To create alist of items, use the [ ]
genes = ['SOD1','CDC11','YFG1']
print(genes)
print(genes[1])
print(genes[1:]) # everything after slot 1 (incl 1)
print(genes[:1]) # everything before slot 1
print(len(genes))
['SOD1', 'CDC11', 'YFG1']
CDC11
['CDC11', 'YFG1']
['SOD1']
3
Can also use negative numbers to start count from the back.
>>>print(genes[-1])
YFG
Python also includes a data type for sets. A set is an unordered collection with no duplicate elements. Basic uses include membership testing and eliminating duplicate entries. Set objects also support mathematical operations like union, intersection, difference, and symmetric difference.
>>> basket = {'apple', 'orange', 'apple', 'pear', 'orange', 'banana'}
>>> print(basket) # show that duplicates have been removed
{'orange', 'banana', 'pear', 'apple'}
>>> 'orange' in basket # fast membership testing
True
>>> 'crabgrass' in basket
False
>>> # Demonstrate set operations on unique letters from two words
...
>>> a = set('abracadabra')
>>> b = set('alacazam')
>>> a # unique letters in a
{'a', 'r', 'b', 'c', 'd'}
>>> a - b # letters in a but not in b
{'r', 'd', 'b'}
>>> a | b # letters in a or b or both
{'a', 'c', 'r', 'd', 'b', 'm', 'z', 'l'}
>>> a & b # letters in both a and b
{'a', 'c'}
>>> a ^ b # letters in a or b but not both
{'r', 'd', 'b', 'm', 'z', 'l'}
>>> a = {x for x in 'abracadabra' if x not in 'abc'}
>>> a
{'r', 'd'}
>>> range(5,10,1)
[5, 6, 7, 8, 9]
>>> range(5,-1,-1)
[5, 4, 3, 2, 1, 0]
l = [ 'a', 100, 12/3.3 ]
# ",".join(l) # this throws an error
";".join(map(str,l))) # have to cast numbers as string
print( ";".join(map(str,l)))
l = [1,2,3,4]
squares = map(lambda x: x**2,l)
print(squares)
['a', 100, 3.6363636363636367]
[1, 2, 3, 4]
[1, 4, 9, 16]
l = ['zzz','yyy','a']
print(list(reversed(l)))
for n in reversed(l):
print(n)
['a', 'yyy', 'zzz']
a
yyy
zzz
See more details here https://docs.python.org/3/tutorial/datastructures.html
list.append(x) - Add an item to the end of the list;list.pop([i]) - Remove the item at the given position in thelist.extend(L) - Extend the list by appending all the items in the given list;list.insert(i, x) - Insert an item at a given position. The first argument is the index of the element before which to insert, so a.insert(0, x) inserts at the front of the list, and a.insert(len(a), x) is equivalent to a.append(x).list.remove(x) - Remove the first item from the list whose value is x. It is an error if there is no such item.
list, and return it. If no index is specified, a.pop() removes
and returns the last item in the list.list.index(x) - Return the index in the list of the first item whose value is x. It is an error if there is no such item.list.count(x) - Return the number of times x appears in the list.list.sort(cmp=None, key=None, reverse=False) - Sort the items of the list in placelist.reverse() - Reverse the order of the items in the listThe LIST.sort() function on a list or the sorted(LIST)
https://docs.python.org/3/howto/sorting.html
#!/usr/bin/env python3
genes = ['SOD1','CDC11','YFG1']
print(genes)
sort_genes = sorted(genes)
print(sort_genes)
numbers = [141, 7, 90, 3, 13]
print("unsorted",numbers)
numbers.sort()
print("sorted",numbers)
print("reversed",sorted(numbers,reverse=True))
alphanumbers = ['141', '7', '90', '3', '13']
print("Alphanumeric strings",alphanumbers)
print("Alpha sorted numbers",sorted(alphanumbers))
print("Numberic sorted",sorted(alphanumbers,key=int))
See https://docs.python.org/3/library/datetime.html
from datetime import datetime
dates = ['3-Jan-2016', '4-Mar-2015', '2-Aug-1999', '1-May-2000']
print(dates)
dates.sort()
print(dates)
#newdates = [ datetime.strptime(d,"%d-%b-%Y") for d in dates ]
newdates = []
for str in dates:
newdates.append(datetime.strptime(str,'%d-%b-%Y'))
print(newdates)
newdates.sort()
print(newdates)
for n in newdates:
print(datetime.strftime(n,"%Y-%b-%d")," OR ",
datetime.strftime(n,"%Y-%m-%d"), " OR ",
datetime.strftime(n,"%A, %b %d, %Y"), " OR ",
datetime.strftime(n,"%c")
)
lst = [ 'BRCA1','SOD1','PTEN']
for gene in sorted(lst):
print("gene is",gene)
DNA='AAAACCGTAG'
for let in DNA:
print(let)
for let in reversed(DNA):
print(let)
BRCA1
PTEN
SOD1
A
A
A
...
G
A
T
...
Dictionaries allow storing of data associated with a key instead of as an ordered list.
Initialize a dictionary, Dictionaries are key and value pairs
things = {} # an empty dictionary
listofstuff = [] # an empty array
print(things)
things = {'diane': 10, 'jack': 13}
print(things)
things['diane']
things['billy'] = 15 # assign a new key/value pair
# if you have a list of pairs of things
strangerthings = dict([('Will', 12), ('Jim', 44), ('Joyce', 45), ('Eleven',11),('Lucas',10)])
strangerthings['Eleven']
{}
{'diane': 10, 'jack': 13}
10
11
Using the for loop and the items() function
for key,value in strangerthings.items():
print("key is", key,"value is",value)
key is Will value is 12
key is Jim value is 44
key is Joyce value is 45
key is Eleven value is 11
key is Lucas value is 10
It is often the case you make a dictionary of values and you have another list and you want to cross-reference it. But maybe not all the values are in your dictionary.
set1 = {'a': 'apple', 'b': 'bear'}
if 'a' in set1:
print("a is in set1")
if 'z' in set1:
print("z is in set1")
These are blocks of code that can be called repeatedly. Simplify tool development.
Might have subroutine to read a sequence file. Or compute a statistic.
Uses indentation just like loops.
def ROUTINENAME(ARGUMENTS):
CODE HERE
These can be used to run a routine that you might do repeatedly.
def average(list):
count=0
sum = 0.0
for item in list:
count += 1
sum += item
return sum / count
print(average([100,200,300,150,110,99]))
https://drj11.wordpress.com/2010/02/22/python-getting-fasta-with-itertools-groupby/
See https://github.com/biodataprog/code_templates/blob/master/Lists_Dictionaries/fasta_parser.py
import itertools
import sys
import re
# based on post here
# https://drj11.wordpress.com/2010/02/22/python-getting-fasta-with-itertools-groupby/
# define what a header looks like in FASTA format
def isheader(line):
return line[0] == '>'
# this function reads in fasta file and returns pairs of data
# where the first item is the ID and the second is the sequence
# it isn't that efficient as it reads it all into memory
# but this is good enough for our project
def aspairs(f):
seq_id = ''
sequence = ''
for header,group in itertools.groupby(f, isheader):
if header:
line = next(group)
seq_id = line[1:].split()[0]
else:
sequence = ''.join(line.strip() for line in group)
yield seq_id, sequence
# here is my program
# get the filename from the cmdline
filename = sys.argv[1]
with open(filename,"r") as f:
seqs = dict(aspairs(f))
# iterate through the sequences
n=0
for k,v in seqs.items():
print( "id is ",k,"seq is",v)
n += 1
print(n,"sequences")
id is Q0142 seq is MTGSGTPPSREVNTYYMTMTMTMTMIMIMTMTMNIHFNNNNNNNINMNSRRMYLFIL*M
id is Q0143 seq is MGLWISFGTPPSYTYLLIMNHKLLLINNNNLTEVHTYFNININIDKMYIH*
Dictionaries are useful ways to generate a unqiue list
dna = 'AAGAGAGGATACA'
bases = {'A':0, 'C':0, 'G':0, 'T':0 }
for l in dna:
bases[l] += 1
print(bases)
{'A': 7, 'C': 1, 'G': 4, 'T': 1}