load parameters from a file in Python - python

I am writing a Python class to model a process and I want to initialized the parameters from a file, say 'input.dat'. The format of the input file looks like this.
'input.dat' file:
Z0: 0 0
k: 0.1
g: 1
Delta: 20
t_end: 300
The code I wrote is the following. It works but appears redundant and inflexible. Is there a better way to do the job? Such as a loop to do readline() and then match the keyword?
def load(self,filename="input.dat"):
FILE = open(filename)
s = FILE.readline().split()
if len(s) is 3:
self.z0 = [float(s[1]),float(s[2])] # initial state
s = FILE.readline().split()
if len(s) is 2:
self.k = float(s[1]) # kappa
s = FILE.readline().split()
if len(s) is 2:
self.g = float(s[1])
s = FILE.readline().split()
if len(s) is 2:
self.D = float(s[1]) # Delta
s = FILE.readline().split()
if len(s) is 2:
self.T = float(s[1]) # end time


Assuming the params are coming from a safe place (made by you or users, not the internet), just make the parameters file a Python file, params.py:
Z0 = (0, 0)
k = 0.1
g = 1
Delta = 20
t_end = 300
Then in your code all you need is:
import params
fancy_calculation(10, k=params.k, delta=params.Delta)
The beauty of this is two-fold: 1) simplicity, and 2) you can use the power of Python in your parameter descriptions -- particularly useful here, for example:
k = 0.1
Delta = 20
g = 3 * k + Delta
Alternatively, you could use Python's built-in JSON or ConfigParser .INI parser modules.


If you are open to some other kind of file where you can keep your parameters, I would suggest you to use a YAML file.
The Python library is PyYAML. This is how you can easily use it with Python.
For a better introduction, look at this Wikipedia article: http://en.wikipedia.org/wiki/YAML.
The benefit is you can read the parameter values as lists or maps.
You would love it!


Try the following:
def load(self, filename="input.dat"):
d = {"Z0": "z0", "k": "k", "g": "g", "Delta": "D", "t_end": "T"}
FILE = open(filename)
for line in FILE:
name, value = line.split(":")
value = value.strip()
if " " in value:
value = map(float, value.split())
else:
value = float(value)
setattr(self, d[name], value)
Proof that it works:
>>> class A(object): pass
...
>>> a = A()
>>> load(a)
>>> a.__dict__
{'k': 0.10000000000000001, 'z0': [0.0, 0.0], 'D': 20.0, 'g': 1.0, 'T': 300.0}


As others have mentioned, in Python you can create object attributes dynamically "on the fly". That means you could do something like the following to create Params objects as they're read-in. I've tried to make the code as data-driven as possible, so relatively flexible.
# maps label to attribute name and types
label_attr_map = {
"Z0:": ["z0", float, float],
"k:": [ "k", float],
"g:": [ "g", float],
"Delta:": [ "D", float],
"t_end:": [ "T", float]
}
class Params(object):
def __init__(self, input_file_name):
with open(input_file_name, 'r') as input_file:
for line in input_file:
row = line.split()
label = row[0]
data = row[1:] # rest of row is data list
attr = label_attr_map[label][0]
datatypes = label_attr_map[label][1:]
values = [(datatypes[i](data[i])) for i in range(len(data))]
self.__dict__[attr] = values if len(values) > 1 else values[0]
params = Params('input.dat')
print 'params.z0:', params.z0
print 'params.k:', params.k
print 'params.g:', params.g
print 'params.D:', params.D
print 'params.T:', params.T
Output:
params.z0: [0.0, 0.0]
params.k: 0.1
params.g: 1.0
params.D: 20.0
params.T: 300.0


Perhaps this might give you what you need:
def load(self,filename='input.dat'):
with open(filename) as fh:
for line in fh:
s = line.split()
if len(s) == 2:
setattr(self,s[1],s[2])
elif len(s) == 3:
setattr(self,s[1],s[2:])
I also didn't include any error checking, but setattr is very handy.


Something like this:
def load(self,filename="input.dat"):
# maps names to number of fields they need
# only necessary for variables with more than 1 field
argmap = dict(Z0=2)
# maps config file names to their attribute names on the object
# if name is the same both places, no need
namemap = dict(Z0="z0", Delta="D", t_end="T")
with open(filename) as FILE:
for line in FILE:
s = line.split()
var = s[0].rstrip(":")
try:
val = [float(x) for x in s[1:]]
except ValueError:
continue
if len(val) == varmap.get(var, 1):
if len(val) == 1:
val = val[0]
setattr(self, namemap.get(var, var), val)


Python objects have a built-in __dict__ member. You can modify it, and then refer to properties as obj.key.
class Data(object):
def __init__(self, path='infile.dat'):
with open(path, 'r') as fo:
for line in fo.readlines():
if len(line) < 2: continue
parts = [s.strip(' :\n') for s in line.split(' ', 1)]
numbers = [float(s) for s in parts[1].split()]
# This is optional... do you want single values to be stored in lists?
if len(numbers) == 1: numbers = numbers[0]
self.__dict__[parts[0]] = numbers
# print parts -- debug
obj = Data('infile.dat')
print obj.g
print obj.Delta
print obj.Z0
At the end of this, we print out a few of the keys. Here's the output of those.
1.0
20.0
[0.0, 0.0]
For consistency, you can remove the line marked "optional" in my code, and have all objects in lists -- regardless of how many elements they have. That will make using them quite a bit easier, because you never have to worry about obj.g[0] returning an error.


Here's another one
def splitstrip(s):
return s.split(':')[1].strip()
with open('input.dat','r') as f:
a.z0 = [float(x) for x in splitstrip(f.readline()).split(' ')]
a.k, a.g, a.D, a.T = tuple([float(splitstrip(x)) for x in f.read().rstrip().split('\n')])
;)

Related

Doing operations on a large data set

I have to perform some analysis on a PSL record which contains information on DNA sequence fragments. Basically I have to find entries that are from the same read in the same contig (these are both values in the PSL entry). The problem is the PSL records are large (10-30 Mb text documents). I wrote a program that works on short records and on the long records given enough time but it took way longer than specified. I was told the program shouldn't take more than ~15 seconds. Mine took over 15 minutes.
PSL records look like this:
275 11 0 0 0 0 0 0 - M02034:35:000000000-A7UU0:1:1101:19443:1992/2 286 0 286 NODE_406138_length_13407_cov_13.425076 13465 408 694 1 286, 0, 408,
171 5 0 0 0 0 0 0 + M02034:35:000000000-A7UU0:1:1101:13497:2001/2 294 0 176 NODE_500869_length_34598_cov_30.643419 34656 34334 34510 1 176, 0, 34334,
188 14 0 10 0 0 0 0 + M02034:35:000000000-A7UU0:1:1101:18225:2002/1 257 45 257 NODE_455027_length_12018_cov_13.759444 12076 11322 11534 1 212, 45, 11322,
My code looks like this:
import sys
class PSLreader :
'''
Class to provide reading of a file containing psl alignments
formatted sequences:
object instantiation:
myPSLreader = PSLreader(<file name>):
object attributes:
fname: the initial file name
methods:
readPSL() : reads psl file, yielding those alignments that are within the first or last
1000 nt
readPSLpairs() : yields psl pairs that support a circular hypothesis
Author: David Bernick
Date: May 12, 2013
'''
def __init__ (self, fname=''):
'''contructor: saves attribute fname '''
self.fname = fname
def doOpen (self):
if self.fname is '':
return sys.stdin
else:
return open(self.fname)
def readPSL (self):
'''
using filename given in init, returns each filtered psl records
that contain alignments that are within the terminal 1000nt of
the target. Incomplete psl records are discarded.
If filename was not provided, stdin is used.
This method selects for alignments that could may be part of a
circle.
Illumina pairs aligned to the top strand would have read1(+) and read2(-).
For the bottoms trand, read1(-) and read2(+).
For potential circularity,
these are the conditions that can support circularity:
read1(+) near the 3' terminus
read1(-) near the 5' terminus
read2(-) near the 5' terminus
read2(+) near the 3' terminus
so...
any read(+) near the 3', or
any read(-) near the 5'
'''
nearEnd = 1000 # this constant determines "near the end"
with self.doOpen() as fileH:
for line in fileH:
pslList = line.split()
if len(pslList) < 17:
continue
tSize = int(pslList[14])
tStart = int(pslList[15])
strand = str(pslList[8])
if strand.startswith('+') and (tSize - tStart > nearEnd):
continue
elif strand.startswith('-') and (tStart > nearEnd):
continue
yield line
def readPSLpairs (self):
read1 = []
read2 = []
for psl in self.readPSL():
parsed_psl = psl.split()
strand = parsed_psl[9][-1]
if strand == '1':
read1.append(parsed_psl)
elif strand == '2':
read2.append(parsed_psl)
output = {}
for psl1 in read1:
name1 = psl1[9][:-1]
contig1 = psl1[13]
for psl2 in read2:
name2 = psl2[9][:-1]
contig2 = psl2[13]
if name1 == name2 and contig1 == contig2:
try:
output[contig1] += 1
break
except:
output[contig1] = 1
break
print(output)
PSL_obj = PSLreader('EEV14-Vf.filtered.psl')
PSL_obj.readPSLpairs()
I was given some example code that looks like this:
def doSomethingPairwise (a):
for leftItem in a[1]:
for rightItem in a[2]:
if leftItem[1] is rightItem[1]:
print (a)
thisStream = [['David', 'guitar', 1], ['David', 'guitar', 2],
['John', 'violin', 1], ['John', 'oboe', 2],
['Patrick', 'theremin', 1], ['Patrick', 'lute',2] ]
thisGroup = None
thisGroupList = [ [], [], [] ]
for name, instrument, num in thisStream:
if name != thisGroup:
doSomethingPairwise(thisGroupList)
thisGroup = name
thisGroupList = [ [], [], [] ]
thisGroupList[num].append([name, instrument, num])
doSomethingPairwise(thisGroupList)
But when I tried to implement it my program still took a long time. Am I thinking about this the wrong way? I realize the nested loop is slow but I don't see an alternative.
Edit: I figured it out, the data was presorted which made my brute force solution very impractical and unnecessary.

I hope help you, since, the question needs a best input example file
#is better create PSLRecord class
class PSLRecord:
def __init__(self, line):
pslList = line.split()
properties = ("matches", "misMatches", "repMatches", "nCount",
"qNumInsert", "qBaseInsert", "tNumInsert",
"tBaseInsert", "strand", "qName", "qSize", "qStart",
"qEnd", "tName", "tSize", "tStart", "tEnd", "blockCount",
"blockSizes", "qStarts", "tStarts")
self.__dict__.update(dict(zip(properties, pslList)))
class PSLreader :
def __init__ (self, fname=''):
self.fname = fname
def doOpen (self):
if self.fname is '':
return sys.stdin
else:
return open(self.fname)
def readPSL (self):
with self.doOpen() as fileH:
for line in fileH:
pslrc = PSLRecord(line)
yield pslrc
#return a dictionary with all psl records group by qName and tName
def readPSLpairs (self):
dictpsl = {}
for pslrc in self.readPSL():
#OP requirement, remove '1' or '2' char, in pslrc.qName[:-1]
key = (pslrc.qName[:-1], pslrc.tName)
if not key in dictpsl:
dictpsl[key] = []
dictpsl[key].append(pslrc)
return dictpsl
#Function filter .... is better out and self-contained
def f_filter(pslrec, nearEnd = 1000):
if (pslrec.strand.startswith('+') and
(int(pslrec.tSize) - int(pslrec.tStart) > nearEnd)):
return False
if (pslrec.strand.startswith('-') and
(int(pslrec.tStart) > nearEnd)):
return False
return True
PSL_obj = PSLreader('EEV14-Vf.filtered.psl')
#read dictionary of pairs
dictpsl = PSL_obj.readPSLpairs()
from itertools import product
#product from itertools
#(1) x (2,3) = (1,2),(1,3)
output = {}
for key, v in dictpsl.items():
name, contig = key
#i get filters aligns in principal strand
strand_princ = [pslrec for pslrec in v if f_filter(pslrec) and
pslrec.qName[-1] == '1']
#i get filters aligns in secondary strand
strand_sec = [pslrec for pslrec in v if f_filter(pslrec) and
pslrec.qName[-1] == '2']
for pslrec_princ, pslrec_sec in product(strand_princ, strand_sec):
#This For has fewer comparisons, since I was grouped before
if not contig in output:
output[contig] = 1
output[contig] += 1
Note: 10-30 Mb isn't large file, if you ask me

Extract data from within parenthesis in python

I know there are many questions with the same title. My situation is a little different. I have a string like:
"Cat(Money(8)Points(80)Friends(Online(0)Offline(8)Total(8)))Mouse(Money(10)Points(10000)Friends(Online(10)Offline(80)Total(90)))"
(Notice that there are parenthesis nested inside another)
and I need to parse it into nested dictionaries like for example:
d["Cat"]["Money"] == 8
d["Cat"]["Points"] = 80
d["Mouse"]["Friends"]["Online"] == 10
and so on. I would like to do this without libraries and regex. If you choose to use these, please explain the code in great detail.
Thanks in advance!
Edit:
Although this code will not make any sense, this is what I have so far:
o_str = "Jake(Money(8)Points(80)Friends(Online(0)Offline(8)Total(8)))Mouse(Money(10)Points(10000)Friends(Online(10)Offline(80)Total(90)))"
spl = o_str.split("(")
def reverseIndex(str1, str2):
try:
return len(str1) - str1.rindex(str2)
except Exception:
return len(str1)
def app(arr,end):
new_arr = []
for i in range(0,len(arr)):
if i < len(arr)-1:
new_arr.append(arr[i]+end)
else:
new_arr.append(arr[i])
return new_arr
spl = app(spl,"(")
ends = []
end_words = []
op = 0
cl = 0
for i in range(0,len(spl)):
print i
cl += spl[i].count(")")
op += 1
if cl == op-1:
ends.append(i)
end_words.append(spl[i])
#break
print op
print cl
print
print end_words
The end words are the sections at the beginning of each statement. I plan on using recursive to do the rest.

Now that was interesting. You really nerd-sniped me on this one...
def parse(tokens):
""" take iterator of tokens, parse to dictionary or atom """
dictionary = {}
# iterate tokens...
for token in tokens:
if token == ")" or next(tokens) == ")":
# token is ')' -> end of dict; next is ')' -> 'leaf'
break
# add sub-parse to dictionary
dictionary[token] = parse(tokens)
# return dict, if non-empty, else token
return dictionary or int(token)
Setup and demo:
>>> s = "Cat(Money(8)Points(80)Friends(Online(0)Offline(8)Total(8)))Mouse(Money(10)Points(10000)Friends(Online(10)Offline(80)Total(90)))"
>>> tokens = iter(s.replace("(", " ( ").replace(")", " ) ").split())
>>> pprint(parse(tokens))
{'Cat': {'Friends': {'Offline': 8, 'Online': 0, 'Total': 8},
'Money': 8,
'Points': 80},
'Mouse': {'Friends': {'Offline': 80, 'Online': 10, 'Total': 90},
'Money': 10,
'Points': 10000}}
Alternatively, you could also use a series of string replacements to turn that string into an actual Python dictionary string and then evaluate that, e.g. like this:
as_dict = eval("{'" + s.replace(")", "'}, ")
.replace("(", "': {'")
.replace(", ", ", '")
.replace(", ''", "")[:-3] + "}")
This will wrap the 'leafs' in singleton sets of strings, e.g. {'8'} instead of 8, but this should be easy to fix in a post-processing step.

Python unified diff with line numbers from both "files"

I'm trying to figure out a way to create unified diffs with line numbers only showing N lines of context. I have been unable to do this with difflib.unified_diff. I need to show changes in both files.
The closest I can come is using diff on the command line like so:
/usr/bin/diff
--unchanged-line-format=' %.2dn %L'
--old-line-format="-%.2dn %L"
--new-line-format="+%.2dn %L"
file1.py
file2.py
BUT I only want to show N lines of context, and /usr/bin/diff doesn't seem to support context with a custom line format (eg. -U2 is not compatible with --line-format "conflicting output style options").
Below is an example of what I'd like to accomplish (the same output as the above diff, but only showing 1 line of context surrounding changes):
+01: def renamed_function()
-01: def original_function():
02:
+03: """ Neat stuff here """
04:
21:
+22: # Here's a new comment
23:
85: # Output the value of foo()
+86: print "Foo is %s"%(foo())
-86: print foo()
87:

I was able to figure out something very close to what I wanted to do. It's slower than regular diff, though. Here's the entire code, from my project GitGate.
def unified_diff(to_file_path, from_file_path, context=1):
""" Returns a list of differences between two files based
on some context. This is probably over-complicated. """
pat_diff = re.compile(r'## (.[0-9]+\,[0-9]+) (.[0-9]+,[0-9]+) ##')
from_lines = []
if os.path.exists(from_file_path):
from_fh = open(from_file_path,'r')
from_lines = from_fh.readlines()
from_fh.close()
to_lines = []
if os.path.exists(to_file_path):
to_fh = open(to_file_path,'r')
to_lines = to_fh.readlines()
to_fh.close()
diff_lines = []
lines = difflib.unified_diff(to_lines, from_lines, n=context)
for line in lines:
if line.startswith('--') or line.startswith('++'):
continue
m = pat_diff.match(line)
if m:
left = m.group(1)
right = m.group(2)
lstart = left.split(',')[0][1:]
rstart = right.split(',')[0][1:]
diff_lines.append("## %s %s ##\n"%(left, right))
to_lnum = int(lstart)
from_lnum = int(rstart)
continue
code = line[0]
lnum = from_lnum
if code == '-':
lnum = to_lnum
diff_lines.append("%s%.4d: %s"%(code, lnum, line[1:]))
if code == '-':
to_lnum += 1
elif code == '+':
from_lnum += 1
else:
to_lnum += 1
from_lnum += 1
return diff_lines

Parse svg:path d attribute

I need to decipher a path element in an SVG document to drive a CNC machine along that path. I wonder if there are any Python libraries that parse SVG and give some sort of pythonic list for the d attribute, e.g.:
<path d="M 20 30 L 20 20 20 40 40 40"/>
parses into
[["M", 20, 30],
["L", 20, 20],
["L", 20, 40],
["L", 40, 40]]

Here's a start it's written by me and in python 2.7.2. Just delete the tests and print statements if you want to.
Copyright 2012 Christopher L. Ramsey
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
from collections import OrderedDict
from re import match
from re import split
from re import sub
class PathIterator(object):
EOI = 'End of Iteration'
PATH_IDENTIFIERS = r'[MLHVCSQTAmlhvcsqa]'
NUMBERS = r'[0-9.-^A-z]'
SEPERATORS = r'\s|\,'
PATH_END = r'[Zz]'
def __init__(self, path):
self.parseable = path.translate(None, '\t\f')
self.parseable = self.parseable.replace('\n', ' ')
print 'strip_newlines: {}'.format(self.parseable)
self.parseable = sub(r'([A-Za-z])([0-9]|\-)', self.insert, self.parseable)
print 'add_space: {}'.format(self.parseable)
self.parseable = self.parseable.replace(',', ' ')
print 'replace_commas: {}'.format(self.parseable)
self.parseable = sub(r'\s+', ' ', self.parseable) # replace any double space with a single space
print 'strip_extra_space: {}'.format(self.parseable)
self.tokens = split(' ', self.parseable)
self.map = self.produce_map(self.tokens)
print self.map
self.elements = self.process(self.map)
def produce_map(self, tkns):
self.m = OrderedDict()
self.i = 0
while self.i < len(tkns):
if match(self.PATH_IDENTIFIERS, tkns[self.i]):
self.m[self.i] = tkns[self.i]
elif match(self.PATH_END, tkns[self.i]):
self.m[self.i] = tkns[self.i]
else:
pass
self.i += 1
return self.m.items()
def process(self, map):
self.mm = []
self.l = len(map)
for e in range(self.l):
try:
self.element = map[e]
self.future = map[e + 1]
self.ident = self.element[1]
self.start = self.element[0] + 1
self.end = self.future[0]
self.nbrs = self.tokens[self.start:self.end]
except:
self.element = map[e]
self.ident = self.element[1]
self.start = self.element[0] + 1
self.end = len(self.tokens)
self.nbrs = self.tokens[self.start:self.end]
print 'start: {} end {}'.format(self.start, self.end)
finally:
self.numbers = []
for number in self.nbrs:
self.numbers.append(float(number))
self.mm.append((self.ident, self.numbers))
return iter(self.mm)
def next(self):
try:
return self.elements.next()
except:
return self.EOI
def insert(self, match_obj):
self.group = match_obj.group()
return '{} {}'.format(self.group[0], self.group[1])
if __name__ == '__main__':
inkscape_path = "M 12,90 C 8.676,90 6,87.324 6,84 L 6,82 6,14 6,12 c 0,-0.334721 0.04135,-0.6507 0.09375,-0.96875 0.0487,-0.295596 0.09704,-0.596915 0.1875,-0.875 C 6.29113,10.12587 6.302142,10.09265 6.3125,10.0625 6.411365,9.774729 6.5473802,9.515048 6.6875,9.25 6.8320918,8.976493 7.0031161,8.714385 7.1875,8.46875 7.3718839,8.223115 7.5612765,7.995278 7.78125,7.78125 8.221197,7.353194 8.72416,6.966724 9.28125,6.6875 9.559795,6.547888 9.8547231,6.440553 10.15625,6.34375 9.9000482,6.443972 9.6695391,6.580022 9.4375,6.71875 c -0.00741,0.0044 -0.023866,-0.0045 -0.03125,0 -0.031933,0.0193 -0.062293,0.04251 -0.09375,0.0625 -0.120395,0.0767 -0.2310226,0.163513 -0.34375,0.25 -0.1061728,0.0808 -0.2132809,0.161112 -0.3125,0.25 C 8.4783201,7.442683 8.3087904,7.626638 8.15625,7.8125 8.0486711,7.942755 7.9378561,8.077785 7.84375,8.21875 7.818661,8.25713 7.805304,8.30462 7.78125,8.34375 7.716487,8.446782 7.6510225,8.548267 7.59375,8.65625 7.4927417,8.850956 7.3880752,9.071951 7.3125,9.28125 7.30454,9.30306 7.288911,9.3218 7.28125,9.34375 7.2494249,9.4357 7.2454455,9.530581 7.21875,9.625 7.1884177,9.731618 7.1483606,9.828031 7.125,9.9375 7.0521214,10.279012 7,10.635705 7,11 l 0,2 0,68 0,2 c 0,2.781848 2.2181517,5 5,5 l 2,0 68,0 2,0 c 2.781848,0 5,-2.218152 5,-5 l 0,-2 0,-68 0,-2 C 89,10.635705 88.94788,10.279012 88.875,9.9375 88.83085,9.730607 88.78662,9.539842 88.71875,9.34375 88.71105,9.3218 88.69545,9.30306 88.6875,9.28125 88.62476,9.107511 88.549117,8.913801 88.46875,8.75 88.42717,8.6672 88.38971,8.580046 88.34375,8.5 88.28915,8.40279 88.216976,8.31165 88.15625,8.21875 88.06214,8.077785 87.951329,7.942755 87.84375,7.8125 87.700576,7.63805 87.540609,7.465502 87.375,7.3125 87.36383,7.3023 87.35502,7.29135 87.34375,7.28125 87.205364,7.155694 87.058659,7.046814 86.90625,6.9375 86.803679,6.86435 86.701932,6.784136 86.59375,6.71875 c -0.0074,-0.0045 -0.02384,0.0044 -0.03125,0 -0.232039,-0.138728 -0.462548,-0.274778 -0.71875,-0.375 0.301527,0.0968 0.596455,0.204138 0.875,0.34375 0.55709,0.279224 1.060053,0.665694 1.5,1.09375 0.219973,0.214028 0.409366,0.441865 0.59375,0.6875 0.184384,0.245635 0.355408,0.507743 0.5,0.78125 0.14012,0.265048 0.276135,0.524729 0.375,0.8125 0.01041,0.03078 0.02133,0.06274 0.03125,0.09375 0.09046,0.278085 0.1388,0.579404 0.1875,0.875 C 89.95865,11.3493 90,11.665279 90,12 l 0,2 0,68 0,2 c 0,3.324 -2.676,6 -6,6 l -72,0 z"
mdn_path = "M10 80 Q 52.5 10, 95 80 T 180 80"
w3c_path = "M100,200 C100,100 250,100 250,200 S400,300 400,200"
w3c_path_neg = "M-100,200 C100,100 250,100 250,200 S-400,300 400,200"
w3c_path_nl = '''
M600,350 l 50,-25
a25,25 -30 0,1 50,-25 l 50,-25
a25,50 -30 0,1 50,-25 l 50,-25
a25,75 -30 0,1 50,-25 l 50,-25
a25,100 -30 0,1 50,-25 l 50,-25
'''
paths = [inkscape_path, mdn_path, w3c_path, str.strip(w3c_path_nl), w3c_path_neg]
for path in paths:
p = PathIterator(path)
char = ''
while char != PathIterator.EOI:
char = p.next()
print char

Getting the d-string can be down in a couple lines using svgpathtools, the rest can be done using regular expressions.
from svgpathtools import svg2paths
paths, attributes = svg2paths('some_svg_file.svg')
paths is a list of svgpathtools Path objects (containing just the curve info, no colors, styles, etc.).
attributes is a list of dictionary objects of the attributes.
Suppose the path you are interested in is the first (the 0th) listed in your SVG, then to extract just the d-string you can use:
d = attributes[0]['d'] # d-string from first path in SVG
# Now for some regular expressions magic
import re
split_by_letters = re.findall('[A-Z|a-z][^A-Z|a-z]*', d)
split_as_you_want = []
for x in split_by_letters:
nums = x[1:].replace(',',' ').split() # list of numbers after letter
for k in range(len(nums) // 2):
split_as_you_want.append([x[0]] + [nums[k]] + [nums[k+1]])
print split_as_you_want
I didn't convert the numbers into strings here as how you want to do that depends on whether they're always integers and whether you care they stay that way. For most purposes this can be done with something like the following right below the "nums = ..." line.
for k, n in enumerate(nums):
try:
nums[k] = int(n)
except ValueError:
nums[k] = float(n)

Python: File formatting

I have a for loop which references a dictionary and prints out the value associated with the key. Code is below:
for i in data:
if i in dict:
print dict[i],
How would i format the output so a new line is created every 60 characters? and with the character count along the side for example:
0001
MRQLLLISDLDNTWVGDQQALEHLQEYLGDRRGNFYLAYATGRSYHSARELQKQVGLMEP
0061
DYWLTAVGSEIYHPEGLDQHWADYLSEHWQRDILQAIADGFEALKPQSPLEQNPWKISYH
0121 LDPQACPTVIDQLTEMLKETGIPVQVIFSSGKDVDLLPQRSNKGNATQYLQQHLAMEPSQ

It's a finicky formatting problem, but I think the following code:
import sys
class EveryN(object):
def __init__(self, n, outs):
self.n = n # chars/line
self.outs = outs # output stream
self.numo = 1 # next tag to write
self.tll = 0 # tot chars on this line
def write(self, s):
while True:
if self.tll == 0: # start of line: emit tag
self.outs.write('%4.4d ' % self.numo)
self.numo += self.n
# wite up to N chars/line, no more
numw = min(len(s), self.n - self.tll)
self.outs.write(s[:numw])
self.tll += numw
if self.tll >= self.n:
self.tll = 0
self.outs.write('\n')
s = s[numw:]
if not s: break
if __name__ == '__main__':
sys.stdout = EveryN(60, sys.stdout)
for i, a in enumerate('abcdefgh'):
print a*(5+ i*5),
shows how to do it -- the output when running for demonstration purposes as the main script (five a's, ten b's, etc, with spaces in-between) is:
0001 aaaaa bbbbbbbbbb ccccccccccccccc dddddddddddddddddddd eeeeee
0061 eeeeeeeeeeeeeeeeeee ffffffffffffffffffffffffffffff ggggggggg
0121 gggggggggggggggggggggggggg hhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh
0181 hhhhhhh

# test data
data = range(10)
the_dict = dict((i, str(i)*200) for i in range( 10 ))
# your loops as a generator
lines = ( the_dict[i] for i in data if i in the_dict )
def format( line ):
def splitter():
k = 0
while True:
r = line[k:k+60] # take a 60 char block
if r: # if there are any chars left
yield "%04d %s" % (k+1, r) # format them
else:
break
k += 60
return '\n'.join(splitter()) # join all the numbered blocks
for line in lines:
print format(line)

I haven't tested it on actual data, but I believe the code below would do the job. It first builds up the whole string, then outputs it a 60-character line at a time. It uses the three-argument version of range() to count by 60.
s = ''.join(dict[i] for i in data if i in dict)
for i in range(0, len(s), 60):
print '%04d %s' % (i+1, s[i:i+60])

It seems like you're looking for textwrap
The textwrap module provides two convenience functions, wrap() and
fill(), as well as TextWrapper, the class that does all the work, and
a utility function dedent(). If you’re just wrapping or filling one or
two text strings, the convenience functions should be good enough;
otherwise, you should use an instance of TextWrapper for efficiency.

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