I'm trying to split string into address, city, state and zip code but unable to split successfully.
Here is my code:
address = "4502 150th Pl SE, Bellevue, WA 98006"
my_add = address.split(',')
street = my_add[0]
city = my_add[1]
state_zip = my_add[2]
state_zip = state_zip
state = state_zip.split(' ')
print(street)
print(city)
print(state_zip)
print(state)
# 4502 150th Pl SE
# Bellevue
# WA 98006
# ['', 'WA', '98006']
I expect that address will be split as:
address : 4502 150th Pl SE
city : Bellevue
state: WA
zipcode: 98006
can anyone help me to find best possible solution. Thanks
If you are sure that a comma is always followed by a space, you can do this:
address = "4502 150th Pl SE, Bellevue, WA 98006"
street, city, state_info = address.split(", ")
state, zipcode = state_info.split(" ")
print("address:", street)
print("city:", city)
print("state:", state)
print("zipcode:", zipcode)
You are getting some extra spaces in there, and since you are splitting on spaces, you end up with my_add[2] containing three elements: an empty string (comes before the first space), your state, and your zip code. You can add .strip() to your code to fix this:
street = my_add[0].strip()
city = my_add[1].strip()
state_zip = my_add[2].strip() # remove extra spaces
state_zip = state_zip.split(' ') # now split on space to get state and zip
state = state_zip[0] # first element: state
zip_code = state_zip[1] # second element: zip
print(street)
print(city)
print(state_zip)
print(state)
print(zip_code)
# 4502 150th Pl SE
# Bellevue
# ['WA', '98006']
# WA
# 98006
I think your solution would be the code below:
address = "4502 150th Pl SE, Bellevue, WA 98006"
my_add = address.split(',')
street = my_add[0]
city = my_add[1]
state_zip = my_add[2]
state_zip_split = state_zip.split(' ')
state_zip = state_zip_split[2]
state = state_zip_split[1]
print("Street: ", street)
print("City: ", city)
print("State Zip: ", state_zip)
print("State: ", state)
You defined state_zip as an array, you needed to split it one more time to get the state and zip code
You can try this.
>>> address = "4502 150th Pl SE, Bellevue, WA 98006"
>>> my_add = address.split(',')
>>> street = my_add[0]
>>> street
'4502 150th Pl SE'
>>> city = my_add[1].strip()
>>> city
'Bellevue'
>>> state_zip = my_add[2].split()[1]
>>> state_zip
'98006'
>>> state = my_add[2].split()[0]
>>> state
'WA'
Hope it helps.
One way to solve this
import re
re.split(', ', address)
*add1, city, state, zipcode = [x for x in re.split('[ ,]', address) if x!='']
add1 = ' '.join(add1)
Related
I am trying to create variables location; contract items; contract code; federal aid using regex on the following text:
PAGE 1
BID OPENING DATE 07/25/18 FROM 0.2 MILES WEST OF ICE HOUSE 07/26/18 CONTRACT NUMBER 03-2F1304 ROAD TO 0.015 MILES WEST OF CONTRACT CODE 'A '
LOCATION 03-ED-50-39.5/48.7 DIVISION HIGHWAY ROAD 44 CONTRACT ITEMS
INSTALL SANDTRAPS AND PULLOUTS FEDERAL AID ACNH-P050-(146)E
PAGE 1
BID OPENING DATE 07/25/18 IN EL DORADO COUNTY AT VARIOUS 07/26/18 CONTRACT NUMBER 03-2H6804 LOCATIONS ALONG ROUTES 49 AND 193 CONTRACT CODE 'C ' LOCATION 03-ED-0999-VAR 13 CONTRACT ITEMS
TREE REMOVAL FEDERAL AID NONE
PAGE 1
BID OPENING DATE 07/25/18 IN LOS ANGELES, INGLEWOOD AND 07/26/18 CONTRACT NUMBER 07-296304 CULVER CITY, FROM I-105 TO PORT CONTRACT CODE 'B '
LOCATION 07-LA-405-R21.5/26.3 ROAD UNDERCROSSING 55 CONTRACT ITEMS
ROADWAY SAFETY IMPROVEMENT FEDERAL AID ACIM-405-3(056)E
This text is from one word file; I'll be looping my code on multiple doc files. In the text above are three location; contract items; contract code; federal aid pairs. But when I use regex to create variables, only the first instance of each pair is included.
The code I have right now is:
# imports
import os
import pandas as pd
import re
import docx2txt
import textract
import antiword
all_bod = []
all_cn = []
all_location = []
all_fedaid = []
all_contractcode = []
all_contractitems = []
all_file = []
text = ' PAGE 1
BID OPENING DATE 07/25/18 FROM 0.2 MILES WEST OF ICE HOUSE 07/26/18 CONTRACT NUMBER 03-2F1304 ROAD TO 0.015 MILES WEST OF CONTRACT CODE 'A '
LOCATION 03-ED-50-39.5/48.7 DIVISION HIGHWAY ROAD 44 CONTRACT ITEMS
INSTALL SANDTRAPS AND PULLOUTS FEDERAL AID ACNH-P050-(146)E
PAGE 1
BID OPENING DATE 07/25/18 IN EL DORADO COUNTY AT VARIOUS 07/26/18 CONTRACT NUMBER 03-2H6804 LOCATIONS ALONG ROUTES 49 AND 193 CONTRACT CODE 'C ' LOCATION 03-ED-0999-VAR 13 CONTRACT ITEMS
TREE REMOVAL FEDERAL AID NONE
PAGE 1
BID OPENING DATE 07/25/18 IN LOS ANGELES, INGLEWOOD AND 07/26/18 CONTRACT NUMBER 07-296304 CULVER CITY, FROM I-105 TO PORT CONTRACT CODE 'B '
LOCATION 07-LA-405-R21.5/26.3 ROAD UNDERCROSSING 55 CONTRACT ITEMS
ROADWAY SAFETY IMPROVEMENT FEDERAL AID ACIM-405-3(056)E'
bod1 = re.search('BID OPENING DATE \s+ (\d+\/\d+\/\d+)', text)
bod2 = re.search('BID OPENING DATE\n\n(\d+\/\d+\/\d+)', text)
if not(bod1 is None):
bod = bod1.group(1)
elif not(bod2 is None):
bod = bod2.group(1)
else:
bod = 'NA'
all_bod.append(bod)
# creating contract number
cn1 = re.search('CONTRACT NUMBER\n+(.*)', text)
cn2 = re.search('CONTRACT NUMBER\s+(.........)', text)
if not(cn1 is None):
cn = cn1.group(1)
elif not(cn2 is None):
cn = cn2.group(1)
else:
cn = 'NA'
all_cn.append(cn)
# location
location1 = re.search('LOCATION \s+\S+', text)
location2 = re.search('LOCATION \n+\S+', text)
if not(location1 is None):
location = location1.group(0)
elif not(location2 is None):
location = location2.group(0)
else:
location = 'NA'
all_location.append(location)
# federal aid
fedaid = re.search('FEDERAL AID\s+\S+', text)
fedaid = fedaid.group(0)
all_fedaid.append(fedaid)
# contract code
contractcode = re.search('CONTRACT CODE\s+\S+', text)
contractcode = contractcode.group(0)
all_contractcode.append(contractcode)
# contract items
contractitems = re.search('\d+ CONTRACT ITEMS', text)
contractitems = contractitems.group(0)
all_contractitems.append(contractitems)
This code parses the only first instance of these variables in the text.
contract-number
location
contract-items
contract-code
federal-aid
03-2F1304
03-ED-50-39.5/48.7
44
A
ACNH-P050-(146)E
But, I am trying to figure out a way to get all possible instances in different observations.
contract-number
location
contract-items
contract-code
federal-aid
03-2F1304
03-ED-50-39.5/48.7
44
A
ACNH-P050-(146)E
03-2H6804
03-ED-0999-VAR
13
C
NONE
07-296304
07-LA-405-R21.5/26.3
55
B
ACIM-405-3(056)E
The all_variables in the code are for looping over multiple word files - we can ignore that if we want :).
Any leads would be super helpful. Thanks so much!
import re
data = []
df = pd.DataFrame()
regex_contract_number =r"(?:CONTRACT NUMBER\s+(?P<contract_number>\S+?)\s)"
regex_location = r"(?:LOCATION\s+(?P<location>\S+))"
regex_contract_items = r"(?:(?P<contract_items>\d+)\sCONTRACT ITEMS)"
regex_federal_aid =r"(?:FEDERAL AID\s+(?P<federal_aid>\S+?)\s)"
regex_contract_code =r"(?:CONTRACT CODE\s+\'(?P<contract_code>\S+?)\s)"
regexes = [regex_contract_number,regex_location,regex_contract_items,regex_federal_aid,regex_contract_code]
for regex in regexes:
for match in re.finditer(regex, text):
data.append(match.groupdict())
df = pd.concat([df, pd.DataFrame(data)], axis=1)
data = []
df
I have been practicing on iterating through dictionary and list in Python.
The source file is a csv document containing Country and Capital. It seems I had to go through 2 for loops for country_dict in order to produce the same print result for country_list and capital_list.
Is there a better way to do this in Python dictionary?
The code:
import csv
path = #Path_to_CSV_File
country_list=[]
capital_list=[]
country_dict={'Country':[],'Capital':[]}
with open(path, mode='r') as data:
for line in csv.DictReader(data):
locals().update(line)
country_dict['Country'].append(Country)
country_dict['Capital'].append(Capital)
country_list.append(Country)
capital_list.append(Capital)
i=14 #set pointer value to the 15th row in the csv document
#---------------------- Iterating through Dictionary using for loops---------------------------
if i >= (len(country_dict['Country'])-1):
print("out of bound")
for count1, element in enumerate(country_dict['Country']):
if count1==i:
print('Country = ' + element)
for count2, element in enumerate(country_dict['Capital']):
if count2==i:
print('Capital = ' + element)
#--------------------------------Direct print for list----------------------------------------
print('Country = ' + country_list[i] + '\nCapital = ' + capital_list[i])
The output:
Country = Djibouti
Capital = Djibouti (city)
Country = Djibouti
Capital = Djibouti (city)
The CSV file content:
Country,Capital
Algeria,Algiers
Angola,Luanda
Benin,Porto-Novo
Botswana,Gaborone
Burkina Faso,Ouagadougou
Burundi,Gitega
Cabo Verde,Praia
Cameroon,Yaounde
Central African Republic,Bangui
Chad,N'Djamena
Comoros,Moroni
"Congo, Democratic Republic of the",Kinshasa
"Congo, Republic of the",Brazzaville
Cote d'Ivoire,Yamoussoukro
Djibouti,Djibouti (city)
Egypt,Cairo
Equatorial Guinea,"Malabo (de jure), Oyala (seat of government)"
Eritrea,Asmara
Eswatini (formerly Swaziland),"Mbabane (administrative), Lobamba (legislative, royal)"
Ethiopia,Addis Ababa
Gabon,Libreville
Gambia,Banjul
Ghana,Accra
Guinea,Conakry
Guinea-Bissau,Bissau
Kenya,Nairobi
Lesotho,Maseru
Liberia,Monrovia
Libya,Tripoli
Madagascar,Antananarivo
Malawi,Lilongwe
Mali,Bamako
Mauritania,Nouakchott
Mauritius,Port Louis
Morocco,Rabat
Mozambique,Maputo
Namibia,Windhoek
Niger,Niamey
Nigeria,Abuja
Rwanda,Kigali
Sao Tome and Principe,São Tomé
Senegal,Dakar
Seychelles,Victoria
Sierra Leone,Freetown
Somalia,Mogadishu
South Africa,"Pretoria (administrative), Cape Town (legislative), Bloemfontein (judicial)"
South Sudan,Juba
Sudan,Khartoum
Tanzania,Dodoma
Togo,Lomé
Tunisia,Tunis
Uganda,Kampala
Zambia,Lusaka
Zimbabwe,Harare
I am not sure if I get your point; Please check out the code.
import csv
path = #Path_to_CSV_File
country_dict={}
with open(path, mode='r') as data:
lines = csv.DictReader(data)
for idx,line in enumerate(lines):
locals().update(line)
country_dict[idx] = {"Country":Country,"Capital":}
i=14 #set pointer value to the 15th row in the csv document
#---------------------- Iterating through Dictionary using for loops---------------------------
country_info = country_dict.get(i)
#--------------------------------Direct print for list----------------------------------------
print('Country = ' + country_info['Country'] + '\nCapital = ' + country_info['Capital'])
I am supposed to get certain information from a .txt file and output it. This is the information I need:
State with the maximum population
State with the minimum population
Average state population
State of Texas population
The DATA looks like:
Alabama
AL
4802982
Alaska
AK
721523
Arizona
AZ
6412700
Arkansas
AR
2926229
California
CA
37341989
This is my code that does not really do anything I need it to do:
def main():
# Open the StateCensus2010.txt file.
census_file = open('StateCensus2010.txt', 'r')
# Read the state name
state_name = census_file.readline()
while state_name != '':
state_abv = census_file.readline()
population = int(census_file.readline())
state_name = state_name.rstrip('\n')
state_abv = state_abv.rstrip('\n')
print('State Name: ', state_name)
print('State Abv.: ', state_abv)
print('Population: ', population)
print()
state_name = census_file.readline()
census_file.close()
main()
All I have it doing is reading the state name, abv and converting the population into an int. I don't need it to do anything of that, however I'm unsure how to do what the assignment is asking. Any hints would definitely be appreciated! I've been trying some things for the past few hours to no avail.
Update:
This is my updated code however I'm receving the following error:
Traceback (most recent call last):
File "main.py", line 13, in <module>
if population > max_population:
TypeError: unorderable types: str() > int()
Code:
with open('StateCensus2010.txt', 'r') as census_file:
while True:
try:
state_name = census_file.readline()
state_abv = census_file.readline()
population = int(census_file.readline())
except IOError:
break
# data processing here
max_population = 0
for population in census_file:
if population > max_population:
max_population = population
print(max_population)
As the data is in consistent order; Statename, State Abv, Population. So you just need to read the lines one time, and display all three 3 information. Below is the sample code.
average = 0.0
total = 0.0
state_min = 999999999999
state_max = 0
statename_min = ''
statename_max = ''
texas_population = 0
with open('StateCensus2010.txt','r') as file:
# split new line, '\n' here means newline
data = file.read().split('\n')
# get the length of the data by using len() method
# there are 50 states in the text file
# each states have 3 information stored,
# state name, state abreviation, population
# that's why length of data which is 150/3 = 50 states
state_total = len(data)/3
# this count is used as an index for the list
count = 0
for i in range(int(state_total)):
statename = data[count]
state_abv = data[count+1]
population = int(data[count+2])
print('Statename : ',statename)
print('State Abv : ',state_abv)
print('Population: ',population)
print()
# sum all states population
total += population
if population > state_max:
state_max = population
statename_max = statename
if population < state_min:
state_min = population
statename_min = statename
if statename == 'Texas':
texas_population = population
# add 3 because we want to jump to next state
# for example the first three lines is Alabama info
# the next three lines is Alaska info and so on
count += 3
# divide the total population with number of states
average = total/state_total
print(str(average))
print('Lowest population state :', statename_min)
print('Highest population state :', statename_max)
print('Texas population :', texas_population)
This problem is pretty easy using pandas.
Code:
states = []
for line in data:
states.append(
dict(state=line.strip(),
abbrev=next(data).strip(),
pop=int(next(data)),
)
)
df = pd.DataFrame(states)
print(df)
print('\nmax population:\n', df.ix[df['pop'].idxmax()])
print('\nmin population:\n', df.ix[df['pop'].idxmin()])
print('\navg population:\n', df['pop'].mean())
print('\nAZ population:\n', df[df.abbrev == 'AZ'])
Test Data:
from io import StringIO
data = StringIO(u'\n'.join([x.strip() for x in """
Alabama
AL
4802982
Alaska
AK
721523
Arizona
AZ
6412700
Arkansas
AR
2926229
California
CA
37341989
""".split('\n')[1:-1]]))
Results:
abbrev pop state
0 AL 4802982 Alabama
1 AK 721523 Alaska
2 AZ 6412700 Arizona
3 AR 2926229 Arkansas
4 CA 37341989 California
max population:
abbrev CA
pop 37341989
state California
Name: 4, dtype: object
min population:
abbrev AK
pop 721523
state Alaska
Name: 1, dtype: object
avg population:
10441084.6
AZ population:
abbrev pop state
2 AZ 6412700 Arizona
Another pandas solution, from the interpreter:
>>> import pandas as pd
>>>
>>> records = [line.strip() for line in open('./your.txt', 'r')]
>>>
>>> df = pd.DataFrame([records[i:i+3] for i in range(0, len(records), 3)],
... columns=['State', 'Code', 'Pop']).dropna()
>>>
>>> df['Pop'] = df['Pop'].astype(int)
>>>
>>> df
State Code Pop
0 Alabama AL 4802982
1 Alaska AK 721523
2 Arizona AZ 6412700
3 Arkansas AR 2926229
4 California CA 37341989
>>>
>>> df.ix[df['Pop'].idxmax()]
State California
Code CA
Pop 37341989
Name: 4, dtype: object
>>>
>>> df.ix[df['Pop'].idxmin()]
State Alaska
Code AK
Pop 721523
Name: 1, dtype: object
>>>
>>> df['Pop'].mean()
10441084.6
>>>
>>> df.ix[df['Code'] == 'AZ' ]
State Code Pop
2 Arizona AZ 6412700
Please try this the earlier code was not python 3 compatible. It supported python 2.7
def extract_data(state):
total_population = 0
for states, stats in state.items():
population = stats.get('population')
state_name = stats.get('state_name')
states = states
total_population = population + total_population
if 'highest' not in vars():
highest = population
higherst_state_name = state_name
highest_state = states
if 'lowest' not in vars():
lowest = population
lowest_state_name = state_name
lowest_state = states
if highest < population:
highest = population
higherst_state_name = state_name
highest_state = states
if lowest > population:
lowest = population
lowest_state_name = state_name
lowest_state = states
print(highest_state, highest)
print(lowest_state, lowest)
print(len(state))
print(int(total_population/len(state)))
print(state.get('TX').get('population'))
def main():
# Open the StateCensus2010.txt file.
census_file = open('states.txt', 'r')
# Read the state name
state_name = census_file.readline()
state = {}
while state_name != '':
state_abv = census_file.readline()
population = int(census_file.readline())
state_name = state_name.rstrip('\n')
state_abv = state_abv.rstrip('\n')
if state_abv in state:
state[state_abv].update({'population': population, 'state_name': state_name})
else:
state.setdefault(state_abv,{'population': population, 'state_name': state_name})
state_name = census_file.readline()
census_file.close()
return state
state=main()
extract_data(state)
My list is formatted like:
gymnastics_school,participant_name,all-around_points_earned
I need to divide it up by schools but keep the scores.
import collections
def main():
names = ["gymnastics_school", "participant_name", "all_around_points_earned"]
Data = collections.namedtuple("Data", names)
data = []
with open('state_meet.txt','r') as f:
for line in f:
line = line.strip()
items = line.split(',')
items[2] = float(items[2])
data.append(Data(*items))
These are examples of how they're set up:
Lanier City Gymnastics,Ben W.,55.301
Lanier City Gymnastics,Alex W.,54.801
Lanier City Gymnastics,Sky T.,51.2
Lanier City Gymnastics,William G.,47.3
Carrollton Boys,Cameron M.,61.6
Carrollton Boys,Zachary W.,58.7
Carrollton Boys,Samuel B.,58.6
La Fayette Boys,Nate S.,63
La Fayette Boys,Kaden C.,62
La Fayette Boys,Cohan S.,59.1
La Fayette Boys,Cooper J.,56.101
La Fayette Boys,Avi F.,53.401
La Fayette Boys,Frederic T.,53.201
Columbus,Noah B.,50.3
Savannah Metro,Levi B.,52.801
Savannah Metro,Taylan T.,52
Savannah Metro,Jacob S.,51.5
SAAB Gymnastics,Dawson B.,58.1
SAAB Gymnastics,Dean S.,57.901
SAAB Gymnastics,William L.,57.101
SAAB Gymnastics,Lex L.,52.501
Suwanee Gymnastics,Colin K.,57.3
Suwanee Gymnastics,Matthew B.,53.201
After processing it should look like:
Lanier City Gymnastics:participants(4)
as it own list
Carrollton Boys(3)
as it own list
La Fayette Boys(6)
etc.
I would recommend putting them in dictionaries:
data = {}
with open('state_meet.txt','r') as f:
for line in f:
line = line.strip()
items = line.split(',')
items[2] = float(items[2])
if items[0] in data:
data[items[0]].append(items[1:])
else:
data[items[0]] = [items[1:]]
Then access schools could be done in the following way:
>>> data['Lanier City Gymnastics']
[['Ben W.',55.301],['Alex W.',54.801],['Sky T'.,51.2],['William G.',47.3]
EDIT:
Assuming you need the whole dataset as a list first, then you want to divide it into smaller lists you can generate the dictionary from the list:
data = []
with open('state_meet.txt','r') as f:
for line in f:
line = line.strip()
items = line.split(',')
items[2] = float(items[2])
data.append(items)
#perform median or other operation on your data
nested_data = {}
for items in data:
if items[0] in data:
data[items[0]].append(items[1:])
else:
data[items[0]] = [items[1:]]
nested_data[item[0]]
When you need to get a subset of a list you can use slicing:
mylist[start:stop:step]
where start, stop and step are optional (see link for more comprehensive introduction)
In the below case i want to match string "Singapore" where "S" should always be capital and rest of the words may be in lower or in uppercase. but in the below string "s" is in lower case and it gets matched in search condition. can any body let me know how to implement this?
import re
st = "Information in sinGapore "
if re.search("S""(?i)(ingapore)" , st):
print "matched"
Singapore => matched
sIngapore => notmatched
SinGapore => matched
SINGAPORE => matched
As commented, the Ugly way would be:
>>> re.search("S[iI][Nn][Gg][Aa][Pp][Oo][Rr][Ee]" , "SingaPore")
<_sre.SRE_Match object at 0x10cea84a8>
>>> re.search("S[iI][Nn][Gg][Aa][Pp][Oo][Rr][Ee]" , "Information in sinGapore")
The more elegant way would be matching Singapore case-insensitive, and then checking that the first letter is S:
reg=re.compile("singapore", re.I)
>>> s="Information in sinGapore"
>>> reg.search(s) and reg.search(s).group()[0]=='S'
False
>>> s="Information in SinGapore"
>>> reg.search(s) and reg.search(s).group()[0]=='S'
True
Update
Following your comment - you could use:
reg.search(s).group().startswith("S")
Instead of:
reg.search(s).group()[0]==("S")
If it seems more readable.
Since you want to set a GV code according to the catched phrase (unique name or several name blank separated, I know that), there must be a step in which the code is choosen in a dictionary according to the catched phrase.
So it's easy to make a profit of this step to perform the test on the first letter (must be uppercased) or the first name in the phrase that no regex is capable of.
I choosed certain conditions to constitute the test. For example, a dot in a first name is not mandatory, but uppercased letters are. These conditions will be easily changed at need.
EDIT 1
import re
def regexize(cntry):
def doot(x):
return '\.?'.join(ch for ch in x) + '\.?'
to_join = []
for c in cntry:
cspl = c.split(' ',1)
if len(cspl)==1: # 'Singapore','Austria',...
to_join.append('(%s)%s'
% (doot(c[0]), doot(c[1:])))
else: # 'Den LMM','LMM Den',....
to_join.append('(%s) +%s'
% (doot(cspl[0]),
doot(cspl[1].strip(' ').lower())))
pattern = '|'.join(to_join).join('()')
return re.compile(pattern,re.I)
def code(X,CNTR,r = regexize):
r = regexize(CNTR)
for ma in r.finditer(X):
beg = ma.group(1).split(' ')[0]
if beg==ma.group(1):
GV = countries[beg[0]+beg[1:].replace('.','').lower()] \
if beg[0].upper()==beg[0] else '- bad match -'
else:
try:
k = (ki for ki in countries.iterkeys()
if beg.replace('.','')==ki.split(' ')[0]).next()
GV = countries[k]
except StopIteration:
GV = '- bad match -'
yield ' {!s:15} {!s:^13}'.format(ma.group(1), GV)
countries = {'Singapore':'SG','Austria':'AU',
'Swiss':'CH','Chile':'CL',
'Den LMM':'DN','LMM Den':'LM'}
s = (' Singapore SIngapore SiNgapore SinGapore'
' SI.Ngapore SIngaPore SinGaporE SinGAPore'
' SINGaporE SiNg.aPoR singapore sIngapore'
' siNgapore sinGapore sINgap.ore sIngaPore'
' sinGaporE sinGAPore sINGaporE siNgaPoRe'
' Austria Aus.trIA aUSTria AUSTRiA'
' Den L.M.M Den Lm.M DEn Lm.M.'
' DEN L.MM De.n L.M.M. Den LmM'
' L.MM DEn LMM DeN LM.m Den')
print '\n'
print '\n'.join(res for res in code(s,countries))
EDIT 2
I improved the code. It's shorter and more readable.
The instruction assert(.....] is to verify that the keys of the dictionaru are well formed for the purpose.
import re
def doot(x):
return '\.?'.join(ch for ch in x) + '\.?'
def regexize(labels,doot=doot,
wg2 = '(%s) *( %s)',wnog2 = '(%s)(%s)',
ri = re.compile('(.(?!.*? )|[^ ]+)( ?) *(.+\Z)')):
to_join = []
modlabs = {}
for K in labels.iterkeys():
g1,g2,g3 = ri.match(K).groups()
to_join.append((wg2 if g2 else wnog2)
% (doot(g1), doot(g3.lower())))
modlabs[g1+g2+g3.lower()] = labels[K]
return (re.compile('|'.join(to_join), re.I), modlabs)
def code(X,labels,regexize = regexize):
reglab,modlabs = regexize(labels)
for ma in reglab.finditer(X):
a,b = tuple(x for x in ma.groups() if x)
k = (a + b.lower()).replace('.','')
GV = modlabs[k] if k in modlabs else '- bad match -'
yield ' {!s:15} {!s:^13}'.format(a+b, GV)
countries = {'Singapore':'SG','Austria':'AU',
'Swiss':'CH','Chile':'CL',
'Den LMM':'DN','LMM Den':'LM'}
assert(all('.' not in k and
(k.count(' ')==1 or k[0].upper()==k[0])
for k in countries))
s = (' Singapore SIngapore SiNgapore SinGapore'
' SI.Ngapore SIngaPore SinGaporE SinGAPore'
' SINGaporE SiNg.aPoR singapore sIngapore'
' siNgapore sinGapore sINgap.ore sIngaPore'
' sinGaporE sinGAPore sINGaporE siNgaPoRe'
' Austria Aus.trIA aUSTria AUSTRiA'
' Den L.M.M Den Lm.M DEn Lm.M.'
' DEN L.MM De.n L.M.M. Den LmM'
' L.MM DEn LMM DeN LM.m Den')
print '\n'.join(res for res in code(s,countries))
You could write a simple lambda to generate the ugly-but-all-re-solution:
>>> leading_cap_re = lambda s: s[0].upper() + ''.join('[%s%s]' %
(c.upper(),c.lower())
for c in s[1:])
>>> leading_cap_re("Singapore")
'S[Ii][Nn][Gg][Aa][Pp][Oo][Rr][Ee]'
For multi-word cities, define a string-splitting version:
>>> leading_caps_re = lambda s : r'\s+'.join(map(leading_cap_re,s.split()))
>>> print leading_caps_re('Kuala Lumpur')
K[Uu][Aa][Ll][Aa]\s+L[Uu][Mm][Pp][Uu][Rr]
Then your code could just be:
if re.search(leading_caps_re("Singapore") , st):
...etc...
and the ugliness of the RE would be purely internal.
interestingly
/((S)((?i)ingapore))/
Does the right thing in perl but doesn't seem to work as needed in python. To be fair the python docs spell it out clearly, (?i) alters the whole regexp
This is the BEST answer:
(?-i:S)(?i)ingapore
ClickHere for proof: