Develop Reference

How can I pass each element of a set to a function?

I have a set with multiple tuples: set1 = {(1,1),(2,1)} for example.
Now I want to pass each tuple of the set to a method with this signature: process_tuple(self, tuple).
I am doing it with a for loop like this:
for tuple in set1:
process_tuple(tuple)
Is there a better way to do it?

Your question is basically "how can I loop without using a loop". While it's possible to do what you're asking with out an explicit for loop, the loop is by far the clearest and best way to go.
There are some alternatives, but mostly they're just changing how the loop looks, not preventing it in the first place. If you want to collect the return values from the calls to your function in a list, you can use a list comprehension to build the list at the same time as you loop:
results = [process_tuple(tuple) for tuple in set1]
You can also do set or dict comprehensions if those seem useful to your specific needs. For example, you could build a dictionary mapping from the tuples in your set to their processed results with:
results_dict = {tuple: process_tuple(tuple) for tuple in set1}
If you don't want to write out for tuple in set1 at all, you could use the builtin map function to do the looping and passing of values for you. It returns an iterator, which you'll need to fully consume to run the function over the full input. Passing the map object to list sometimes makes sense, for instance, to convert inputs into numbers:
user_numbers = list(map(int, input("Enter space-separated integers: ").split()))
But I'd also strongly encourage you to think of your current code as perhaps the best solution. Just because you can change it to something else, doesn't mean you should.

Compare whether the first two elements on a nested list are equal to a comparison list in python

In python 2.7, I would like to verify whether a subset list of elements is included in a longer nested list when comparing let's say only the first two elements.
Lets say we have a big list of nested elements (this big_list will have over 10k elements so looping for every comparison is very inefficient and I'd like to avoid this). For this example, lets say we only have 4 nested lists in big_list:
`
big_list = ((2,3,5,6,7), (4,5,6,7,8), (6,7,8,8), (8,4,2,7))
`
If I have a single list, let's say (4,5,11,11,11), I am looking for an operation that will return True when compared to big_list since the second list in big_list starts with (4,5,...) and matches the first two elements of my single_list. Essentially I want to know whether the first two elements of a single list (e.g. (4,5,11,11,11)) are repeated in my big list regardless of the other followed numbers (e.g. 11,11, ...).
My operation should also return False if another single_list (e.g. (4,8,11,11,11) ) does not match the first two element in the big_list.
I hope this is clearer. Any help?
Thanks in advance,

Since you have a huge list, to avoid iterating over the whole thing every time — O(n) time complexity for each search, you can do a constant time lookup using a set.
tup_truth_set = set([tup[:2] for tup in big_list]) # set with first two letters of interest
then you would simply do something like this to check in constant time:
tuple_of_interest[:2] in tup_truth_set

I don't think that you can avoid the loop over your list. Even if you don't run the loop yourself and suppose there is a built-in function, that I am not aware of and can do what you are asking, I am pretty sure it would loop the list in the background. So I suggest a single line of code to do that, including a loop, obviously.
(4,5,11,11,11)[:2] in [i[:2] for i in big_list]

Python : Adding data to list

I am learning lists and trying to create a list and add data to it.
mylist=[]
mylist[0]="hello"
This generates Error.
Why cant we add members to lists like this, like we do with arrays in javascript.
Since these are also dynamic and we can add as many members and of any data type to it.
In javascript this works:
var ar=[];
ar[0]=333;
Why this dosent work in Python and we only use append() to add to list.

mylist[0] = 'hello' is syntactic sugar for mylist.__setitem__(0, 'hello').
As per the docs for object.__setitem__(self, key, value):
The same exceptions should be raised for improper key values as for
the __getitem__() method.
The docs for __getitem__ states specifically what leads to IndexError:
if value outside the set of indexes for the sequence (after any
special interpretation of negative values), IndexError should be
raised.
As to the purpose behind this design decision, one can write several chapters to explain why list has been designed in this way. You should familiarise yourself with Python list indexing and slicing before making judgements on its utility.

Lists in Python are fundamentally different to arrays in languages like C. You do not create a list of a fixed size and assign elements to indexes in it. Instead you either create an empty list and append elements to it, or use a list-comprehension to generate a list from a type of expression.
In your case, you want to add to the end, so you must use the .append method:
mylist.append('hello')
#["hello"]
And an example of a list comprehension:
squares = [x**2 for x in range(10)]
#[1,4,9,16,25,36,49,64,81,100]

Finding intersections of huge sets with huge dicts

I have a dict with 50,000,000 keys (strings) mapped to a count of that key (which is a subset of one with billions).
I also have a series of objects with a class set member containing a few thousand strings that may or may not be in the dict keys.
I need the fastest way to find the intersection of each of these sets.
Right now, I do it like this code snippet below:
for block in self.blocks:
#a block is a python object containing the set in the thousands range
#block.get_kmers() returns the set
count = sum([kmerCounts[x] for x in block.get_kmers().intersection(kmerCounts)])
#kmerCounts is the dict mapping millions of strings to ints
From my tests so far, this takes about 15 seconds per iteration. Since I have around 20,000 of these blocks, I am looking at half a week just to do this. And that is for the 50,000,000 items, not the billions I need to handle...
(And yes I should probably do this in another language, but I also need it done fast and I am not very good at non-python languages).

There's no need to do a full intersection, you just want the matching elements from the big dictionary if they exist. If an element doesn't exist you can substitute 0 and there will be no effect on the sum. There's also no need to convert the input of sum to a list.
count = sum(kmerCounts.get(x, 0) for x in block.get_kmers())

Remove the square brackets around your list comprehension to turn it into a generator expression:
sum(kmerCounts[x] for x in block.get_kmers().intersection(kmerCounts))
That will save you some time and some memory, which may in turn reduce swapping, if you're experiencing that.
There is a lower bound to how much you can optimize here. Switching to another language may ultimately be your only option.

I have single-element arrays. How do I change them into the elements themselves?

Importing a JSON document into a pandas dataframe using records = pandas.read_json(path), where path was a pre-defined path to the JSON document, I discovered that the content of certain columns of the resulting dataframe "records" are not simply strings as expected. Instead, each "cell" in such a column is an array, containing one single element -- the string of interest. This makes selecting columns using boolean indexing difficult. For example, records[records['category']=='Python Books'] in Ipython outputs an empty dataframe; had the "cells" contained strings instead of arrays of strings, the output would have been nonempty, containing rows that correspond to python books.
I could modify the JSON document, so that "records" reads the strings in properly. But is there a way to modify "records" directly, to somehow strip the single-element arrays into the elements themselves?

Update: After clarification, I believe this might accomplish what you want while limiting it to a single iteration over the data:
nested_column_1 = records["column_name_1"]
nested_column_2 = records["column_name_2"]
clean_column_1 = []
clean_column_2 = []
for i in range(0, len(records.index):
clean_column_1.append(nested_column_1[i][0])
clean_column_2.append(nested_column_2[i][0])
Then you convert the clean_column lists to Series like you mentioned in your comment. Obviously, you make as many nested_column and clean_column lists as you need, and update them all in the loop.
You could generalize this pretty easily by keeping a record of "problem" columns and using that to create a data structure to manage the nested/clean lists, rather than declaring them explicitly as I did in my example. But I thought this might illustrate the approach more clearly.
Obviously, this assumes that all columns have the same number of elements, which maybe isn't a a valid assertion in your case.
Original Answer:
Sorry if I'm oversimplifying or misunderstanding the problem, but could you just do something like this?
simplified_list = [element[0] for element in my_array_of_arrays]
Or if you don't need the whole thing at once, just a generator instead:
simplifying_generator = (element[0] for element in my_array_of_arrays)