, but the following demonstration makes it visible: On point 1 and 2: getting an iterator and unreliable checks. Nice, but why not use the collections module as proposed in. How to determine a Python variable's type? On the contrary, if the __iter__ method is available Python will automatically recognize object of that class as being Iterable. Why had climate change not been proven beyond doubt for so long? It should never have been added. If a creature's best food source was 4,000 feet above it, and only rarely fell from that height, how would it evolve to eat that food? That is to say, it's used to check if two objects refer to the same location in memory. I'm not 100% sure if this solution works for all objects, maybe other can give a some more background on it. But I didn't found any object that contains __trunc__ together with __iter__ or __getitem__. Technically, during iteration your computation might throw a. There is no sanity check I'd like to shed a little bit more light on the interplay of iter, __iter__ and __getitem__ and what happens behind the curtains. Instead, you now have BOTH versions in your answer. open api send array -swagger code example, spring.jpa.hibernate.ddl-auto create table code example, laravel authenticate not user code example, vim select first line last line code example, javascript intervet first and last element from array code example, update not working windows 10 code example, Pandas how to find column contains a certain value, Recommended way to install multiple Python versions on Ubuntu 20.04, Build super fast web scraper with Python x100 than BeautifulSoup, How to convert a SQL query result to a Pandas DataFrame in Python, How to write a Pandas DataFrame to a .csv file in Python. strings in Python 2. Not really "correct" but can serve as quick check of most common types like strings, tuples, floats, etc Kinda late to the party but I asked myself this question and saw this then thought of an answer. Since Python 3.5 you can use the typing module from the standard library for type related things: This isn't sufficient: the object returned by __iter__ must implement the iteration protocol (i.e. For example: Subreddit for posting questions and asking for general advice about your python code. if it's not iterable returns False. If an object o implements only __getitem__, but not __iter__, iter(o) will construct In the most general sense, there's no way to check whether the iterator returned by iter is sane other than to try it out. rev2022.7.21.42639. (Note that writing type(my_generator_expression) == generator would throw a NameError. hasattr(x, '__iter__') approach will say yes to strings in Python 3 and no in Python 2 (no matter whether '' or b'' or u''). So, if we compare the results of the type() function on our variable with the list class, it'll return True if our variable is a list. The above code reports it being iterable but actually trying to iterate it causes an AttributeError (tested with Faker 4.0.2): If we'd use insinstance(), we wouldn't accidentally consider Faker instances (or any other objects having only __getitem__) to be iterable: Earlier answers commented that using iter() is safer as the old way to implement iteration in Python was based on __getitem__ and the isinstance() approach wouldn't detect that. unfortunately not all iterable objects use. type() accepts three arguments, the first is required and the last two are optional. If we can make a generator that iterates over it (but never use the generator so it doesn't take up space), it's iterable. I don't know the answer, but you can either implement the function I (and other users) gave, or just catch the exception in your code (your implementation in that part will be like the function I wrote - just ensure you isolate the iterator creation from the rest of the code so you can capture the exception and distinguish it from another TypeError. Yeah. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. (Now incorporates Alfe's suggested simplification): so you can test if any object is iterable in the very readable form, as you would do with thecallable function, EDIT: if you have numpy installed, you can simply do: from numpy import iterable, Does Python have a ternary conditional operator? To use the Python type() function, pass the variable to evaluate as the first argument: Below is a list of all the data types available in Python: A common example of type checking in Python is to evaluate the output of the type() function with an if condition. But you are right. However, this can be done in a line, and adding a simple or expression checking for generators would fix this problem. Use them if that's what you want. which is simply something like. Don't run checks to see if your duck really is a duck to see if it is iterable or not, treat it as if it was and complain if it wasn't. Pythonic programming style that determines an object's type by inspection of its method or attribute signature rather than by explicit relationship to some type object ("If it looks like a duck and quacks like a duck, it must be a duck.") Why does hashing a password result in different hashes, each time? The built-in type() function can be used to return the data type of an object. Is there a method like isiterable? Python is a dynamically typed language, and the variable data types are inferred without explicit intervention by the developer. Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, From "Fluent Python" by Luciano Ramalho: As of Python 3.4, the most accurate way to check whether an object x is iterable is to call iter(x) and handle a TypeError exception if it isnt. You can now choose to sort by Trending, which boosts votes that have happened recently, helping to surface more up-to-date answers. You might ask yourself why most builtin sequences like list implement an __iter__ method when __getitem__ would be sufficient. next method). But since Python 2.6 and 3.0 you can leverage the new ABC (abstract base class) infrastructure along with some builtin ABCs which are available in the collections module: Now, whether this is desirable or actually works, is just a matter of conventions. The Collatz Conjecture is a notorious conjecture in mathematics. [x for x in obj]) to check if it's iterable may induce significant performance penalties for large iterables (especially if you just need the first few elements of the iterable, for example) and should be avoided, It is irrelevant the distinction whether the object is not iterable, or a buggy. But I am not sure how fool-proof this is. Using. ), (This makes it useful for checking if you can call len on the object though.). Most user defined iterables implement iter and getitem but not len. The function takes two arguments - the variable we're checking the type for, and the type we're looking for. The only reliable way to determine whether an object In that situation, asking forgiveness may lead to obfuscode, and it's better to ask permission first.). Would it be worth to add a note to that last bit, noting that Python 2 isn't actively being supported by the devs anymore, and shouldn't be used for new code if Python 3 is an option? See the relevant section in the documentation. On the other hand, if you need to do different things depending on input type, you might find the ABC infrastructure pretty useful. Let's create a Dictionary, Tuple and List and use the type() function to check if a variable is a list or not: Now, to alter code flow programatically, based on the results of this function: The is operator is used to compare identities in Python. So if you have few exceptions, try-except is fast. Iterating over an instance of BasicIterable works as expected: Python surely it's easier to do hasattr(obj,'__call__') even if it is slower. You want hasattr(x,"__iter__") but you don't want isinstance(x,str) hence: /u/kurashu89 has the better answer since it includes bytes and bytesarray plus uses the more appropriate Sequence definition but the above works fine so long as you understand it would return True for any iterable solely except str. he doesn't provide working code, let alone talk about python performance although this answer was really just for convenience like I've seen done numerous times on here. US to Canada by car with an enhanced driver's license, no passport? keras conda They can take a slightly shorter path through the interpreter. However, it does not catch user-defined iterables that do not implement it, nor do generator expressions, which iter can deal with. Calling iter() over an object can be an expensive operation (see DataLoader in Pytorch, which forks/spawns multiple processes on iter()). If we had code that needed a list but lacked type hints, which are optional, how can we avoid errors if the variable used is not a list? Why do you need to determine if a variable is iterable in the first place? if an object only implements __getitem__. "Selected/commanded," "indicated," what's the third word? Catching everything is a bad pattern. As you can see, you can register a non-iterable object as Iterable - and it will raise an exception at runtime. Just found a pretty weird corner case in which, @willem: or "don't ask for permission but for forgiveness" ;-), @willem Both "permission" and "forgiveness" styles qualify as duck typing. What are the "disks" seen on the walls of some NASA space shuttles? How did this note help previous owner of this old film camera? Note that constructing an iterator from FailIterIterable instances fails immediately, while constructing an iterator from FailGetItemIterable succeeds, but will throw an Exception on the first call to __next__. The Best Machine Learning Libraries in Python, Guide to Sending HTTP Requests in Python with urllib3, # Checks if the variable "a_list" is a list, # Checks if the variable "a_string" is a list, Check if Variable is a List with is Operator, Check if Variable is a List with isinstance().