Can iterators be reset in Python?

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Can I reset an iterator / generator in Python? I am using DictReader and would like to reset it to the beginning of the file.

I see many answers suggesting itertools.tee, but that's ignoring one crucial warning in the docs for it:

This itertool may require significant auxiliary storage (depending on how much temporary data needs to be stored). In general, if one iterator uses most or all of the data before another iterator starts, it is faster to use list() instead of tee().

Basically, tee is designed for those situation where two (or more) clones of one iterator, while "getting out of sync" with each other, don't do so by much -- rather, they say in the same "vicinity" (a few items behind or ahead of each other). Not suitable for the OP's problem of "redo from the start".

L = list(DictReader(...)) on the other hand is perfectly suitable, as long as the list of dicts can fit comfortably in memory. A new "iterator from the start" (very lightweight and low-overhead) can be made at any time with iter(L), and used in part or in whole without affecting new or existing ones; other access patterns are also easily available.

As several answers rightly remarked, in the specific case of csv you can also .seek(0) the underlying file object (a rather special case). I'm not sure that's documented and guaranteed, though it does currently work; it would probably be worth considering only for truly huge csv files, in which the list I recommmend as the general approach would have too large a memory footprint.

Can iterators be reset in Python?, Can I reset an iterator generator in Python I am using DictReader and would like to reset it from the csv module to the beginning of t Python iterators normally can’t be “reset”—once they’re exhausted they’re supposed to raise StopIteration every time next () is called on them. To iterate anew you’ll need to request a fresh iterator object with the iter () function.

If you have a csv file named 'blah.csv' That looks like


you know that you can open the file for reading, and create a DictReader with

blah = open('blah.csv', 'r')
reader= csv.DictReader(blah)

Then, you will be able to get the next line with, which should output


using it again will produce


However, at this point if you use, the next time you call you will get



This seems to be the functionality you're looking for. I'm sure there are some tricks associated with this approach that I'm not aware of however. @Brian suggested simply creating another DictReader. This won't work if you're first reader is half way through reading the file, as your new reader will have unexpected keys and values from wherever you are in the file.

Can iterators be reset in Python?, protocol, which consist of the methods __iter__() and __next__() . Inverted iterator: reversed() will return an iterator that is accessed in reverse order. iterator modules provided in python: itertools module. Using Python iter() – A simple Example. Let’s look at a few examples of iterators. You can try them in the Python interactive shell. Note that for Python 3 you need __next__() instead of next().

No. Python's iterator protocol is very simple, and only provides one single method (.next() or __next__()), and no method to reset an iterator in general.

The common pattern is to instead create a new iterator using the same procedure again.

If you want to "save off" an iterator so that you can go back to its beginning, you may also fork the iterator by using itertools.tee

Python Iterators, What is the difference between generator and iterator in python? An iterable is an object that can be iterated through. For example, given this syntax: for x in list: pass In this case, list is the iterable and x is the loop counter. It is important to distinguish iterable from iterator; the latter refers to a different type of object in Python.

Yes, if you use numpy.nditer to build your iterator.

>>> lst = [1,2,3,4,5]
>>> itr = numpy.nditer([lst])
>>> itr.finished
>>> itr.reset()

Python Iterators, The same effect can be achieved in Python by combining map() and count() to form map(f, Make an iterator that returns elements from the first iterable until it is  As you have learned in the Python Classes/Objects chapter, all classes have a function called __init__(), which allows you to do some initializing when the object is being created. The __iter__() method acts similar, you can do operations (initializing etc.), but must always return the iterator object itself.

There's a bug in using .seek(0) as advocated by Alex Martelli and Wilduck above, namely that the next call to .next() will give you a dictionary of your header row in the form of {key1:key1, key2:key2, ...}. The work around is to follow with a call to to get rid of the header row.

So your code would look something like this:

f_in = open('myfile.csv','r')
reader = csv.DictReader(f_in)

for record in reader:
    if some_condition:
        # reset reader to first row of data on 2nd line of file

What's the difference between iterators and generators in Python , I would define instead a class that obeys the iterator protocol, that is to that reset function to the generator so i can modify its state. if thinking  In this Python Programming Tutorial for Beginners video I am going to show you How to use Iterators in Python . Iterators are the objects which can be iterat

9.1. itertools, Iterators are objects that can be iterated over like we do in a for loop. We can also There is no reset, but it's possible to create another generator. This can be  Iterator in Python is simply an object that can be iterated upon. An object which will return data, one element at a time. An object which will return data, one element at a time. Technically speaking, a Python iterator object must implement two special methods, __iter__() and __next__() , collectively called the iterator protocol .

resetting a generator, They are iterable containers which you can get an iterator from. All these objects have a iter() method which is used to get an iterator: Example. Return an iterator​  The first few exercises include an excuse to create your own Python iterator. Practice working with iterators. You don’t learn new Python skills by reading, you learn them by writing code. If you’d like to practice working with iterators, you can sign up for Python Morsels using the form below. The first exercise I send you will involve

Python Tutorial: Generators, Hi, I would like to know how to reinitialize/reset a generator. I mean is one of the reasons people use generators and iterators in the first place. Generators come from python, and I found a similar question at stackoverflow:. It does the iterating over an iterable. You can use an iterator to get the next value or to loop over it. Once, you loop over an iterator, there are no more stream values. Iterators use the lazy evaluation approach. Many built-in classes in Python are iterators. A generator function is a function which returns an iterator.

  • Possible duplicate of Reseting generator object in Python
  • Using list() to cache multipassage over a csvreader on a 5MB file sees my runtime go from ~12secs to ~0.5s.
  • This was what my theory told me, nice to see that what I thought should happen, does.
  • @Wilduck: the behavior you're describing with another instance of DictReader won't happen if you make a new file handle and pass that to the second DictReader, right?
  • If you have two file handlers they will behave independently, yes.
  • While you're analysis of the .next() method is probably correct, there is a fairly simple way to get what the op is asking for.
  • @Wilduck: I see that your answer. I just answered the iterator question, and I have no idea about the csv module. Hopefully both answers are useful to the original poster.
  • Strictly, the iterator protocol also requires __iter__. That is, iterators are required also to be iterables.
  • Can nditer cycle through the array like itertools.cycle?
  • @LWZ: I don't think so, but you can try: the next() and on a StopIteration exception do a reset().
  • ...followed by a next()
  • This is what I was looking for !
  • Note that the limit of "operands" here is 32:…