Develop Reference

How to extract URL from a redirect URL using regex in Python?

I have the following test_string from which I need to obtain the actual URL.
Test string (partly shown):
An experimental and modeling study of autoignition characteristics of
butanol/diesel blends over wide temperature ranges
<http://scholar.google.com/scholar_url?url=3Dhttps://www.sciencedirect.com/=
science/article/pii/S0010218020301346&hl=3Den&sa=3DX&d=3D448628313728630325=
1&scisig=3DAAGBfm26Wh2koXdeGZkQxzZbenQYFPytLQ&nossl=3D1&oi=3Dscholaralrt&hi=
st=3Dv2Y_3P0AAAAJ:17949955323429043383:AAGBfm1nUe-t2q_4mKFiHSHFEAo0A4rRSA>
Y Qiu, W Zhou, Y Feng, S Wang, L Yu, Z Wu, Y Mao=E2=80=A6 - Combustion and =
Flame,
2020
Desired output for part of test_string
https://www.sciencedirect.com/science/article/pii/S0010218020301346
I have been trying to obtain this with the MWE given below applied to many strings, but it gives only one URL.
MWE
from urlparse import urlparse, parse_qs
import re
from re import search
test_string = '''
Production, Properties, and Applications of ALPHA-Terpineol
<http://scholar.google.com/scholar_url?url=https://link.springer.com/content/pdf/10.1007/s11947-020-02461-6.pdf&hl=en&sa=X&d=12771069332921982368&scisig=AAGBfm1tFjLUm7GV1DRnuYCzvR4uGWq9Cg&nossl=1&oi=scholaralrt&hist=v2Y_3P0AAAAJ:17949955323429043383:AAGBfm1nUe-t2q_4mKFiHSHFEAo0A4rRSA>
A Sales, L de Oliveira Felipe, JL Bicas
Abstract ALPHA-Terpineol (CAS No. 98-55-5) is a tertiary monoterpenoid
alcohol widely
and commonly used in the flavors and fragrances industry for its sensory
properties.
It is present in different natural sources, but its production is mostly
based on ...
Save
<http://scholar.google.com/citations?update_op=email_library_add&info=oB2z7uTzO7EJ&citsig=AMD79ooAAAAAYLfmix3sQyUWnFrHeKYZxuK31qlqlbCh&hl=en>
Twitter
<http://scholar.google.com/scholar_share?hl=en&oi=scholaralrt&ss=tw&url=https://link.springer.com/content/pdf/10.1007/s11947-020-02461-6.pdf&rt=Production,+Properties,+and+Applications+of+%CE%B1-Terpineol&scisig=AAGBfm0yXFStqItd97MUyPT5nRKLjPIK6g>
Facebook
<http://scholar.google.com/scholar_share?hl=en&oi=scholaralrt&ss=fb&url=https://link.springer.com/content/pdf/10.1007/s11947-020-02461-6.pdf&rt=Production,+Properties,+and+Applications+of+%CE%B1-Terpineol&scisig=AAGBfm0yXFStqItd97MUyPT5nRKLjPIK6g>
An experimental and modeling study of autoignition characteristics of
butanol/diesel blends over wide temperature ranges
<http://scholar.google.com/scholar_url?url=3Dhttps://www.sciencedirect.com/=
science/article/pii/S0010218020301346&hl=3Den&sa=3DX&d=3D448628313728630325=
1&scisig=3DAAGBfm26Wh2koXdeGZkQxzZbenQYFPytLQ&nossl=3D1&oi=3Dscholaralrt&hi=
st=3Dv2Y_3P0AAAAJ:17949955323429043383:AAGBfm1nUe-t2q_4mKFiHSHFEAo0A4rRSA>
Y Qiu, W Zhou, Y Feng, S Wang, L Yu, Z Wu, Y Mao=E2=80=A6 - Combustion and =
Flame,
2020
Butanol/diesel blend is considered as a very promising alternative fuel
with
agreeable combustion and emission performance in engines. This paper
intends to
further investigate its autoignition characteristics with the combination
of a heated =E2=80=A6
[image: Save]
<http://scholar.google.com/citations?update_op=3Demail_library_add&info=3DE=
27Gd756Qj4J&citsig=3DAMD79ooAAAAAYImDxwWCwd5S5xIogWp9RTavFRMtTDgS&hl=3Den>
[image:
Twitter]
<http://scholar.google.com/scholar_share?hl=3Den&oi=3Dscholaralrt&ss=3Dtw&u=
rl=3Dhttps://www.sciencedirect.com/science/article/pii/S0010218020301346&rt=
=3DAn+experimental+and+modeling+study+of+autoignition+characteristics+of+bu=
tanol/diesel+blends+over+wide+temperature+ranges&scisig=3DAAGBfm19DOLNm3-Fl=
WaO0trAxZkeidxYWg>
[image:
Facebook]
<http://scholar.google.com/scholar_share?hl=3Den&oi=3Dscholaralrt&ss=3Dfb&u=
rl=3Dhttps://www.sciencedirect.com/science/article/pii/S0010218020301346&rt=
=3DAn+experimental+and+modeling+study+of+autoignition+characteristics+of+bu=
tanol/diesel+blends+over+wide+temperature+ranges&scisig=3DAAGBfm19DOLNm3-Fl=
WaO0trAxZkeidxYWg>
Using NMR spectroscopy to investigate the role played by copper in prion
diseases.
<http://scholar.google.com/scholar_url?url=3Dhttps://europepmc.org/article/=
med/32328835&hl=3Den&sa=3DX&d=3D16122276072657817806&scisig=3DAAGBfm1AE6Kyl=
jWO1k0f7oBnKFClEzhTMg&nossl=3D1&oi=3Dscholaralrt&hist=3Dv2Y_3P0AAAAJ:179499=
55323429043383:AAGBfm1nUe-t2q_4mKFiHSHFEAo0A4rRSA>
RA Alsiary, M Alghrably, A Saoudi, S Al-Ghamdi=E2=80=A6 - =E2=80=A6 and of =
the Italian
Society of =E2=80=A6, 2020
Prion diseases are a group of rare neurodegenerative disorders that develop
as a
result of the conformational conversion of normal prion protein (PrPC) to
the disease-
associated isoform (PrPSc). The mechanism that actually causes disease
remains =E2=80=A6
[image: Save]
<http://scholar.google.com/citations?update_op=3Demail_library_add&info=3Dz=
pCMKavUvd8J&citsig=3DAMD79ooAAAAAYImDx3r4gltEWBAkhl0g2POsXB9Qn4Lk&hl=3Den>
[image:
Twitter]
<http://scholar.google.com/scholar_share?hl=3Den&oi=3Dscholaralrt&ss=3Dtw&u=
rl=3Dhttps://europepmc.org/article/med/32328835&rt=3DUsing+NMR+spectroscopy=
+to+investigate+the+role+played+by+copper+in+prion+diseases.&scisig=3DAAGBf=
m1RidyRD-x2FOemP6iqCsr-6GAVKA>
[image:
Facebook]
<http://scholar.google.com/scholar_share?hl=3Den&oi=3Dscholaralrt&ss=3Dfb&u=
rl=3Dhttps://europepmc.org/article/med/32328835&rt=3DUsing+NMR+spectroscopy=
+to+investigate+the+role+played+by+copper+in+prion+diseases.&scisig=3DAAGBf=
m1RidyRD-x2FOemP6iqCsr-6GAVKA>
'''
regex = re.compile('(http://scholar.*?)&')
url_all = regex.findall(test_string)
citation_url = []
for i in url_all:
if search('scholar.google.com',i):
qs = parse_qs(urlparse(i).query).values()
if search('http',str(qs[0])):
citation_url.append(qs[0])
print citation_url
Present output
https://link.springer.com/content/pdf/10.1007/s11947-020-02461-6.pdf
Desired output
https://link.springer.com/content/pdf/10.1007/s11947-020-02461-6.pdf
https://www.sciencedirect.com/science/article/pii/S0010218020301346
https://europepmc.org/article/med/3232883
How to get handle URL text wrapping with equal sign and extracting the redirect URL in Python?

You could match either a question mark or ampersand [&?] using a character class. Looking at the example data, for the url= part, you can add optional newlines and an optional equals sign and adjust accordingly.
Some urls start with 3D, you can make that part optional using a non capturing group (?:3D)?
Then capture in group 1 matching http followed by matching all chars except &
\bhttp://scholar\.google\.com.*?[&?]\n?u=?\n?r\n?l\n?=(?:3D)?(http[^&]+)
Regex demo

see this regex pattern i think it might help to extract redirect uri
(http:\/\/scholar[\w.\/=&?]*)[?]?u[=]?rl=([\w\:.\/\-=]+)
also see this example here https://regex101.com/r/dmkF3h/3

Data Truncated: Cant scroll to Capture all Data Selenium Python

I have got the first 50 dataset from the table but can seem to get all:
url='https://definitivehc.maps.arcgis.com/home/item.html?id=1044bb19da8d4dbfb6a96eb1b4ebf629&view=list&showFilters=false#data'
browser = webdriver.Chrome(r"C:\Users\scrape\chromedriver")
browser.get(url)
time.sleep(25)
rows_in_table = browser.find_elements_by_xpath('//table[#class="dgrid-row-table"]//tr[td]')
for element in rows_in_table:
print(element.text.replace('\n', '||'))
result:Snippet of first 50 data points
Atmore Community Hospital||Short Term Acute Care Hospital||Atmore||AL||36502||Escambia||Alabama||01||053||01053||51||49||6||6||0.00||0.36||2||2.00||46
Gadsden Regional Medical Center||Short Term Acute Care Hospital||Gadsden||AL||35903||Etowah||Alabama||01||055||01055||346||222||40||40||0.00||0.73||124||8.00||47
Riverview Regional Medical Center||Short Term Acute Care Hospital||Gadsden||AL||35901||Etowah||Alabama||01||055||01055||281||256||45||45||0.00||0.26||25||6.00||48
Fayette Medical Center (FKA Weimer Medical Center)||Short Term Acute Care Hospital||Fayette||AL||35555||Fayette||Alabama||01||057||01057||61||45||8||8||0.00||0.23||16||2.00||49
Russellville Hospital||Short Term Acute Care Hospital||Russellville||AL||35653||Franklin||Alabama||01||059||01059||100||49||7||7||0.00||0.40||51||2.00||50
Thanks for your help.

JSON data in dash DataTable invalid argument

I'm trying to display my data into a Dash DataTable but i've got this error:
Invalid argument `data` passed into DataTable.
Expected an array.
Was supplied type `object`.
My data (amazon comments) :
[
{
"ratings": {
"\n 5 star\n ": "\n ",
"\n 4 star\n ": "\n ",
"\n 3 star\n ": "\n ",
"\n 2 star\n ": "\n ",
"\n 1 star\n ": "\n "
},
"reviews": [
{
"review_text": "The \"MPD Digital (TM) USA Made Ham CB Radio GMRS Repeater Transmission MILSPEC M17/ 163A RG-213/U (RG8/U) Coaxial Cable with UHF PL259 Connectors, 12 inches \", I having two products of like nature from MPD, the older of the two being lightly used between transmitter and SWR meter,... to being placed in storage when not in use, is a disappointing, if not marginal product given the high level of promoting by MPD (Times Microwave) relative to product component selection, product design, to manufacturing processes and procedures. i) The advertised description for this coax cable is a contradiction. This RF related product is either an RG-213/U or RG-8/U and not both types of RF transmission cable simultaneously. When measured at 50MHz, the Velocity of Propagation (VP) for Foam High Density Polyethylene (FHDPE) dielectric RG-213/U is 66% with 1.5dB loss/100ft where as FHDPE dielectric RG-8/U, the VP is 85% with 1.2dB loss/100ft. ii) The cable ends do not use high grade Amphenol, PL-259 connectors as they did in the past for this product line, the MPD cable received most recently from Kimberly Distribution, being produced with cheap and short (function of cost reducing engineering to basic disrespect, presuming the end user will not know the difference), Chinese made PL-259 connectors (see photo) and per such, have a smaller mating surface with the coax cable, thus less robust attachment. iii) The cable markings for product type, e.g. RG-213/U, are not of a permanent nature, the printing being neither molded into the cable outer jacket or laser burned, the label wearing off with ease from cleaning or use (see photo). Because of such low persistent printing method, less I check the purchase order or some other user is tasked, cannot properly determine with any great assurance, cable type (RF properties), thus VP (velocity of propagation), signal loss, SWR,... As a side note, since the printing on the outer jacket of the coax cable is easy to remove (not permanent), leaving no other identifiers present (mystery cable), that this electrical product maybe considered contraband per contract, code and insurance underwriters for applications in which UL standards compliant electrical components e.g. DoD, Hospitals, Schools, Civil Defense, Fire and Police,... are required or mandated. iv) The 12\" inch (1' ft) coax cables by MPD (Times Microwave) from current to past are not consistent in overall length as seen from simple side by side compassion (see photo and arrogantly rotated by disrespectful Amazon). There seeming to be some manufacturing (procedural and process controls) confusion at MPD relative to how to make consistent measurements (cuts) of the product e.g. is the coax conductor measured to 12\" or the entire path length (connector end point to connector end point) is measured to 12\". The MPD (Time Microwave) cable with contradicting advertising along with low end build quality is an indication that the leadership at MPD has prioritized cutting corners on raw component selection and manufacturing methods for the sake of cost reduction and or higher margins and earnings, as appose to being driven to manufacture a high end and excellent analytical product for discriminating customers. Remember: \"do a job, big or small, do it right, or not at all\". Less processes and procedures are adjusted and rigorously adhered to by Times Microwave (MPD), do not recommend this coax cable, from contradicting description thus EE (Electrical Engineering) properties, to raw component selection thus ultimately integrated build quality to product assurance and type, for demanding and disciplined RF applications. Minus 0.25 for inconsistent process and procedure for measuring total cable path length. Minus 0.25 for contradicting product description, thus electrical (RF) properties of the coax cable. Minus 0.50 for using Chinese made PL-259 connectors rather than high grade Amphenol connectors like in the past. Minus 1.0 for having easy to remove, non permanent type markings (printing) on the transmission coax cable jacket. Park McGraw JPL, Spacecraft Soldering Course Certified Experimental Physicist, Former US Navy, NASA Fellow Former CEO Class C Electrical Contracting Firm, Life Safety Industry Former Instructor, Basic Electricity and Electronics, University of Hawai`i Hilo Former Member Technical Staff and Process Engineering Mgr, Laser and Sensor Products Center, Northrop Grumman (Space Park)",
"review_posted_date": None,
"review_header": "Uses Chinese Made PL-259 Connectors, Cable Type Printing Wears Off Easily, Contradicting Description",
"review_rating": "3.0 ",
"review_author": "Directed Energy"
},
{
"review_text": "I ordered this coax for Amateur Radio use. RG-213 is rugged coax, much better than many of the air dielectric cables which are actually somewhat fragile. It is double shielded. The connectors are first quality and their installation appears first class. The price is very competitive. I have no connection with browning but I have come to respect their quality products and the value they provide. I have several of their antenna mounts and they are by far the best I have ever seen. In my 40+ years as a ham I learned long ago you buy the best because it lasts. I will confirm the specs on the cable and post any issues here when I get a chance, but I can tell from the packaging, connected quality, weight, and feel the manufacturer intended to deliver a first class product and spared no expense in doing so. I have bought other coax on Amazon but this was the most impressive so far re packaging. I never buy coax on ebay, been burned too often. This piece is intended to allow me to run my qrp cw rig by the pool but I may someday want to run higher power or use it for another antenna run to the shack. I probably own 3000 feet of coax installed at various sites but had none to spare nearby, so it was either gas or coax. The coax arrived in a sturdy box, it was sealed in moisture proof plastic bagging, and uniformly coiled and bound with quality cable ties. It's obvious the manufacturer takes good care of their inventory and this assembly is not made in someone's garage! W7CCE",
"review_posted_date": None,
"review_header": "Excellent quality coax, connectors",
"review_rating": "5.0 ",
"review_author": "Merciless"
},
{
"review_text": "The coax was working well for six months or so. When I recently unscrewed the PL-259 from my radio, the entire connector came off the coax. The crimp sleeve slid off and the center conductor came completely out of the connector. There was solder on the inner pin of the connector, but it never reached the wire itself, so only the crimp sleeve was holding the wire in, and apparently the crimp sleeve wasn't crimped very well.",
"review_posted_date": None,
"review_header": "Connector Failed",
"review_rating": "1.0 ",
"review_author": "RichG"
}
],
"url": "http://www.amazon.com/dp/product-reviews/B00Y7H39IW/ref=cm_cr_dp_d_show_all_btm?ie=UTF8&reviewerType=all_reviews&pageNumber=14",
"name": "MPD Digital USA Made Ham CB Radio GMRS Repeater Transmission MILSPEC M17/ 163A RG-213/U (RG8/U) Coaxial Cable with Soldered Silver UHF PL-259 Connectors, 12 inches",
"price": "$14.99"
}]
My code :
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.layout = html.Div([
dcc.Upload(
id='upload-data',
children=html.Div([
'Drag and Drop or ',
html.A('Select Files')
]),
style={
'width': '20%',
'height': '40px',
'lineHeight': '60px',
'borderWidth': '1px',
'borderStyle': 'dashed',
'borderRadius': '5px',
'textAlign': 'center',
'margin': '10px'
},
# Allow multiple files to be uploaded
multiple=True
),
html.Div(id='output-data-upload'),
])
def update_output(contents, filename):
.
.
.
dt = pd.DataFrame(data_extract)
return html.Div([
html.H5(filename),
dash_table.DataTable(
style_data={
'whiteSpace': 'normal',
'height': 'auto'
},
data=dt.to_dict('list'),
columns=[{'name': i, 'id': i} for i in dt.columns]
)
])
#app.callback(Output('output-data-upload', 'children'),
[Input('upload-data', 'contents')],
[State('upload-data', 'filename')])
def parse_contents(list_of_contents, list_of_names):
if list_of_contents is not None:
children = [
update_output(c, n) for c, n in
zip(list_of_contents, list_of_names)]
return children
if __name__ == '__main__':
app.run_server(debug=True)
I upload a csv file to generate the data_extract in the update_output() function which i want to display in my DataTable.
I convert my data_extract into a pandas DataFrame, then i try to submit my data with data=dt.to_dict('list'). I also tried with different argument.

I guess you only need the review part of the data? If so, and dt is that part of the json, you can use
data=dt.to_dict('records'),
because your structure is [{column -> value}, … , {column -> value}], see pandas reference

How to map the most "similar" strings from one list to another in python?

Given are two lists containing strings.
One contains the name of organisations (mostly universitys) all around the world - not only written in english but always using latin alphabet.
The other list contains mostly full addresses in which strings (organisations) from the first list may occur.
An Example:
addresses = [
"Department of Computer Science, Katholieke Universiteit Leuven, Leuven, Belgium",
"Machine Learning and Computational Biology Research Group, Max Planck Institutes Tübingen, Tübingen, Germany 72076",
"Department of Computer Science and Engineering, University of Washington, Seattle, USA 98185",
"Knowledge Discovery Department, Fraunhofer IAIS, Sankt Augustin, Germany 53754",
"Computer Science Department, University of California, Santa Barbara, USA 93106",
"Fraunhofer IAIS, Sankt Augustin, Germany",
"Department of Computer Science, Cornell University, Ithaca, NY",
"University of Wisconsin-Madison"
]
organisations = [
"Catholic University of Leuven"
"Fraunhofer IAIS"
"Cornell University of Ithaca"
"Tübingener Max Plank Institut"
]
As you can see the desired mapping would be:
"Department of Computer Science, Katholieke Universiteit Leuven, Leuven, Belgium",
--> Catholic University of Leuven
"Machine Learning and Computational Biology Research Group, Max Planck Institutes Tübingen, Tübingen, Germany 72076",
--> Max Plank Institut Tübingen
"Department of Computer Science and Engineering, University of Washington, Seattle, USA 98185",
--> --
"Knowledge Discovery Department, Fraunhofer IAIS, Sankt Augustin, Germany 53754",
--> Fraunhofer IAIS
"Computer Science Department, University of California, Santa Barbara, USA 93106",
"Fraunhofer IAIS, Sankt Augustin, Germany",
--> Fraunhofer IAIS
"Department of Computer Science, Cornell University, Ithaca, NY"
--> "Cornell University of Ithaca",
"University of Wisconsin-Madison",
--> --
My thinking was to use some kind of "disctance- algorithm" to calculate the similarity of the strings. Since I cannot just look for an organisation in an address just by doing if address in organisation because it could be written slightly differently at in different places. So my first guess was using the difflib module. Especially the difflib.get_close_matches() function for selecting for every address the closest string from the organisations list. But I am not quite confident, that the results will be accurate enough. Although I don't know how high I should set the ratio which seams to be a similarity measure.
Before spending too much time in trying the difflib module I thought of asking the more experienced people here, if this is the right approach or if there is a more suited tool / way to solve my problem. Thanks!
PS: I don't need an optimal solution.

Use the following as your string distance function (instead of plain levenshtein distance):
def strdist(s1, s2):
words1 = set(w for w in s1.split() if len(w) > 3)
words2 = set(w for w in s2.split() if len(w) > 3)
scores = [min(levenshtein(w1, w2) for w2 in words2) for w1 in words1]
n_shared_words = len([s for s in scores if s <= 3])
return -n_shared_words
Then use the Munkres assignment algorithm shown here since there appears to be a 1:1 mapping between organisations and adresses.

You can use soundex or metaphone to translate the sentence into a list of phonems, then compare the most similar lists.
Here is a Python implementation of the double-metaphone algo.

How to classify users into different countries, based on the Location field

Most web applications have a Location field, in which uses may enter a Location of their choice.
How would you classify users into different countries, based on the location entered.
For eg, I used the Stack Overflow dump of users.xml and extracted users' names, reputation and location:
['Jeff Atwood', '12853', 'El Cerrito, CA']
['Jarrod Dixon', '1114', 'Morganton, NC']
['Sneakers OToole', '200', 'Unknown']
['Greg Hurlman', '5327', 'Halfway between the boardwalk and Six Flags, NJ']
['Power-coder', '812', 'Burlington, Ontario, Canada']
['Chris Jester-Young', '16509', 'Durham, NC']
['Teifion', '7024', 'Wales']
['Grant', '3333', 'Georgia']
['TimM', '133', 'Alabama']
['Leon Bambrick', '2450', 'Australia']
['Coincoin', '3801', 'Montreal']
['Tom Grochowicz', '125', 'NJ']
['Rex M', '12822', 'US']
['Dillie-O', '7109', 'Prescott, AZ']
['Pete', '653', 'Reynoldsburg, OH']
['Nick Berardi', '9762', 'Phoenixville, PA']
['Kandis', '39', '']
['Shawn', '4248', 'philadelphia']
['Yaakov Ellis', '3651', 'Israel']
['redwards', '21', 'US']
['Dave Ward', '4831', 'Atlanta']
['Liron Yahdav', '527', 'San Rafael, CA']
['Geoff Dalgas', '648', 'Corvallis, OR']
['Kevin Dente', '1619', 'Oakland, CA']
['Tom', '3316', '']
['denny', '573', 'Winchester, VA']
['Karl Seguin', '4195', 'Ottawa']
['Bob', '4652', 'US']
['saniul', '2352', 'London, UK']
['saint_groceon', '1087', 'Houston, TX']
['Tim Boland', '192', 'Cincinnati Ohio']
['Darren Kopp', '5807', 'Woods Cross, UT']
using the following Python script:
from xml.etree import ElementTree
root = ElementTree.parse('SO Export/so-export-2009-05/users.xml').getroot()
items = ['DisplayName','Reputation','Location']
def loop1():
for count,i in enumerate(root):
det = [i.get(x) for x in items]
print det
if count>30: break
loop1()
What is the simplest way to classify people into different countries? Are there any ready lookup tables available that provide me an output saying X location belongs to Y country?
The lookup table need not be totally accurate. Reasonably accurate answers are obtained by querying the location string on Google, or better still, Wolfram Alpha.

You best bet is to use a Geocoding API like geopy (some Examples).
The Google Geocoding API, for example, will return the country in the CountryNameCode-field of the response.
With just this one location field the number of false matches will probably be relatively high, but maybe it is good enough.
If you had server logs, you could try to also look up the users IP address with an IP geocoder (more information and pointers on Wikipedia

Force users to specify country, because you'll have to deal with ambiguities. This would be the right way.
If that's not possible, at least make your best-guess in conjunction with their IP address.
For example, ['Grant', '3333', 'Georgia']
Is this Georgia, USA?
Or is this the Republic of Georgia?
If their IP address suggests somewhere in Central Asia or Eastern Europe, then chances are it's the Republic of Georgia. If it's North America, chances are pretty good they mean Georgia, USA.
Note that mappings for IP address to country isn't 100% accurate, and the database needs to be updated regularly. In my opinion, far too much trouble.