- Python 3 - dictionary haskey Method - The method haskey returns true if a given key is available in the dictionary, otherwise it returns a false.
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- A dictionary that allows multiple keys for one value ' class Container(object): '. This is used to wrap an object to avoid infinite recursion when calling my own methods from the inside. If a method sees this container, it assumes it has been called from the inside and not the user.
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Sorting HOW TO¶ Author. Andrew Dalke and Raymond Hettinger. Python lists have a built-in list.sort method that modifies the list in-place. There is also a sorted built-in function that builds a new sorted list from an iterable. In this document, we explore the various techniques for sorting data using Python.
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Description
![The The](/uploads/1/2/6/0/126094197/791105853.png)
The method has_key() returns true if a given key is available in the dictionary, otherwise it returns a false.
Syntax
Following is the syntax for has_key() method −
Parameters
- key − This is the Key to be searched in the dictionary.
Return Value
This method return true if a given key is available in the dictionary, otherwise it returns a false.
Example
The following example shows the usage of has_key() method.
When we run the above program, it produces the following result −
Fredrik Lundh | November 2006 | Originally posted to online.effbot.org
One of the things I noticed when skimming through the various reactions to my recent “with”-article is that some people seem tohave a somewhat fuzzy understanding of Python’s other block statement,the good old for-in loop statement. The with statementdidn’t introduce code blocks in Python; they’ve always been there.To rectify this, for-in probably deserves it’s own article,so here we go (but be warned that the following is a bit rough; I reservethe right to tweak it a little over the next few days).
On the surface, Python’s for-in statement is taken rightaway from Python’s predecessor ABC, where it’s described as:
In ABC, what’s called statements in Python are known as
commands, and sequences are known as
trains. (The wholelanguage is like that, by the way; lots of common mechanisms describedusing less-common names. Maybe they thought that renaming everythingwould make it easier for people to pick up the subtle details of thelanguage, instead of assuming that everything worked exactly as otherseemingly similar languages, or maybe it only makes sense if you’reDutch.)
Anyway, to take each element (item) from a train (sequence) inturn, we can simply do (using a psuedo-Python syntax):
and keep doing that until we run out of items. When we do, we’llget an IndexError exception, which tells us that it’s time tostop.
And in its simplest and original form, this is exactly what thefor-in statement does; when you write
the interpreter will simply fetch train[0] and assign it toname, and then execute the code block. It’ll then fetchtrain[1], train[2], and so on, until it gets an IndexError.
The code inside the for-in loop is executed in the samescope as the surrounding code; in the following example:
the variables train, name, and value all live inthe same namespace.
This is pretty straightforward, of course, but it immediately getsa bit more interesting once you realize that you can use customobjects as
trains. Just implement the __getitem__method, and you can control how the loop behaves. The following code:
will run the loop as long as the given condition is true, with valuesprovided by the custom train. In other words, the
do somethingpart is turned into a block of code that’s being executed under thecontrol of the custom sequence object. The above is equivalent to:
except that index is a hidden variable, and the controllingcode is placed in a separate object.
You can use this mechanism for everything from generatingsequence elements on the fly (like xrange):
and fetching data from an external source:
or from a stream:
to fetching data from some other source:
It’s more explicit in the latter examples, but in all theseexamples, the code in __getitem__ is basically treating theblock of code inside the for-in loop as an in-lined callback.
Also note how the last two examples don’t even bother to look atthe index; they just keep
callingthe for-in block untilthey run out of data. Or, less obvious, until they run out of bits inthe internal index variable.
To deal with this, and also avoid the issue with having objectsthat looks a lot as sequences, but doesn’t support random access, thefor-in statement was redesigned in Python 2.2. Instead of using the__getitem__ interface, for-in now starts bylooking for an __iter__ hook. If present, this method iscalled, and the resulting object is then used to fetch items, oneby one. This new protocol behaves like this:
where obj is an internal variable, and the next methodindicates end of data by raising the StopIterator exception,instead of IndexError. Using a custom object can looksomething like:
(Here, the MyTrain object returns itself, which means that thefor-in statement will call MyTrain’s own next method todo the actual work. In some cases, it makes more sense to use anindependent object for the iteration).
Using this mechanism, we can now rewrite the file iterator fromabove as:
and, with very little work, get an object that doesn’t supportnormal indexing, and doesn’t break down if used on a file with morethan 2 billion lines.
But what about ordinary sequences, you ask? That’s of courseeasily handled by a wrapper object, that keeps an internal counter,and maps next calls to __getitem__ calls, in exactly thesame way as the original for-in statement did. Python providesa standard implementation of such an object, iter, which isused automatically if __iter__ doesn’t exist.
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This wasn’t very difficult, was it?
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Footnote: In Python 2.2 and later, several non-sequence objectshave been extended to support the new protocol. For example, you canloop over both text files and dictionaries; the former return linesof text, the latter dictionary keys.