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Commit bd07c60d authored by Mikael Boden's avatar Mikael Boden
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Fix_to_FASTA_header

parent a30165e5
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Showing with 1230 additions and 34 deletions
guide.py
View file @ bd07c60d
......@@ -288,7 +288,7 @@ def scoreAlignment(aln, substmat = None, gap = -1):
if gap_here:
score = gap
else:
score = substmat.get(aln.seqs[i][pos], aln.seqs[j][pos])
score = substmat.__getitem__(aln.seqs[i][pos], aln.seqs[j][pos])
if min == None:
min = score
elif min > score:
......@@ -317,7 +317,7 @@ def align(seqA, seqB, substMatrix, gap=-1):
# Calculate the optimum score at each location in the matrix, note which option that was chosen for traceback
for i in range(1, lenA + 1):
for j in range(1, lenB + 1):
match = S[i - 1, j - 1] + substMatrix.get(stringA[i - 1], stringB[j - 1])
match = S[i - 1, j - 1] + substMatrix.__getitem__(stringA[i - 1], stringB[j - 1])
delete = S[i - 1, j] + gap
insert = S[i, j - 1] + gap
Traceback[i, j] = numpy.argmax([match, delete, insert])
......@@ -382,7 +382,7 @@ class SubstMatrix():
G -1 -1 1
T -1 -1 -1 1
A C G T
>>> sm.get('C', 'T')
>>> sm.__getitem__('C', 'T')
-1
"""
def __init__(self, alphabet, scoremat = None):
......
hca.py 0 → 100644
View file @ bd07c60d
This diff is collapsed.
heap.py 0 → 100644
View file @ bd07c60d
import numpy as np
class LabelHeap:
"""
Min and max heap: data structure for keeping a list of labels, sorted by a value associated with each.
Based on max heap in Necaise, "Data structures and algorithms in Python" (Ch 13); fixed a bunch of bugs though...
"""
def __init__(self, maxsize, reverse = False):
"""
Initialise a heap.
:param maxsize: the maximum size of the heap
:param reverse: heap in descending order if true, else ascending
"""
self.reverse = reverse
self._elements = np.array([None for _ in range(maxsize)])
self._idx2val = dict()
self._count = 0
def __len__(self):
"""
The number of elements in the heap currently.
:return: the number of added elements
"""
return self._count
def __str__(self):
"""
String representation of heap. A list of labels in a binary tree (first element is the smallest/greatest value)
:return: heap as a string
"""
return str([y for y in self._elements[:self._count]])
def __repr__(self):
return self.__str__()
def capacity(self):
"""
Maximum size allocated to heap
:return: the number of elements that this heap can store
"""
return len(self._elements)
def __getitem__(self, i):
"""
Retrieve the value by tree index (index 0 is the root and contains the smallest/greatest value)
:param i: index in tree
:return: the value at this index
"""
return self._idx2val[self._elements[i]]
def add(self, label, value):
"""
Add a label with value to heap
:param label:
:param value:
"""
assert self._count < self.capacity(), "Cannot add to a full heap"
assert not label in self._idx2val, "Cannot add a duplicate label"
self._elements[self._count] = label
self._idx2val[label] = value
self._count += 1
self._siftUp(self._count - 1)
def pop(self):
"""
Pop the (label, value) pair with minimum/maximum value; removes the entry
:return: tuple with label and value
"""
assert self._count > 0, "Cannot extract from an empty heap"
label = self._elements[0]
self._count -= 1
self._elements[0] = self._elements[self._count]
self._siftDown(0)
return (label, self._idx2val[label])
def peek(self):
"""
Peek the (label, value) pair with minimum/maximum value; does not change the heap
:return: tuple with label and value
"""
assert self._count > 0, "Cannot peek in an empty heap"
return (self._elements[0], self._idx2val[self._elements[0]])
def _delete(self, i):
"""
Delete by internal, binary tree index
:param i: index
:return:
"""
assert self._count > i, "Cannot delete index" + str(i)
self._count -= 1
self._elements[i] = self._elements[self._count]
self._siftDown(i)
def _siftUp(self, i):
if i > 0:
parent = (i-1) // 2
if (self[i] > self[parent] if self.reverse else self[i] < self[parent]): # swap
tmp = self._elements[i]
self._elements[i] = self._elements[parent]
self._elements[parent] = tmp
self._siftUp(parent)
def _siftDown(self, i):
left = 2 * i + 1
right = 2 * i + 2
extremist = i
if left < self._count and (self[left] >= self[extremist] if self.reverse else self[left] <= self[extremist]):
extremist = left
if right < self._count and (self[right] >= self[extremist] if self.reverse else self[right] <= self[extremist]):
extremist = right
if extremist != i: # swap
tmp = self._elements[i]
self._elements[i] = self._elements[extremist]
self._elements[extremist] = tmp
self._siftDown(extremist)
\ No newline at end of file
ival.py
View file @ bd07c60d
......@@ -97,7 +97,7 @@ class IntervalTree:
def putAll(self, tree):
for i in tree:
self.put(i.getInterval(), tree.get(i.getInterval()))
self.put(i.getInterval(), tree.__getitem__(i.getInterval()))
def _randomizedInsert(self, node, ival, value):
if node == None: return IntervalNode(ival, value)
......
phylo.py
View file @ bd07c60d
......@@ -150,6 +150,8 @@ class PhyloNode:
A number of methods are named with a _ prefix. These can be, but
are not intended to be used from outside the class. """
_verbose = True
def __init__(self, parent = None, label=''):
""" Initialise a node.
Set its parent (another PhyloNode), parent can be None.
......@@ -183,7 +185,8 @@ class PhyloNode:
for i in range(self.nChildren()):
stubs[i] = str(self.children[i])
if self.dist or self.dist == 0.0:
dist = ':' + str(self.dist)
if self.dist == 0.0: dist = ''
else: dist = ':' + '%5.3f' % self.dist
if self.label != None:
label = str(self.label)
if self.nChildren() == 0:
......@@ -277,6 +280,7 @@ class PhyloNode:
else:
self.seqscores = [[0 if a == sym else 999999 for a in aln.alphabet] for sym in
self.sequence] # if we want to weight scores, this would need to change
if self._verbose: print('Forward:', self.label, '\n\t', self.seqscores)
return self.seqscores
def _backwardParsimony(self, aln, seq=None):
......@@ -314,6 +318,7 @@ class PhyloNode:
col += 1
for i in range(self.nChildren()):
self.children[i]._backwardParsimony(aln, sequence.Sequence(childbuf[i], aln.alphabet, self.children[i].label or "Child of "+self.label, gappy=True))
if self._verbose: print('Backward:', self.label, '\n\t', self.backptr)
return self.sequence
def getSequence(self):
......@@ -394,7 +399,6 @@ class PhyloNode:
Methods for generating a single tree by clustering, here UPGMA Zvelebil and Baum p. 278
----------------------------------------------------------------------------------------"""
def runUPGMA(aln, measure, absoluteDistances=False):
""" Generate an ultra-metric, bifurcating, rooted tree from an alignment based on pairwise distances.
Use specified distance metric (see sequence.calcDistances).
......@@ -403,6 +407,7 @@ def runUPGMA(aln, measure, absoluteDistances=False):
D = {}
N = {} # The number of sequences in each node
M = aln.calcDistances(measure) # determine all pairwise distances
print(M)
nodes = [PhyloNode(label=seq.name) for seq in aln.seqs] # construct all leaf nodes
""" For each node-pair, assign the distance between them. """
for i in range(len(nodes)):
......@@ -411,16 +416,17 @@ def runUPGMA(aln, measure, absoluteDistances=False):
N[nodes[i]] = 1 # each cluster contains a single sequence
for j in range(0, i):
D[frozenset([nodes[i], nodes[j]])] = M[i, j]
""" Now: treat each node as a cluster,
until there is only one cluster left,
find the *closest* pair of clusters, and
merge that pair into a new cluster (to replace the two that merged).
""" Treat each node as a cluster, until there is only one cluster left, find the *closest*
pair of clusters, and merge that pair into a new cluster (to replace the two that merged).
In each case, the new cluster is represented by the (phylo)node that is formed. """
while len(N) > 1: # N will contain all "live" clusters, to be reduced to a signle below
while len(N) > 1: # N will contain all "live" clusters, to be reduced to a single below
closest_pair = (None, None) # The two nodes that are closest to one another according to supplied metric
closest_dist = None # The distance between them
print(len(N), 'nodes remain')
for pair in D: # check all pairs which should be merged
dist = D[pair]
pair_as_list = list(pair)
print('Inspecting \"' + str(pair_as_list[0]) + '\" and \"' + str(pair_as_list[1]) + '\" at distance %5.3f' % D[pair])
if closest_dist == None or dist < closest_dist:
closest_dist = dist
closest_pair = list(pair)
......@@ -428,21 +434,23 @@ def runUPGMA(aln, measure, absoluteDistances=False):
x = closest_pair[0] # See Zvelebil and Baum p. 278 for notation
y = closest_pair[1]
z = PhyloNode() # create a new node for the cluster z
z.dist = D.pop(frozenset([x, y])) / 2.0 # assign the absolute distance, travelled so far, note: this will change to relative distance later
z.dist = D.pop(frozenset([x, y])) / 2.0 # assign the absolute distance, change to relative distance later
Nx = N.pop(x) # find number of sequences in x, remove the cluster from list N
Ny = N.pop(y) # find number of sequences in y, remove the cluster from list N
dz = {} # new distances to cluster z
x.parent = z
y.parent = z
z.children = [x, y]
print('Closest pair is \"' + str(x) + '\" ('+str(Nx)+') and \"' + str(y) + '\" ('+str(Ny)+') at distance %5.3f' % (z.dist * 2), 'form new node ' + str(z))
for w in N: # for each node w ...
# we will merge x and y into a new cluster z, so need to consider w (which is not x or y)
dxw = D.pop(frozenset([x, w])) # retrieve and remove distance from D: x to w
dyw = D.pop(frozenset([y, w])) # retrieve and remove distance from D: y to w
dz[w] = (Nx * dxw + Ny * dyw) / (Nx + Ny) # distance: z to w
print(str(z) + ' gets distance to \"' + str(w) + '\": (', Nx, '* %5.3f' % dxw, '+', Ny, '* %5.3f' % dyw, ') / (', Nx, '+', Ny, ') = %5.3f' % dz[w])
N[z] = Nx + Ny # total number of sequences in new cluster, insert new cluster in list N
for w in dz: # we have to run through the nodes again, now not including the removed x and y
D[frozenset([z, w])] = dz[w] # for each "other" cluster, update distance per EQ8.16 (Z&B p. 278)
x.parent = z
y.parent = z
z.children = [x, y]
nodes.append(z)
if not absoluteDistances:
x._propagateDistance(z.dist) # convert absolute distances to relative by recursing down left path
......@@ -595,7 +603,17 @@ if __name__ == '__main__1':
print(tree)
if __name__ == '__main__':
tree = readNewick('/Users/mikael/simhome/ASR/parsitest.nwk')
tree.putAlignment(sequence.Alignment(sequence.readFastaFile('/Users/mikael/simhome/ASR/parsitest.aln', sequence.DNA_Alphabet)))
aln = sequence.readFastaFile('/Users/mikael/Documents/Teaching/SCIE2100/Exams/pdistupgma.aln', sequence.Protein_Alphabet)
tree = runUPGMA(sequence.Alignment(aln), "fractional")
writeNewickFile('/Users/mikael/Documents/Teaching/SCIE2100/Exams/pdistupgma.nwk', tree)
if __name__ == '__main__3':
aln = sequence.readClustalFile('/Users/mikael/simhome/ASR/dp16_example.aln', sequence.Protein_Alphabet)
tree = runUPGMA(aln, "poisson")
writeNewickFile('/Users/mikael/simhome/ASR/dp16_example_UPGMA.nwk', tree)
if __name__ == '__main__4':
tree = readNewick('/Users/mikael/simhome/ASR/parsitest2.nwk')
tree.putAlignment(sequence.Alignment(sequence.readFastaFile('/Users/mikael/simhome/ASR/parsitest2.aln', sequence.DNA_Alphabet)))
tree.parsimony()
print(tree.strSequences())
\ No newline at end of file
sequence.py
View file @ bd07c60d
......@@ -269,12 +269,13 @@ def parseDefline(string):
"""
if len(string) == 0: return ('', '', '', '')
s = string.split()[0]
if re.match("^sp\|[A-Z][A-Z0-9]{5}\|\S+", s): arg = s.split('|'); return (arg[1], arg[2], arg[0], '')
if re.match("^sp\|[A-Z][A-Z0-9]*\|\S+", s): arg = s.split('|'); return (arg[1], arg[2], arg[0], '')
elif re.match("^tr\|[A-Z][A-Z0-9]*\|\S+", s): arg = s.split('|'); return (arg[1], arg[2], arg[0], '')
elif re.match("^gi\|[0-9]*\|\S+\|\S+", s): arg = s.split('|'); return (arg[1], arg[3], arg[0], arg[2])
elif re.match("gb\|\S+\|\S+", s): arg = s.split('|'); return (arg[1], arg[2], arg[0], '')
elif re.match("emb\|\S+\|\S+", s): arg = s.split('|'); return (arg[1], arg[2], arg[0], '')
elif re.match("^refseq\|\S+\|\S+", s): arg = s.split('|'); return (arg[1], arg[2], arg[0], '')
elif re.match("[A-Z][A-Z0-9]*\|\S+", s): arg = s.split('|'); return (arg[0], arg[1], 'UniProt', '') # assume this is UniProt
else: return (s, '', '', '')
def readFastaFile(filename, alphabet = None, ignore = False, gappy = False, parse_defline = True):
......@@ -849,7 +850,7 @@ def alignGlobal(seqA, seqB, substMatrix, gap = -1):
# that ends at sequence indices i and j, for A and B, resp.)
for i in range(1, lenA + 1):
for j in range(1, lenB + 1):
match = S[i-1, j-1] + substMatrix.get(seqA[i-1], seqB[j-1])
match = S[i-1, j-1] + substMatrix.__getitem__(seqA[i - 1], seqB[j - 1])
fromTop = S[i-1, j ] + gap
fromLeft = S[i , j-1] + gap
S[i, j] = max([match, fromTop, fromLeft])
......@@ -908,7 +909,7 @@ def alignLocal(seqA, seqB, substMatrix, gap = -1):
# that ends at sequence indices i and j, for A and B, resp.)
for i in range(1, lenA + 1):
for j in range(1, lenB + 1):
match = S[i-1, j-1] + substMatrix.get(seqA[i-1], seqB[j-1])
match = S[i-1, j-1] + substMatrix.__getitem__(seqA[i - 1], seqB[j - 1])
fromTop = S[i-1, j ] + gap
fromLeft = S[i , j-1] + gap
S[i, j] = max([match, fromTop, fromLeft, 0]) # Local: add option that we re-start alignment from "0"
......@@ -967,12 +968,12 @@ def tripletAlignGlobal(seqA, seqB, seqC, subsMatrix, gap = -1):
for j in range(1, lenB+1):
for k in range(1, lenC+1):
# Scored using sum-of-pairs
matchABC = S[i-1, j-1, k-1] + subsMatrix.get(seqA[i-1], seqB[j-1]) \
+ subsMatrix.get(seqA[i-1], seqC[k-1]) \
+ subsMatrix.get(seqB[j-1], seqC[k-1])
matchAB = S[i-1, j-1, k] + 2*gap + subsMatrix.get(seqA[i-1], seqB[j-1])
matchBC = S[i, j-1, k-1] + 2*gap + subsMatrix.get(seqB[j-1], seqC[k-1])
matchAC = S[i-1, j, k-1] + 2*gap + subsMatrix.get(seqA[i-1], seqC[k-1])
matchABC = S[i-1, j-1, k-1] + subsMatrix.__getitem__(seqA[i - 1], seqB[j - 1]) \
+ subsMatrix.__getitem__(seqA[i - 1], seqC[k - 1]) \
+ subsMatrix.__getitem__(seqB[j - 1], seqC[k - 1])
matchAB = S[i-1, j-1, k] + 2*gap + subsMatrix.__getitem__(seqA[i - 1], seqB[j - 1])
matchBC = S[i, j-1, k-1] + 2*gap + subsMatrix.__getitem__(seqB[j - 1], seqC[k - 1])
matchAC = S[i-1, j, k-1] + 2*gap + subsMatrix.__getitem__(seqA[i - 1], seqC[k - 1])
gapAB = S[i, j, k-1] + 3*gap
gapBC = S[i-1, j, k] + 3*gap
gapAC = S[i, j-1, k] + 3*gap
......
sstruct.py
View file @ bd07c60d
......@@ -26,8 +26,6 @@ cf_dict = { # Chou-Fasman table
'T': ( 83, 119, 96, 0.086, 0.108, 0.065, 0.079 ), # Threonine
'W': ( 108, 137, 96, 0.077, 0.013, 0.064, 0.167 ), # Tryptophan
'Y': ( 69, 147, 114, 0.082, 0.065, 0.114, 0.125 ), # Tyrosine
'V': ( 106, 170, 50, 0.062, 0.048, 0.028, 0.053 ), # Valine
'Y': ( 69, 147, 114, 0.082, 0.065, 0.114, 0.125 ), # Tyrosine
'V': ( 106, 170, 50, 0.062, 0.048, 0.028, 0.053 ),} # Valine
prot_alpha = sym.Protein_Alphabet
......
test_hca.py 0 → 100644
View file @ bd07c60d
import unittest
from hca import *
import random
class MyTestCase(unittest.TestCase):
N = 8
def setUp(self):
""" Set up for each test """
self.pairidxs1 = dict()
y = 0
for i in range(self.N):
for j in range(i + 1, self.N):
self.pairidxs1[(i, j)] = y
y += 1
self.pairidxs2 = dict()
for i in range(self.N):
for j in range(0, i):
self.pairidxs2[(i, j)] = self.pairidxs1[(j, i)]
def test_PairArray1(self):
pa1 = PairArray(self.N)
pa2 = PairArray(self.N)
for p in self.pairidxs1:
pa1[p] = self.pairidxs1[p]
for p in self.pairidxs2:
pa2[p] = self.pairidxs2[p]
for (i, j) in self.pairidxs1:
self.assertEqual(pa1[(j, i)], self.pairidxs1[(i, j)])
for (i, j) in self.pairidxs2:
self.assertEqual(pa2[(j, i)], pa1[(j, i)])
def test_DNode1(self):
layer0 = [DNode(i) for i in range(0, 10)]
layer1 = []
for i in range(0, len(layer0) // 2):
layer1.append(DNode(i + len(layer0), children=[layer0[i * 2], layer0[i * 2 + 1]], dist = random.randint(1, 10)))
root = DNode(len(layer0) + len(layer1), layer1, dist = 100)
self.assertEquals(root.nChildren(), len(layer1))
self.assertEquals(len(root.getLeaves()), len(layer0))
for i in range(len(layer1)):
self.assertEquals(layer1[i].nChildren(), 2)
for i in range(len(layer0)):
self.assertEquals(layer0[i].nChildren(), 0)
def test_DNode2(self):
layer0 = [DNode(i) for i in range(0, 10)]
layer1 = []
for i in range(0, len(layer0) // 2):
layer1.append(DNode(i + len(layer0), children=[layer0[i * 2], layer0[i * 2 + 1]], dist = random.randint(1, 10)))
root1 = DNode(len(layer0) + len(layer1), layer1, dist = 100)
s1 = str(root1)
root2 = parse(s1)
self.assertEquals(root2.nChildren(), root1.nChildren())
self.assertEquals(len(root2.getLeaves()), len(root1.getLeaves()))
s2 = str(root2)
root3 = parse(s2)
self.assertEquals(str(root3), s2)
def test_DNode3(self):
layer0 = [DNode(i) for i in range(0, 8)]
layer1 = []
for i in range(0, len(layer0) // 2):
layer1.append(DNode(i + len(layer0), children=[layer0[i * 2], layer0[i * 2 + 1]], dist = random.randint(1, 10)))
layer2 = []
for i in range(0, len(layer1) // 2):
layer2.append(DNode(i + len(layer0) + len(layer1), children=[layer1[i * 2], layer1[i * 2 + 1]], dist = random.randint(11, 20)))
root = DNode(len(layer0) + len(layer1) + len(layer2), layer2, dist = 30)
chars = 'ABCDEFGHIJKLMNOP'
labels_list = [ch for ch in chars]
root1 = parse(root.newick(labels_list))
labels_rev = [ch for ch in chars[::-1]]
labels_off1 = [ch for ch in chars[1:]]
labels_dict = {}
for i in range(len(labels_list)):
labels_dict[i] = labels_list[i]
root2 = parse(root.newick(labels_dict))
self.assertEquals(len(parse(root.newick(labels_rev)).getLeaves()), len(root.getLeaves()))
self.assertEquals(root.newick(labels_dict), root.newick(labels_list))
for ch in chars[:-1]: # all chars except last one
node1 = root1.findNode(ch)
node2 = root2.findNode(ch)
self.assertIsNotNone(node1)
self.assertIsNotNone(node2)
self.assertEquals(len(node1.getLeaves()), len(node2.getLeaves()))
self.assertEquals(str(root1.findNode(ch)), str(root2.findNode(ch)))
def test_DNode4(self):
pass
if __name__ == '__main__':
unittest.main()
test_heap.py 0 → 100644
View file @ bd07c60d
import unittest
from heap import *
import random
class MyTestCase(unittest.TestCase):
def setUp(self):
""" Set up for each test """
idxs = [i for i in range(random.randint(0, 10), random.randint(10, 50))]
random.shuffle(idxs)
self.a = [(idx, random.random()) for idx in idxs]
self.mh = LabelHeap(len(self.a))
self.maxh = LabelHeap(len(self.a), reverse = True)
for (address, value) in self.a:
self.mh.add(address, value)
self.maxh.add(address, value)
def test_MinHeap1(self):
self.assertEqual(len(self.mh), len(self.a))
def test_MinHeap2(self):
minidx = 0
for i in range(1, len(self.a)):
if self.a[i][1] < self.a[minidx][1]:
minidx = i
#print(self.mh._elements[0], self.mh[0])
(address, value) = self.mh.pop()
self.assertEqual(address, self.a[minidx][0])
self.assertEqual(value, self.a[minidx][1])
def test_MinHeap3(self):
ys = [y[1] for y in self.a]
ys.sort(reverse=False)
for y in ys:
self.assertEqual(y, self.mh[0])
self.mh.pop()
def test_MaxHeap3(self):
ys = [y[1] for y in self.a]
ys.sort(reverse=True)
for y in ys:
self.assertEqual(y, self.maxh[0])
self.maxh.pop()
def test_MinHeap4(self):
mh1 = LabelHeap(10)
self.assertEquals(len(mh1), 0)
mh1.add('a', 2)
self.assertEquals(len(mh1), 1)
mh1.add('b', 1)
self.assertEquals(len(mh1), 2)
(label, y) = mh1.pop()
self.assertEquals(label, 'b')
self.assertEquals(len(mh1), 1)
mh1.add('c', 3)
self.assertEquals(len(mh1), 2)
if __name__ == '__main__':
unittest.main()
webservice.py
View file @ bd07c60d
......@@ -176,7 +176,7 @@ def getGODef(goterm):
goterm: the identifier, e.g. 'GO:0002080'
"""
# first turn off server certificate verification
if (not os.environ.get('PYTHONHTTPSVERIFY', '') and getattr(ssl, '_create_unverified_context', None)):
if (not os.environ.__getitem__('PYTHONHTTPSVERIFY', '') and getattr(ssl, '_create_unverified_context', None)):
ssl._create_default_https_context = ssl._create_unverified_context
# Construct URL with query term
url = __ebiGOUrl__ + 'ontology/go/search?query=' + goterm
......@@ -225,7 +225,7 @@ def getGOTerms(genes):
# Construct URL
# Get the entry: fill in the fields specified below
# first turn off server certificate verification
if (not os.environ.get('PYTHONHTTPSVERIFY', '') and getattr(ssl, '_create_unverified_context', None)):
if (not os.environ.__getitem__('PYTHONHTTPSVERIFY', '') and getattr(ssl, '_create_unverified_context', None)):
ssl._create_default_https_context = ssl._create_unverified_context
page = 1
try:
......@@ -234,7 +234,7 @@ def getGOTerms(genes):
urlreq = urllib.request.Request(url)
urlreq.add_header('Accept-encoding', 'gzip')
response = urllib.request.urlopen(urlreq)
if response.info().get('Content-Encoding') == 'gzip':
if response.info().__getitem__('Content-Encoding') == 'gzip':
buf = StringIO(response.read())
f = gzip.GzipFile(fileobj=buf)
data = f.read().decode("utf-8")
......@@ -285,7 +285,7 @@ def getGenes(goterms, taxo=None):
term = termbatch[i]
uri_string += term + "," if i < len(termbatch) - 1 else term
# first turn off server certificate verification
if (not os.environ.get('PYTHONHTTPSVERIFY', '') and getattr(ssl, '_create_unverified_context', None)):
if (not os.environ.__getitem__('PYTHONHTTPSVERIFY', '') and getattr(ssl, '_create_unverified_context', None)):
ssl._create_default_https_context = ssl._create_unverified_context
page = 1
try:
......@@ -294,7 +294,7 @@ def getGenes(goterms, taxo=None):
urlreq = urllib.request.Request(url)
urlreq.add_header('Accept-encoding', 'gzip')
response = urllib.request.urlopen(urlreq)
if response.info().get('Content-Encoding') == 'gzip':
if response.info().__getitem__('Content-Encoding') == 'gzip':
buf = StringIO(response.read())
f = gzip.GzipFile(fileobj=buf)
data = f.read().decode("utf-8")
......@@ -534,7 +534,7 @@ def getUniProtDict(ids, cols="", db='uniprot', identities=None):
request = urllib.request.Request(url, data)
opener = urllib.request.build_opener()
response = opener.open(request)
page = response.read(200000).decode('utf-8')
page = response.read(20000000).decode('utf-8')
up_dict = {}
# For each record we retrieve, split the line by tabs and build up the UniProt dict
......
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