I apologize if this is a silly question, but I have been trying to teach myself how to use BeautifulSoup so that I can create a few projects. This will print the output in sorted order by values in ascending order. But for academic purposes, the question’s example is just fine. Many people have already explained about import vs from, so I want to try to explain a bit more under the hood, where the actual difference lies. Python doesn’t really have ++ and –, and I personally never felt it was such a loss. The annotations are not used in any way by Python itself, it pretty much populates and ignores them.
Deleting items in dictionary
Let’s pretend you want to live in the immutable world and do not want to modify the original but want to create a new dict that is the result of adding a new key to the original. For adding a single key, the accepted answer has less computational overhead. If the word key is just a variable, as you have mentioned then the main thing to note is that when you run a ‘FOR LOOP’ over a dictionary it runs through only the ‘keys’ and ignores the ‘values’. In ..-syntax, it always iterates over the keys (the values are accessible using dictionarykey). If you want the 2.x behavior in 3.x, you can call list(d.items()). In Python 3.x, iteritems() was replaced with simply items(), which returns a set-like view backed by the dict, like iteritems() but even better.
- I faced the same issue with Ubuntu 20.4 and have tried many solutions but nothing worked out.
- But for a more complicated loop you may want to flatten it by iterating over a well-named generator expression and/or calling out to a well-named function.
- If the word key is just a variable, as you have mentioned then the main thing to note is that when you run a ‘FOR LOOP’ over a dictionary it runs through only the ‘keys’ and ignores the ‘values’.
- Doing the Pythonic thing, that is, using the language in the way it was intended to be used, usually is both more readable and computationally efficient.
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- Once an iterator raises StopIteration it will always raise it – if you want to iterate again, you need a new one.
- If you want the 2.x behavior in 3.x, you can call list(d.items()).
- In addition, this kind of increments are not widely used in python code because python have a strong implementation of the iterator pattern plus the function enumerate.
- Simply put, the ++ and — operators don’t exist in Python because they wouldn’t be operators, they would have to be statements.
- Yes it is possible, and it does have a method that implements this, but you don’t want to use it directly.
Take a look at Behaviour of increment and decrement operators in Python for an explanation of why this doesn’t work. The left part may be false, but the right part is true (Python has “truth-y” and “fals-y” values), so the check always succeeds. But for Python (how Jim Fasarakis Hilliard said) the return type it’s just an hint, so it’s suggest the return but allow anyway to return other type like a string.. This hasn’t been actually implemented as of 3.6 as far as I can tell so it might get bumped to future versions. This is especially useful if you need to make comparisons in a setting where a function is expected.
However, there are some fun (esoteric) facts that can be derived from this grammar statement. This means the type of result the function returns, but it can be None. For it to effectively describe that function f returns an object of type int. Connect and share knowledge within a single location that is structured and easy to search.
Note the differences in brace usage and assignment operator. To translate this pseudocode into Python you would need to know the data structures being referenced, and a bit more of the algorithm implementation. Find centralized, trusted content and collaborate around the technologies you use most. Note that with this approach, your key will need to follow the rules of valid identifier names in Python. Yes it is possible, and it does have a method that implements this, but you don’t want to use it directly. I’m not sure why, but this enviroment variable was never set.
Check if a key is already in dictionary
Doing the Pythonic thing, that is, using the language in the way it was intended to be used, usually is both more readable and computationally efficient. It would create a runtime error because you are changing the keys while the program is running. If you are absolutely set on reducing time, use the for key in my_dict way, but you have been warned.
In this particular case with urllib package, the second way import urllib.request and use of urllib.request is how standard library uniformly uses it. This makes all names from the module available in the local namespace. First of all, let me explain exactly what the basic import statements do. However the absence of this operator is in the python philosophy increases consistency and avoids implicitness.
Creating a dictionary with initial values
But for a more complicated loop you may want to flatten it by iterating over a well-named generator expression and/or calling out to a well-named function. Trying to fit everything on one line is rarely “Pythonic”. However, if you’d like to add, for example, thousands of new key-value pairs, you should consider using the update() method. So we see that using the subscript notation is actually much faster than using __setitem__.
I faced the same issue with Ubuntu 20.4 and have tried many solutions but nothing worked out. Even after update and upgrade, the openssl version showed OpenSSL 1.1.1h 22 Sep 2020. But in my windows system, where the code works without any issue, openssl version is OpenSSL 1.1.1k 25 Mar 2021.
What does -> mean in Python function definitions?
And because integers are immutable, the only way to ‘change’ a variable is by reassigning it. In more detail, Python 2.x has docstrings, which allow you to attach a metadata string to various types of object. This is amazingly handy, so Python 3 extends the feature by allowing you to attach metadata to functions describing their parameters and return values. This is particularly useful if you are working with dictionaries that always consist of the same data types or structures, for example a dictionary of lists.
If you want to loop over a dictionary and modify it in iteration (perhaps add/delete a key), in Python 2, it was possible by looping over my_dict.keys(). I prefer functions with clear names to operators with non-always clear semantics (hence the classic interview question about ++x vs. x++ and the difficulties of overloading it). I’ve also never been a huge fan of what post-incrementation does for readability. Simply put, the ++ and — operators don’t exist in Python because they wouldn’t be operators, they would have to be statements. All namespace modification in Python is a statement, for simplicity and consistency.
For when to use for key in dict and when it must be for key in dict.keys() see David Goodger’s Idiomatic Python article (archived copy). In Python 3, dict.iterkeys(), dict.itervalues() and dict.iteritems() are no longer supported. Use dict.keys(), dict.values() and dict.items() instead. Beside the first the others have no typing meaning; but it still is valid syntax to hide a lambda definition in the return signature of a function. There is also the strangely named, oddly behaved, and yet still handy dict.setdefault(). If you want to add a dictionary within a dictionary you can do it this way.
This is how Python knows to exit a for loop, or a list comprehension, or a generator expression, or any other iterative context. Once an iterator raises StopIteration it will always raise it – if you want to iterate again, you need a new one. Or, in other words, after you’ve run this statement, you can simplyuse a plain (unqualified) name to refer to things defined in module X.But X itself is not defined, so X.name doesn’t work. And if namewas already defined, it is replaced by the new version.
And if name in X ischanged to point to some other object, your module won’t notice. The main reason ++ comes in handy in C-like languages is for keeping track of indices. In Python, you deal with data in an abstract way and seldom increment through indices and such. The closest-in-spirit thing to ++ is the next method of iterators. There’s no preconceived use case, but the PEP suggests several.
The “advantage” is debatable, but as already stated here and cited from the The Zen of Python, “simple is better python libraries for parallel processing than complex” and “readability counts”. I claim that the concept of continue is less complex than generator expressions. If you’re not joining two dictionaries, but adding new key-value pairs to a dictionary, then using the subscript notation seems like the best way.
