Develop Reference

Problem skipping line whilst iterating using previous line and current line comparison

I have a list of sorted data arranged so that each item in the list is a csv line to be written to file.
The final step of the script checks the contents of each field and if all but the last field match then it will copy the current line's last field onto the previous line's last field.
I would like to as I've found and processed one of these matches skip the current line where the field was copied from thus only leaving one of the lines.
Here's an example set of data
field1,field2,field3,field4,something
field1,field2,field3,field4,else
Desired output
field1,field2,field3,field4,something else
This is what I have so far
output_csv = ['field1,field2,field3,field4,something',
'field1,field2,field3,field4,else']
# run through the output
# open and create a csv file to save output
with open('output_table.csv', 'w') as f:
previous_line = None
part_duplicate_line = None
part_duplicate_flag = False
for line in output_csv:
part_duplicate_flag = False
if previous_line is not None:
previous = previous_line.split(',')
current = line.split(',')
if (previous[0] == current[0]
and previous[1] == current[1]
and previous[2] == current[2]
and previous[3] == current[3]):
print(previous[0], current[0])
previous[4] = previous[4].replace('\n', '') + ' ' + current[4]
part_duplicate_line = ','.join(previous)
part_duplicate_flag = True
f.write(part_duplicate_line)
if part_duplicate_flag is False:
f.write(previous_line)
previous_line = line
ATM script adds the line but doesn't skip the next line, I've tried various renditions of continue statements after part_duplicate_line is written to file but to no avail.

Looks like you want one entry for each combination of the first 4 fields
You can use a dict to aggregate data -
#First we extract the key and values
output_csv_keys = list(map(lambda x: ','.join(x.split(',')[:-1]), output_csv))
output_csv_values = list(map(lambda x: x.split(',')[-1], output_csv))
#Then we construct a dictionary with these keys and combine the values into a list
from collections import defaultdict
output_csv_dict = defaultdict(list)
for key, value in zip(output_csv_keys, output_csv_values):
output_csv_dict[key].append(value)
#Then we extract the key/value combinations from this dictionary into a list
for_printing = [','.join([k, ' '.join(v)]) for k, v in output_csv_dict.items()]
print(for_printing)
#Output is ['field1,field2,field3,field4,something else']
#Each entry of this list can be output to the csv file

I propose to encapsulate what you want to do in a function where the important part obeys this logic:
either join the new info to the old record
or output the old record and forget it
of course at the end of the loop we have in any case a dangling old record to output
def join(inp_fname, out_fname):
'''Input file contains sorted records, when two (or more) records differ
only in the last field, we join the last fields with a space
and output only once, otherwise output the record as-is.'''
######################### Prepare for action ##########################
from csv import reader, writer
with open(inp_fname) as finp, open(out_fname, 'w') as fout:
r, w = reader(finp), writer(fout)
######################### Important Part starts here ##############
old = next(r)
for new in r:
if old[:-1] == new[:-1]:
old[-1] += ' '+new[-1]
else:
w.writerow(old)
old = new
w.writerow(old)
To check what I've proposed you can use these two snippets (note that these records are shorter than yours, but it's an example and it doesn't matter because we use only -1 to index our records).
The 1st one has a "regular" last record
open('a0.csv', 'w').write('1,1,2\n1,1,3\n1,2,0\n1,3,1\n1,3,2\n3,3,0\n')
join('a0.csv', 'a1.csv')
while the 2nd has a last record that must be joined to the previous one.
open('b0.csv', 'w').write('1,1,2\n1,1,3\n1,2,0\n1,3,1\n1,3,2\n')
join('b0.csv', 'b1.csv')
If you run the snippets, as I have done before posting, in the environment where you have defined join you should get what you want.

String Cutting with multiple lines

so i'm new to python besides some experience with tKintner (some GUI experiments).
I read an .mbox file and copy the plain/text in a string. This text contains a registering form. So a Stefan, living in Maple Street, London working for the Company "MultiVendor XXVideos" has registered with an email for a subscription.
Name_OF_Person: Stefan
Adress_HOME: London, Maple
Street
45
Company_NAME: MultiVendor
XXVideos
I would like to take this data and put in a .csv row with column
"Name", "Adress", "Company",...
Now i tried to cut and slice everything. For debugging i use "print"(IDE = KATE/KDE + terminal... :-D ).
Problem is, that the data contains multiple lines after keywords but i only get the first line.
How would you improve my code?
import mailbox
import csv
import email
from time import sleep
import string
fieldnames = ["ID","Subject","Name", "Adress", "Company"]
searchKeys = [ 'Name_OF_Person','Adress_HOME','Company_NAME']
mbox_file = "REG.mbox"
export_file_name = "test.csv"
if __name__ == "__main__":
with open(export_file_name,"w") as csvfile:
writer = csv.DictWriter(csvfile, dialect='excel',fieldnames=fieldnames)
writer.writeheader()
for message in mailbox.mbox(mbox_file):
if message.is_multipart():
content = '\n'.join(part.get_payload() for part in message.get_payload())
content = content.split('<')[0] # only want text/plain.. Ill split #right before HTML starts
#print content
else:
content = message.get_payload()
idea = message['message-id']
sub = message['subject']
fr = message['from']
date = message['date']
writer.writerow ('ID':idea,......) # CSV writing will work fine
for line in content.splitlines():
line = line.strip()
for pose in searchKeys:
if pose in line:
tmp = line.split(pose)
pmt = tmp[1].split(":")[1]
if next in line !=:
print pose +"\t"+pmt
sleep(1)
csvfile.closed
OUTPUT:
OFFICIAL_POSTAL_ADDRESS =20
Here, the lines are missing..
from file:
OFFICIAL_POSTAL_ADDRESS: =20
London, testarossa street 41
EDIT2:
#Yaniv
Thank you, iam still trying to understand every step, but just wanted to give a comment. I like the idea to work with the list/matrix/vector "key_value_pairs"
The amount of keywords in the emails is ~20 words. Additionally, my values are sometimes line broken by "=".
I was thinking something like:
Search text for Keyword A,
if true:
search text from Keyword A until keyword B
if true:
copy text after A until B
Name_OF_=
Person: Stefan
Adress_
=HOME: London, Maple
Street
45
Company_NAME: MultiVendor
XXVideos
Maybe the HTML from EMAIL.mbox is easier to process?
<tr><td bgcolor=3D"#eeeeee"><font face=3D"Verdana" size=3D"1">
<strong>NAM=
E_REGISTERING_PERSON</strong></font></td><td bgcolor=3D"#eeeeee"><font
fac=e=3D"Verdana" size=3D"1">Stefan </font></td></tr>
But the "=" are still there
should i replace ["="," = "] with "" ?

I would go for a "routine" parsing loop over the input lines, and maintain a current_key and current_value variables, as a value for a certain key in your data might be "annoying", and spread across multiple lines.
I've demonstrated such parsing approach in the code below, with some assumptions regarding your problem. For example, if an input line starts with a whitespace, I assumed it must be the case of such "annoying" value (spread across multiple lines). Such lines would be concatenated into a single value, using some configurable string (the parameter join_lines_using_this). Another assumption is that you might want to strip whitespaces from both keys and values.
Feel free to adapt the code to fit your assumptions on the input, and raise Exceptions whenever they don't hold!
# Note the usage of .strip() in some places, to strip away whitespaces. I assumed you might want that.
def parse_funky_text(text, join_lines_using_this=" "):
key_value_pairs = []
current_key, current_value = None, ""
for line in text.splitlines():
line_split = line.split(':')
if line.startswith(" ") or len(line_split) == 1:
if current_key is None:
raise ValueError("Failed to parse this line, not sure which key it belongs to: %s" % line)
current_value += join_lines_using_this + line.strip()
else:
if current_key is not None:
key_value_pairs.append((current_key, current_value))
current_key, current_value = None, ""
current_key = line_split[0].strip()
# We've just found a new key, so here you might want to perform additional checks,
# e.g. if current_key not in sharedKeys: raise ValueError("Encountered a weird key?! %s in line: %s" % (current_key, line))
current_value = ':'.join(line_split[1:]).strip()
# Don't forget the last parsed key, value
if current_key is not None:
key_value_pairs.append((current_key, current_value))
return key_value_pairs
Example usage:
text = """Name_OF_Person: Stefan
Adress_HOME: London, Maple
Street
45
Company_NAME: MultiVendor
XXVideos"""
parse_funky_text(text)
Will output:
[('Name_OF_Person', 'Stefan'), ('Adress_HOME', 'London, Maple Street 45'), ('Company_NAME', 'MultiVendor XXVideos')]

You indicate in the comments that your input strings from the content should be relatively consistent. If that is the case, and you want to be able to split that string across multiple lines, the easiest thing to do would be to replace \n with spaces and then just parse the single string.
I've intentionally constrained my answer to using just string methods rather than inventing a huge function to do this. Reason: 1) Your process is already complex enough, and 2) your question really boils down to how to process the string data across multiple lines. If that is the case, and the pattern is consistent, this will get this one off job done
content = content.replace('\n', ' ')
Then you can split on each of the boundries in your consistently structured headers.
content = content.split("Name_OF_Person:")[1] #take second element of the list
person = content.split("Adress_HOME:")[0] # take content before "Adress Home"
content = content.split("Adress_HOME:")[1] #take second element of the list
address = content.split("Company_NAME:")[0] # take content before
company = content.split("Adress_HOME:")[1] #take second element of the list (the remainder) which is company
Normally, I would suggest regex. (https://docs.python.org/3.4/library/re.html). Long term, if you need to do this sort of thing again, regex is going to pay dividends on time spend munging data. To make a regex function "cut" across multiple lines, you would use the re.MULTILINE option. So it might endup looking something like re.search('Name_OF_Person:(.*)Adress_HOME:', html_reg_form, re.MULTILINE)

Parsing GenBank to FASTA with yield in Python (x, y)

For now I have tried to define and document my own function to do it, but I am encountering issues with testing the code and I have actually no idea if it is correct. I found some solutions with BioPython, re or other, but I really want to make this work with yield.
#generator for GenBank to FASTA
def parse_GB_to_FASTA (lines):
#set Default label
curr_label = None
#set Default sequence
curr_seq = ""
for line in lines:
#if the line starts with ACCESSION this should be saved as the beginning of the label
if line.startswith('ACCESSION'):
#if the label has already been changed
if curr_label is not None:
#output the label and sequence
yield curr_label, curr_seq
''' if the label starts with ACCESSION, immediately replace the current label with
the next ACCESSION number and continue with the next check'''
#strip the first column and leave the number
curr_label = '>' + line.strip()[12:]
#check for the organism column
elif line.startswith (' ORGANISM'):
#add the organism name to the label line
curr_label = curr_label + " " + line.strip()[12:]
#check if the region of the sequence starts
elif line.startswith ('ORIGIN'):
#until the end of the sequence is reached
while line.startswith ('//') is False:
#get a line without spaces and numbers
curr_seq += line.upper().strip()[12:].translate(None, '1234567890 ')
#if no more lines, then give the last label and sequence
yield curr_label, curr_seq

I often work with very large GenBank files and found (years ago) that the BioPython parsers were too brittle to make it through 100's of thousands of records (at the time), without crashing on an unusual record.
I wrote a pure python(2) function to return the next whole record from an open file, reading in 1k chunks, and leaving the file pointer ready to get the next record. I tied this in with a simple iterator that uses this function, and a GenBank Record class which has a fasta(self) method to get a fasta version.
YMMV, but the function that gets the next record is here as should be pluggable in any iterator scheme you want to use. As far as converting to fasta goes you can use logic similar to your ACCESSION and ORIGIN grabbing above, or you can get the text of sections (like ORIGIN) using:
sectionTitle='ORIGIN'
searchRslt=re.search(r'^(%s.+?)^\S'%sectionTitle,
gbrText,re.MULTILINE | re.DOTALL)
sectionText=searchRslt.groups()[0]
Subsections like ORGANISM, require a left side pad of 5 spaces.
Here's my solution to the main issue:
def getNextRecordFromOpenFile(fHandle):
"""Look in file for the next GenBank record
return text of the record
"""
cSize =1024
recFound = False
recChunks = []
try:
fHandle.seek(-1,1)
except IOError:
pass
sPos = fHandle.tell()
gbr=None
while True:
cPos=fHandle.tell()
c=fHandle.read(cSize)
if c=='':
return None
if not recFound:
locusPos=c.find('\nLOCUS')
if sPos==0 and c.startswith('LOCUS'):
locusPos=0
elif locusPos == -1:
continue
if locusPos>0:
locusPos+=1
c=c[locusPos:]
recFound=True
else:
locusPos=0
if (len(recChunks)>0 and
((c.startswith('//\n') and recChunks[-1].endswith('\n'))
or (c.startswith('\n') and recChunks[-1].endswith('\n//'))
or (c.startswith('/\n') and recChunks[-1].endswith('\n/'))
)):
eorPos=0
else:
eorPos=c.find('\n//\n',locusPos)
if eorPos == -1:
recChunks.append(c)
else:
recChunks.append(c[:(eorPos+4)])
gbrText=''.join(recChunks)
fHandle.seek(cPos-locusPos+eorPos)
return gbrText

Creating a dictionary using python and a .txt file

I have downloaded the following dictionary from Project Gutenberg http://www.gutenberg.org/cache/epub/29765/pg29765.txt (it is 25 MB so if you're on a slow connection avoid clicking the link)
In the file the keywords I am looking for are in uppercases for instance HALLUCINATION, then in the dictionary there are some lines dedicated to the pronunciation which are obsolete for me.
What I want to extract is the definition, indicated by "Defn" and then print the lines. I have came up with this rather ugly 'solution'
def lookup(search):
find = search.upper() # transforms our search parameter all upper letters
output = [] # empty dummy list
infile = open('webster.txt', 'r') # opening the webster file for reading
for line in infile:
for part in line.split():
if (find == part):
for line in infile:
if (line.find("Defn:") == 0): # ugly I know, but my only guess so far
output.append(line[6:])
print output # uncertain about how to proceed
break
Now this of course only prints the first line that comes right after "Defn:". I am new when it comes to manipulate .txt files in Python and therefore clueless about how to proceed. I did read in the line in a tuple and noticed that there are special new line characters.
So I want to somehow tell Python to keep on reading until it runs out of new line characters I suppose, but also that doesn't count for the last line which has to be read.
Could someone please enhance me with useful functions I might could use to solve this problem (with a minimal example would be appreciated).
Example of desired output:
lookup("hallucination")
out: To wander; to go astray; to err; to blunder; -- used of mental
processes. [R.] Byron.
lookup("hallucination")
out: The perception of objects which have no reality, or of \r\n
sensations which have no corresponding external cause, arising from \r\n
disorder or the nervous system, as in delirium tremens; delusion.\r\n
Hallucinations are always evidence of cerebral derangement and are\r\n
common phenomena of insanity. W. A. Hammond.
from text:
HALLUCINATE
Hal*lu"ci*nate, v. i. Etym: [L. hallucinatus, alucinatus, p. p. of
hallucinari, alucinari, to wander in mind, talk idly, dream.]
Defn: To wander; to go astray; to err; to blunder; -- used of mental
processes. [R.] Byron.
HALLUCINATION
Hal*lu`ci*na"tion, n. Etym: [L. hallucinatio cf. F. hallucination.]
1. The act of hallucinating; a wandering of the mind; error; mistake;
a blunder.
This must have been the hallucination of the transcriber. Addison.
2. (Med.)
Defn: The perception of objects which have no reality, or of
sensations which have no corresponding external cause, arising from
disorder or the nervous system, as in delirium tremens; delusion.
Hallucinations are always evidence of cerebral derangement and are
common phenomena of insanity. W. A. Hammond.
HALLUCINATOR
Hal*lu"ci*na`tor, n. Etym: [L.]

Here is a function that returns the first definition:
def lookup(word):
word_upper = word.upper()
found_word = False
found_def = False
defn = ''
with open('dict.txt', 'r') as file:
for line in file:
l = line.strip()
if not found_word and l == word_upper:
found_word = True
elif found_word and not found_def and l.startswith("Defn:"):
found_def = True
defn = l[6:]
elif found_def and l != '':
defn += ' ' + l
elif found_def and l == '':
return defn
return False
print lookup('hallucination')
Explanation: There are four different cases we have to consider.
We haven't found the word yet. We have to compare the current line to the word we are looking for in uppercases. If they are equal, we found the word.
We have found the word, but haven't found the start of the definition. We therefore have to look for a line that starts with Defn:. If we found it, we add the line to the definition (excluding the six characters for Defn:.
We have already found the start of the definition. In that case, we just add the line to the definition.
We have already found the start of definition and the current line is empty. The definition is complete and we return the definition.
If we found nothing, we return False.
Note: There are certain entries, e.g. CRANE, that have multiple definitions. The above code is not able to handle that. It will just return the first definition. However, it is far from easy to code a perfect solution considering the format of the file.

You can split into paragraphs and use the index of the search word and find the first Defn paragraph after:
def find_def(f,word):
import re
with open(f) as f:
lines = f.read()
try:
start = lines.index("{}\r\n".format(word)) # find where our search word is
except ValueError:
return "Cannot find search term"
paras = re.split("\s+\r\n",lines[start:],10) # split into paragraphs using maxsplit = 10 as there are no grouping of paras longer in the definitions
for para in paras:
if para.startswith("Defn:"): # if para startswith Defn: we have what we need
return para # return the para
print(find_def("in.txt","HALLUCINATION"))
Using the whole file returns:
In [5]: print find_def("gutt.txt","VACCINATOR")
Defn: One who, or that which, vaccinates.
In [6]: print find_def("gutt.txt","HALLUCINATION")
Defn: The perception of objects which have no reality, or of
sensations which have no corresponding external cause, arising from
disorder or the nervous system, as in delirium tremens; delusion.
Hallucinations are always evidence of cerebral derangement and are
common phenomena of insanity. W. A. Hammond.
A slightly shorter version:
def find_def(f,word):
import re
with open(f) as f:
lines = f.read()
try:
start = lines.index("{}\r\n".format(word))
except ValueError:
return "Cannot find search term"
defn = lines[start:].index("Defn:")
return re.split("\s+\r\n",lines[start+defn:],1)[0]

From here I learned an easy way to deal with memory mapped files and use them as if they were strings. Then you can use something like this to get the first definition for a term.
def lookup(search):
term = search.upper()
f = open('webster.txt')
s = mmap.mmap(f.fileno(), 0, access=mmap.ACCESS_READ)
index = s.find('\r\n\r\n' + term + '\r\n')
if index == -1:
return None
definition = s.find('Defn:', index) + len('Defn:') + 1
endline = s.find('\r\n\r\n', definition)
return s[definition:endline]
print lookup('hallucination')
print lookup('hallucinate')
Assumptions:
There is at least one definition per term
If there are more than one, only the first is returned

Creating a table which has sentences from a paragraph each on a row with Python

I have an abstract which I've split to sentences in Python. I want to write to 2 tables. One which has the following columns: abstract id (which is the file number that I extracted from my document), sentence id (automatically generated) and each sentence of this abstract on a row.
I would want a table that looks like this
abstractID SentenceID Sentence
a9001755 0000001 Myxococcus xanthus development is regulated by(1st sentence)
a9001755 0000002 The C signal appears to be the polypeptide product (2nd sentence)
and another table NSFClasses having abstractID and nsfOrg.
How to write sentences (each on a row) to table and assign sentenceId as shown above?
This is my code:
import glob;
import re;
import json
org = "NSF Org";
fileNo = "File";
AbstractString = "Abstract";
abstractFlag = False;
abstractContent = []
path = 'awardsFile/awd_1990_00/*.txt';
files = glob.glob(path);
for name in files:
fileA = open(name,'r');
for line in fileA:
if line.find(fileNo)!= -1:
file = line[14:]
if line.find(org) != -1:
nsfOrg = line[14:].split()
print file
print nsfOrg
fileA = open(name,'r')
content = fileA.read().split(':')
abstract = content[len(content)-1]
abstract = abstract.replace('\n','')
abstract = abstract.split();
abstract = ' '.join(abstract)
sentences = abstract.split('.')
print sentences
key = str(len(sentences))
print "Sentences--- "

As others have pointed out, it's very difficult to follow your code. I think this code will do what you want, based on your expected output and what we can see. I could be way off, though, since we can't see the file you are working with. I'm especially troubled by one part of your code that I can't see enough to refactor, but feels obviously wrong. It's marked below.
import glob
for filename in glob.glob('awardsFile/awd_1990_00/*.txt'):
fh = open(filename, 'r')
abstract = fh.read().split(':')[-1]
fh.seek(0) # reset file pointer
# See comments below
for line in fh:
if line.find('File') != -1:
absID = line[14:]
print absID
if line.find('NSF Org') != -1:
print line[14:].split()
# End see comments
fh.close()
concat_abstract = ''.join(abstract.replace('\n', '').split())
for s_id, sentence in enumerate(concat_abstract.split('.')):
# Adjust numeric width arguments to prettify table
print absID.ljust(15),
print '{:06d}'.format(s_id).ljust(15),
print sentence
In that section marked, you are searching for the last occurrence of the strings 'File' and 'NSF Org' in the file (whether you mean to or not because the loop will keep overwriting your variables as long as they occur), then doing something with the 15th character onward of that line. Without seeing the file, it is impossible to say how to do it, but I can tell you there is a better way. It probably involves searching through the whole file as one string (or at least the first part of it if this is in its header) rather than looping over it.
Also, notice how I condensed your code. You store a lot of things in variables that you aren't using at all, and collecting a lot of cruft that spreads the state around. To understand what line N does, I have to keep glancing ahead at line N+5 and back over lines N-34 to N-17 to inspect variables. This creates a lot of action at a distance, which for reasons cited is best to avoid. In the smaller version, you can see how I substituted in string literals in places where they are only used once and called print statements immediately instead of storing the results for later. The results are usually more concise and easily understood.