The ultimate tool to split/extract street name from street number

Question

I have some addresses.csv in different international formats

Example Street 1
Teststraße 2
Teststr. 1-5
Baker Street 221b
221B Baker Street
19th Ave 3B
3B 2nd Ave
1-3 2nd Mount x Ave
105 Lock St # 219
Test Street, 1
BookAve, 54, Extra Text 123#

For example we in Germany write Teststraße 2 and in the USA 2 Test Street

Is there a way to seperate/extract all street names and street numbers? output-names.csv

Example Street
Teststraße
Teststr.
Baker Street
Baker Street
19th Ave
2nd Ave
2nd Mount Good Ave
Lock St # 219
Test Street
BookAve

output-numbers.csv

1
2
1-5
221b
221B
3B
3B
1-3
105
1
54

output-extra_text.csv

Extra Text 123#

I am using macOS 13.. the shell is zsh 5.8.1 or bash-3.2

---

my thoughts that i had: you could sort the addresses first like this:

x=The-adress-line;
if [ x = "begins with a letter"];
    then 
    if [ x = "begins with a letter + number + SPACE"];
        then
        echo 'something like "1A Street"';
        # NUMBER = '1A' / NAME = 'Street'
    else
        echo 'It begins with the STREET-NAME';
    fi;
elif [ x = "begins with a number"];
    then
    echo 'maybe STREET-NAME like "19th Ave 19B" or STREET-NUMBER like "19B Street"';
    # NUMBER = '19B' / NAME = '19th Ave' or 'Street'
    if [ x = "begins with a number + SPACE"];
        then
        echo 'It begins with the STREET-NUMBER like "1 Street"';
        # NUMBER = '1' / NAME = 'Street'
    elif [ x = "is (number)(text)(space)(text)(number(maybe-text))"];
        then
            echo 'For example 19th Street 19B -> The last number+text is the number (19B)'
            # NUMBER = '19B' / NAME = '19th Street'
    elif [ x = "is (number(maybe-text))(space)(number)(text)(space)(text)"];
        then
        echo 'For example 19B 19th Street -> The first number+text is the number (19B)'
            # NUMBER = '19B' / NAME = '19th Street'
    else
        echo 'INVALID';
else
    echo 'INVALID';
fi;

Answer 1

IMHO all you can do is a best-effort employing a series of regexps to match the addresses you know about, e.g. using GNU awk for the 3rd arg to match() and \s shorthand for [[:space:]] and 3 of the possible regexps defined:

$ cat tst.awk
BEGIN { OFS="\",\"" }
{
    name = number = type = ""
    gsub(/"/,"\"\"")
}
match($0,/^([^0-9]+)([0-9]+(-[0-9]+)?[[:alpha:]]?)$/,a) {
    # Example Street 1
    # Teststraße 2
    # Teststr. 1-5
    # Baker Street 221b
    # Test Street, 1
    type   = 1
    name   = a[1]
    number = a[2]
}
!type && match($0,/^([0-9]+[[:alpha:]])\s+([^0-9]+)$/,a) {
    # 221B Baker Street
    type   = 2
    name   = a[2]
    number = a[1]
}
!type && match($0,/^([0-9]+[[:alpha:]]{2}.*)\s+([0-9]+[[:alpha:]]?)$/,a) {
    # 19th Ave 3B
    type   = 3
    name   = a[1]
    number = a[2]
}
{
    gsub(/^\s+|\s+$/,"",name)
    gsub(/^\s+|\s+$/,"",number)
    if ( !doneHdr++ ) {
        print "\"" "type", "name", "number", "$0" "\""
    }
    print "\"" type, name, number, $0 "\""
}

$ awk -f tst.awk file
"type","name","number","$0"
"1","Example Street","1","Example Street 1"
"1","Teststraße","2","Teststraße 2"
"1","Teststr.","1-5","Teststr. 1-5"
"1","Baker Street","221b","Baker Street 221b"
"2","Baker Street","221B","221B Baker Street"
"3","19th Ave","3B","19th Ave 3B"
"","","","3B 2nd Ave"
"","","","1-3 2nd Mount x Ave"
"","","","105 Lock St # 219"
"1","Test Street,","1","Test Street, 1"
"","","","BookAve, 54, Extra Text 123#"

You'd add the other regexps to match the formats of address you know about in the appropriate order such that if an address might match 2 or more regexps you have the more restrictive regexp(s) first. You may actually want to modify the above to print a warning if an address matches 2 or more regexps as you may then want to tweak or re-order or consolidate them.

If you reach the print line with type still empty, that's the "invalid" case and then you could write/add a new regexp to match those if appropriate.

I do expect you'll come across cases where you simply can't write code to distinguish one address format from another but hopefully this best-effort approach will be adequate for your needs. If you have city/state/county you could always curl an address using google maps to see if it's real or not as a last-ditch effort for addresses you can't identify (but that'd take forever if you tried to do ONLY that for all your addresses).

Produce output however you like wherever you like once the address recognition algorithm is working, I'm just dumping CSV above for ease of developing/testing.