Develop Reference

Saving file format after editing it with ConfigParser

i am using ConfigParser to write some modification in a configuration file, basically what i am doing is :
retrieve my urls from an api
write them in my config file
but after the edit, i noticed that the file format has changed :
Before the edit :
[global_tags]
[agent]
interval = "10s"
round_interval = true
metric_batch_size = 10000
[[inputs.cpu]]
percpu = true
totalcpu = true
[[inputs.prometheus]]
urls= []
interval = "140s"
[inputs.prometheus.tags]
exp = "exp"
After the edit :
[global_tags]
[agent]
interval = "10s"
round_interval = true
metric_batch_size = 10000
[[inputs.cpu]
percpu = true
totalcpu = true
[[inputs.prometheus]
interval = "140s"
response_timeout = "120s"
[inputs.prometheus.tags]
exp = "snmp"
the offset changed and all the comments that were in the file has been deleted, my code :
edit = configparser.ConfigParser(strict=False, allow_no_value=True, empty_lines_in_values=False)
edit.read("file.conf")
edit.set("[section]", "urls", str(urls))
print(edit)
# Write changes back to file
with open('file.conf', 'w') as configfile:
edit.write(configfile)
I have already tried : SafeConfigParser, RawConfigParser but it doesn't work.
when i do a print(edit.section()), here is what i get : ['global_tags', 'agent', '[inputs.cpu', , '[inputs.prometheus', 'inputs.prometheus.tags']
Is there any help please ?

Here's an example of a "filter" parser that retains all other formatting but changes the urls line in the agent section if it comes across it:
import io
def filter_config(stream, item_filter):
"""
Filter a "config" file stream.
:param stream: Text stream to read from.
:param item_filter: Filter function; takes a section and a line and returns a filtered line.
:return: Yields (possibly) filtered lines.
"""
current_section = None
for line in stream:
stripped_line = line.strip()
if stripped_line.startswith('['):
current_section = stripped_line.strip('[]')
elif not stripped_line.startswith("#") and " = " in stripped_line:
line = item_filter(current_section, line)
yield line
def urls_filter(section, line):
if section == "agent" and line.strip().startswith("urls = "):
start, sep, end = line.partition(" = ")
return start + sep + "hi there..."
return line
# Could be a disk file, just using `io.StringIO()` for self-containedness here
config_file = io.StringIO("""
[global_tags]
[agent]
interval = "10s"
round_interval = true
metric_batch_size = 10000
# HELLO! THIS IS A COMMENT!
metric_buffer_limit = 100000
urls = ""
[other]
urls = can't touch this!!!
""")
for line in filter_config(config_file, urls_filter):
print(line, end="")
The output is
[global_tags]
[agent]
interval = "10s"
round_interval = true
metric_batch_size = 10000
# HELLO! THIS IS A COMMENT!
metric_buffer_limit = 100000
urls = hi there...
[other]
urls = can't touch this!!!
so you can see all comments and (mis-)indentation was preserved.

The problem is that you're passing brackets with the section name, which is unnecessary:
edit.set("[section]", "urls", str(urls))
See this example from the documentation:
import configparser
config = configparser.RawConfigParser()
# Please note that using RawConfigParser's set functions, you can assign
# non-string values to keys internally, but will receive an error when
# attempting to write to a file or when you get it in non-raw mode. Setting
# values using the mapping protocol or ConfigParser's set() does not allow
# such assignments to take place.
config.add_section('Section1')
config.set('Section1', 'an_int', '15')
config.set('Section1', 'a_bool', 'true')
config.set('Section1', 'a_float', '3.1415')
config.set('Section1', 'baz', 'fun')
config.set('Section1', 'bar', 'Python')
config.set('Section1', 'foo', '%(bar)s is %(baz)s!')
# Writing our configuration file to 'example.cfg'
with open('example.cfg', 'w') as configfile:
config.write(configfile)
But, anyway, it won't preserve the identation, nor will it support nested sections; you could try the YAML format, which does allow to use indentation to separate nested sections, but it won't keep the exact same indentation when saving, but, do you really need it to be the exact same? Anyway, there are various configuration formats out there, you should study them to see what fits your case better.

python-ldap unable to do any basic search queries on open server

I have been trying to do some basic search queries, but I am unable to connect to an open LDAP server regardless. I tried a couple of servers, and none of them worked. I used Apache Directory Studio to make sure that the keyword was there but it did not work either way. I tried a variety of different code from different sources.
This was the first one I used
:
https://www.linuxjournal.com/article/6988
import ldap
keyword = "boyle"
def main():
server = "ldap.forumsys.com"
username = "cn=read-only-admin,dc=example,dc=com"
password = "password"
try:
l = ldap.open(server)
l.simple_bind_s(username,password)
print "Bound to server . . . "
l.protocol_version = ldap.VERSION3
print "Searching . . ."
mysearch (l,keyword)
except ldap.LDAPError:
print "Couldnt connect"
def mysearch(l, keyword):
base = ""
scope = ldap.SCOPE_SUBTREE
filter = "cn=" + "*" + keyword + "*"
retrieve_attributes = None
count = 0
result_set = []
timeout = 0
try:
result_id = l.search(base, scope, filter, retrieve_attributes)
while l != 1:
result_id = l.search(base, scope,filter, retrieve_attributes)
result_type, result_data = l.result(result_id, timeout)
if result_data == []:
break
else:
if result_type == ldap.RES_SEARCH_ENTRY:
result_set.append(result_data)
if len (result_set = 0):
print "No Results"
for i in range (len(result_set)):
for entry in result_set[i]:
try:
name = entry[1]['cn'][0]
mail = entry[1]['mail'][0]
#phone = entry[1]['telephonenumber'][0]
#desc = entry[1]['description'][0]
count = count + 1
print name + mail
except:
pass
except ldap.LDAPError, error_message:
print error_message
main()
Every time I ran this program, I received an error
{'desc': u"No such object"}
I also tried this
import ldap
try:
l = ldap.open("ldap.example.com")
except ldap.LDAPError, e:
print e
base_dn = "cn=read-only-admin,dc=example,dc=com"
search_scope = ldap.SCOPE_SUBTREE
retrieve_attributes = None
search_filter = "uid=myuid"
try:
l_search = l.search(base_dn, search_scope, search_filter, retrieve_attributes)
result_status, result_data = l.result(l_search, 0)
print result_data
except ldap.LDAPError, e:
print e
The error on this one was
{'desc': u"Can't contact LDAP server"}
I spent about 5 hours trying to figure this out. I would really appreciate it if you guys could give me some advice. Thanks.

There are several bogus things in there.
I will only comment your first code sample because it can be used by anyone with that public LDAP server.
l = ldap.open(server)
Function ldap.open() is deprecated since many years. You should use function ldap.initialize() with LDAP URI as argument instead like this:
l = ldap.initialize("ldap://ldap.forumsys.com")
l_search = l.search(..)
This is the asynchronous method which just returns a message ID (int) of the underlying OpenLDAP C API (libldap). It's needed if you want to retrieve extended controls returned by the LDAP server along with search results. Is that what you want?
As a beginner you probably want to use the simpler method LDAPObject.search_s() which immediately returns a list of (DN, entry) 2-tuples.
See also: python-ldap -- Sending LDAP requests
while l != 1
This does not make sense at all because l is your LDAPObject instance (LDAP connection object). Note that LDAPObject.search() would raise an exception if it gets an Integer error code from OpenLDAP's libldap. No need to do C-style error checks at this level.
filter = "cn=" + "" + keyword + ""
If keyword can be arbitrary input this is a prone to LDAP injection attacks. Don't do that.
For adding arbitrary input into a LDAP filter use function ldap.filter.escape_filter_chars() to properly escape special characters. Also avoid using variable name filter because it's the name of a built-in Python function and properly enclose the filter in parentheses.
Better example:
ldap_filter = "(cn=*%s*)" % (ldap.filter.escape_filter_chars(keyword))
base = ""
The correct search base you have to use is:
base = "dc=example,dc=com"
Otherwise ldap.NO_SUCH_OBJECT is raised.
So here's a complete example:
import pprint
import ldap
from ldap.filter import escape_filter_chars
BINDDN = "cn=read-only-admin,dc=example,dc=com"
BINDPW = "password"
KEYWORD = "boyle"
ldap_conn = ldap.initialize("ldap://ldap.forumsys.com")
ldap_conn.simple_bind_s(BINDDN, BINDPW)
ldap_filter = "(cn=*%s*)" % (ldap.filter.escape_filter_chars(KEYWORD))
ldap_results = ldap_conn.search_s(
"dc=example,dc=com",
ldap.SCOPE_SUBTREE,
ldap_filter,
)
pprint.pprint(ldap_results)

Python 3.6 script surprisingly slow on Windows 10 but not on Ubuntu 17.10

I recently had to write a challenge for a company that was to merge 3 CSV files into one based on the first attribute of each (the attributes were repeating in all files).
I wrote the code and sent it to them, but they said it took 2 minutes to run. That was funny because it ran for 10 seconds on my machine. My machine had the same processor, 16GB of RAM, and had an SSD as well. Very similar environments.
I tried optimising it and resubmitted it. This time they said they ran it on an Ubuntu machine and got 11 seconds, while the code ran for 100 seconds on the Windows 10 still.
Another peculiar thing was that when I tried profiling it with the Profile module, it went on forever, had to terminate after 450 seconds. I moved to cProfiler and it recorded it for 7 seconds.
EDIT: The exact formulation of the problem is
Write a console program to merge the files provided in a timely and
efficient manner. File paths should be supplied as arguments so that
the program can be evaluated on different data sets. The merged file
should be saved as CSV; use the id column as the unique key for
merging; the program should do any necessary data cleaning and error
checking.
Feel free to use any language you’re comfortable with – only
restriction is no external libraries as this defeats the purpose of
the test. If the language provides CSV parsing libraries (like
Python), please avoid using them as well as this is a part of the
test.
Without further ado here's the code:
#!/usr/bin/python3
import sys
from multiprocessing import Pool
HEADERS = ['id']
def csv_tuple_quotes_valid(a_tuple):
"""
checks if a quotes in each attribute of a entry (i.e. a tuple) agree with the csv format
returns True or False
"""
for attribute in a_tuple:
in_quotes = False
attr_len = len(attribute)
skip_next = False
for i in range(0, attr_len):
if not skip_next and attribute[i] == '\"':
if i < attr_len - 1 and attribute[i + 1] == '\"':
skip_next = True
continue
elif i == 0 or i == attr_len - 1:
in_quotes = not in_quotes
else:
return False
else:
skip_next = False
if in_quotes:
return False
return True
def check_and_parse_potential_tuple(to_parse):
"""
receives a string and returns an array of the attributes of the csv line
if the string was not a valid csv line, then returns False
"""
a_tuple = []
attribute_start_index = 0
to_parse_len = len(to_parse)
in_quotes = False
i = 0
#iterate through the string (line from the csv)
while i < to_parse_len:
current_char = to_parse[i]
#this works the following way: if we meet a quote ("), it must be in one
#of five cases: "" | ", | ," | "\0 | (start_of_string)"
#in case we are inside a quoted attribute (i.e. "123"), then commas are ignored
#the following code also extracts the tuples' attributes
if current_char == '\"':
if i == 0 or (to_parse[i - 1] == ',' and not in_quotes): # (start_of_string)" and ," case
#not including the quote in the next attr
attribute_start_index = i + 1
#starting a quoted attr
in_quotes = True
elif i + 1 < to_parse_len:
if to_parse[i + 1] == '\"': # "" case
i += 1 #skip the next " because it is part of a ""
elif to_parse[i + 1] == ',' and in_quotes: # ", case
a_tuple.append(to_parse[attribute_start_index:i].strip())
#not including the quote and comma in the next attr
attribute_start_index = i + 2
in_quotes = False #the quoted attr has ended
#skip the next comma - we know what it is for
i += 1
else:
#since we cannot have a random " in the middle of an attr
return False
elif i == to_parse_len - 1: # "\0 case
a_tuple.append(to_parse[attribute_start_index:i].strip())
#reached end of line, so no more attr's to extract
attribute_start_index = to_parse_len
in_quotes = False
else:
return False
elif current_char == ',':
if not in_quotes:
a_tuple.append(to_parse[attribute_start_index:i].strip())
attribute_start_index = i + 1
i += 1
#in case the last attr was left empty or unquoted
if attribute_start_index < to_parse_len or (not in_quotes and to_parse[-1] == ','):
a_tuple.append(to_parse[attribute_start_index:])
#line ended while parsing; i.e. a quote was openned but not closed
if in_quotes:
return False
return a_tuple
def parse_tuple(to_parse, no_of_headers):
"""
parses a string and returns an array with no_of_headers number of headers
raises an error if the string was not a valid CSV line
"""
#get rid of the newline at the end of every line
to_parse = to_parse.strip()
# return to_parse.split(',') #if we assume the data is in a valid format
#the following checking of the format of the data increases the execution
#time by a factor of 2; if the data is know to be valid, uncomment 3 lines above here
#if there are more commas than fields, then we must take into consideration
#how the quotes parse and then extract the attributes
if to_parse.count(',') + 1 > no_of_headers:
result = check_and_parse_potential_tuple(to_parse)
if result:
a_tuple = result
else:
raise TypeError('Error while parsing CSV line %s. The quotes do not parse' % to_parse)
else:
a_tuple = to_parse.split(',')
if not csv_tuple_quotes_valid(a_tuple):
raise TypeError('Error while parsing CSV line %s. The quotes do not parse' % to_parse)
#if the format is correct but more data fields were provided
#the following works faster than an if statement that checks the length of a_tuple
try:
a_tuple[no_of_headers - 1]
except IndexError:
raise TypeError('Error while parsing CSV line %s. Unknown reason' % to_parse)
#this replaces the use my own hashtables to store the duplicated values for the attributes
for i in range(1, no_of_headers):
a_tuple[i] = sys.intern(a_tuple[i])
return a_tuple
def read_file(path, file_number):
"""
reads the csv file and returns (dict, int)
the dict is the mapping of id's to attributes
the integer is the number of attributes (headers) for the csv file
"""
global HEADERS
try:
file = open(path, 'r');
except FileNotFoundError as e:
print("error in %s:\n%s\nexiting...")
exit(1)
main_table = {}
headers = file.readline().strip().split(',')
no_of_headers = len(headers)
HEADERS.extend(headers[1:]) #keep the headers from the file
lines = file.readlines()
file.close()
args = []
for line in lines:
args.append((line, no_of_headers))
#pool is a pool of worker processes parsing the lines in parallel
with Pool() as workers:
try:
all_tuples = workers.starmap(parse_tuple, args, 1000)
except TypeError as e:
print('Error in file %s:\n%s\nexiting thread...' % (path, e.args))
exit(1)
for a_tuple in all_tuples:
#add quotes to key if needed
key = a_tuple[0] if a_tuple[0][0] == '\"' else ('\"%s\"' % a_tuple[0])
main_table[key] = a_tuple[1:]
return (main_table, no_of_headers)
def merge_files():
"""
produces a file called merged.csv
"""
global HEADERS
no_of_files = len(sys.argv) - 1
processed_files = [None] * no_of_files
for i in range(0, no_of_files):
processed_files[i] = read_file(sys.argv[i + 1], i)
out_file = open('merged.csv', 'w+')
merged_str = ','.join(HEADERS)
all_keys = {}
#this is to ensure that we include all keys in the final file.
#even those that are missing from some files and present in others
for processed_file in processed_files:
all_keys.update(processed_file[0])
for key in all_keys:
merged_str += '\n%s' % key
for i in range(0, no_of_files):
(main_table, no_of_headers) = processed_files[i]
try:
for attr in main_table[key]:
merged_str += ',%s' % attr
except KeyError:
print('NOTE: no values found for id %s in file \"%s\"' % (key, sys.argv[i + 1]))
merged_str += ',' * (no_of_headers - 1)
out_file.write(merged_str)
out_file.close()
if __name__ == '__main__':
# merge_files()
import cProfile
cProfile.run('merge_files()')
# import time
# start = time.time()
# print(time.time() - start);
Here is the profiler report I got on my Windows.
EDIT: The rest of the csv data provided is here. Pastebin was taking too long to process the files, so...
It might not be the best code and I know that, but my question is what slows down Windows so much that doesn't slow down an Ubuntu? The merge_files() function takes the longest, with 94 seconds just for itself, not including the calls to other functions. And there doesn't seem to be anything too obvious to me for why it is so slow.
Thanks
EDIT: Note: We both used the same dataset to run the code with.

It turns out that Windows and Linux handle very long strings differently. When I moved the out_file.write(merged_str) inside the outer for loop (for key in all_keys:) and stopped appending to merged_str, it ran for 11 seconds as expected. I don't have enough knowledge on either of the OS's memory management systems to be able to give a prediction on why it is so different.
But I would say that the way that the second one (the Windows one) is the more fail-safe method because it is unreasonable to keep a 30 MB string in memory. It just turns out that Linux sees that and doesn't always try to keep the string in cache, or to rebuild it every time.
Funny enough, initially I did run it a few times on my Linux machine with these same writing strategies, and the one with the large string seemed to go faster, so I stuck with it. I guess you never know.
Here's the modified code
for key in all_keys:
merged_str = '%s' % key
for i in range(0, no_of_files):
(main_table, no_of_headers) = processed_files[i]
try:
for attr in main_table[key]:
merged_str += ',%s' % attr
except KeyError:
print('NOTE: no values found for id %s in file \"%s\"' % (key, sys.argv[i + 1]))
merged_str += ',' * (no_of_headers - 1)
out_file.write(merged_str + '\n')
out_file.close()

When I run your solution on Ubuntu 16.04 with the three given files, it seems to take ~8 seconds to complete. The only modification I made was to uncomment the timing code at the bottom and use it.
$ python3 dimitar_merge.py file1.csv file2.csv file3.csv
NOTE: no values found for id "aaa5d09b-684b-47d6-8829-3dbefd608b5e" in file "file2.csv"
NOTE: no values found for id "38f79a49-4357-4d5a-90a5-18052ef03882" in file "file2.csv"
NOTE: no values found for id "766590d9-4f5b-4745-885b-83894553394b" in file "file2.csv"
8.039648056030273
$ python3 dimitar_merge.py file1.csv file2.csv file3.csv
NOTE: no values found for id "38f79a49-4357-4d5a-90a5-18052ef03882" in file "file2.csv"
NOTE: no values found for id "766590d9-4f5b-4745-885b-83894553394b" in file "file2.csv"
NOTE: no values found for id "aaa5d09b-684b-47d6-8829-3dbefd608b5e" in file "file2.csv"
7.78482985496521
I rewrote my first attempt without using csv from the standard library and am now getting times of ~4.3 seconds.
$ python3 lettuce_merge.py file1.csv file2.csv file3.csv
4.332579612731934
$ python3 lettuce_merge.py file1.csv file2.csv file3.csv
4.305467367172241
$ python3 lettuce_merge.py file1.csv file2.csv file3.csv
4.27345871925354
This is my solution code (lettuce_merge.py):
from collections import defaultdict
def split_row(csv_row):
return [col.strip('"') for col in csv_row.rstrip().split(',')]
def merge_csv_files(files):
file_headers = []
merged_headers = []
for i, file in enumerate(files):
current_header = split_row(next(file))
unique_key, *current_header = current_header
if i == 0:
merged_headers.append(unique_key)
merged_headers.extend(current_header)
file_headers.append(current_header)
result = defaultdict(lambda: [''] * (len(merged_headers) - 1))
for file_header, file in zip(file_headers, files):
for line in file:
key, *values = split_row(line)
for col_name, col_value in zip(file_header, values):
result[key][merged_headers.index(col_name) - 1] = col_value
file.close()
quotes = '"{}"'.format
with open('lettuce_merged.csv', 'w') as f:
f.write(','.join(quotes(a) for a in merged_headers) + '\n')
for key, values in result.items():
f.write(','.join(quotes(b) for b in [key] + values) + '\n')
if __name__ == '__main__':
from argparse import ArgumentParser, FileType
from time import time
parser = ArgumentParser()
parser.add_argument('files', nargs='*', type=FileType('r'))
args = parser.parse_args()
start_time = time()
merge_csv_files(args.files)
print(time() - start_time)
I'm sure this code could be optimized even further but sometimes just seeing another way to solve a problem can help spark new ideas.

Why can't I open a file from a variable made from several concatenating strings in Python?

So I wrote this code
spec = raw_input("Enter the specimen number: ")
naorimp = raw_input("Native or Implant (N/I)? ")
trial = raw_input("Trial number: ")
typana = raw_input("What do you want to analyze (contact area[CA]/contact pressure[CP])? ")
try :
if typana.lower() == "cp" :
naorimp = naorimp.upper()
TSfilnm = 'pressure'+spec+naorimp.upper()+trial+'.txt'
else :
naorimp = naorimp.upper()
TSfilnm = 'area'+spec+naorimp+trial+'.txt'
TSfile = open(TSfilnm, 'r')
myofilnm = 'accelerometer'+spec+naorim.upper()+trial+'.txt'
print myofilnm
myofile = open(myofilnm, 'r')
except :
print "File could not be found."
print "Please re-run the program."
exit()
print "OK"
I want to open a file based on user's input and several parameters (specimen no., native or implant, trial no., and type of analysis.) The file is already in the same folder as the python file code. But when I run the program I always end up with except statements (File could not be found. Please re-run the program). I have double-checked the real file name and the string inside the TSfilnm variable, and they are the same. However, the TSfile could not be executed.
P.S. The file name in my folder is: pressure3N1.txt, area3N1.txt, accelerometer3N1.txt

You are missing a p in the variable name in this line
myofilnm = 'accelerometer'+spec+naorim.upper()+trial+'.txt'
should be
myofilnm = 'accelerometer'+spec+naorimp.upper()+trial+'.txt'
Also don't use 'except' alone during development, it will only hide errors like in this case. It's better to do something like.
import sys
try:
#Your_code_here
except:
print sys.exc_info()[1]
#Any other code you wanna run

Python - Changing File Object within function

Sorry - My questions is how can I change a file object within a function from a different function?
I've been trying to work out this error in my first python script for too long now, Dr Google and the forums aren't helping me too much, but I'm hoping you can.
I have a looping function that generates alot of data and I would like to output it to a text file, and create a new text file after the third loop.
I have 2 functions defined, one to create the data hashes, the other to create the new files.
The new files are being created as expected (aaa.txt, baa.txt...etc) but the "hashit" function only ever writes to the first file (aaa.txt) even though the others are being created.
I have tried fo.close() fo.flush(), as well as referencing fo in the functions but can't seem to make it work. Also I've moved the fo.write from the function to the main body.
I have included a cut down version of the code that I've been using to troubleshoot this issue, the real one has several more loops increasing the string length.
Thanks in advance
import smbpasswd, hashlib
base = '''abcdefghijklmnopqrstuvwxyz '''
# base length 95
print(base)
baselen = len(base)
name = 'aaa.txt'
fo = open(name, "w")
print "Name of the file: ", fo.name
print "Closed or not : ", fo.closed
print "Opening mode : ", fo.mode
print "Softspace flag : ", fo.softspace
pw01 = 0
pw02 = 0
pw03 = 0
def hashit(passwd):
#2
# Need to install module
# sudo apt-get install python-smbpasswd
hex_dig_lm = smbpasswd.lmhash(passwd)
hex_dig_ntlm = smbpasswd.nthash(passwd)
#print '%s:%s' % smbpasswd.hash(passwd)
hash_md5 = hashlib.md5(passwd)
hex_dig_md5 = hash_md5.hexdigest()
print(passwd)
print(hex_dig_lm)
print(hex_dig_ntlm)
print(hex_dig_md5)
hashstring = passwd +","+ hex_dig_lm +","+ hex_dig_md5 + '\n'
fo.write(hashstring);
def newfile(name):
fo.flush()
fo = open(name, "a")
print("-------newfile------")
print "Name of the file: ", fo.name
print "Closed or not : ", fo.closed
print('NewFile : ' + name)
raw_input("\n\nPress the enter key to exit.")
# add 3rd digit
while (pw03 < baselen):
pwc03 = base[pw03]
name = pwc03 + 'aa.txt'
fo.close
newfile(name);
pw03 += 1
while (pw02 < baselen):
pwc02 = base[pw02]
pw02 += 1
while (pw01 < baselen):
pwc01 = base[pw01]
pw01 += 1
passwd = pwc03 + pwc02 + pwc01
hashit(passwd);
else:
pw01 = 0
else:
pw02 = 0
else:
pw03 = 0

In your newfile() function, add this line first:
global fo