Three options:
- You could sum the nested lists; - sum()takes a second argument, a starting value, set that to an empty list:
 - >>> sum(myList[0], [])
[1, 2, 3, 4, 5, 6, 7, 8, 9]
 - This works because - sum()is essentially implemented as a loop:
 -  def sum(values, start=0):
     total = start
     for value in values:
         total += value
     return total
 - which works with list concatenation, provided the start value is a list object itself. - 0 + [1, 2, 3]would not work, but- [] + [1, 2, 3]works just fine.
 
- You could use - reduce()with- operator.add(), which is essentially the same as- sum(), minus the requirement to give a start value:
 - from operator import add
reduce(add, myList[0])
 - operator.add()could be replaced with- lambda a, b: a + bor with- list.__add__if imports are to be avoided at all cost.
 - As the nested input list grows, - operator.iadd()(in-place add, for lists the equivalent of- list.extend()) will rapidly become a faster option:
 - from operator import iadd
reduce(add, myList[0], [])
 - but this does need an empty list to start with. 
- You could chain the lists using - itertools.chain.from_iterable():
 - >>> from itertools import chain
>>> list(chain.from_iterable(myList[0]))
[1, 2, 3, 4, 5, 6, 7, 8, 9]
 
All three solutions require that you use indexing to remove the outermost list, although you can also pass the one element in myList as a single argument to chain.from_iterable() with list(chain.from_iterable(*myList)) as well.
Of these options, reduce(add, ...) is the fastest:
>>> timeit.timeit("sum(myList[0], [])", 'from __main__ import myList')
1.2761731147766113
>>> timeit.timeit("reduce(add, myList[0])", 'from __main__ import myList; from operator import add')
1.0545191764831543
>>> timeit.timeit("reduce(lambda a, b: a.extend(b) or a, myList[0], [])", 'from __main__ import myList')
2.225532054901123
>>> timeit.timeit("list(chain.from_iterable(myList[0]))", 'from __main__ import myList; from itertools import chain')
2.0208170413970947
and comparing iadd versus add:
>>> timeit.timeit("reduce(add, myList[0])", 'from __main__ import myList; from operator import add')
0.9298770427703857
>>> timeit.timeit("reduce(iadd, myList[0], [])", 'from __main__ import myList; from operator import iadd')
1.178157091140747
>>> timeit.timeit("reduce(add, myListDoubled)", 'from __main__ import myList; myListDoubled = myList[0] + myList[0]; from operator import add')
2.3597090244293213
>>> timeit.timeit("reduce(iadd, myListDoubled, [])", 'from __main__ import myList; myListDoubled = myList[0] + myList[0]; from operator import iadd')
1.730151891708374
You could use recursion to avoid using a loop, to make this work for arbitrarily nested lists:
def flatten(lst):
    try:
        return flatten(sum(lst, []))
    except TypeError:
        return lst
Demo:
>>> flatten(myList)
[1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> flatten(myList + myList)
[1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9]