iPhone has a pretty good telephone number splitting function, for example:
Singapore mobile: +65 9852 4135
Singapore resident line: +65 6325 6524
China mobile: +86 135-6952-3685
China resident line: +86 10-65236528
HongKong: +886 956-238-82
USA: +1 (732) 865-3286
Notice the nice features here:
- the splitting of country code, area code, and the rest is automatic;
- the delimiter is also nicely adopted to different countries, e.g. "()", "-" and space.
Note the parsing logic is doable to me, however, I don't know where to get the knowledge of most countries' telephone number format.
where could i found such knowledge, or an open source code that implemented it?
You can get similar functionality with the libphonenumber code library.
Interestingly enough, you cannot use an NSNumberFormatter for this, but you can write your own custom class for it. Just create a new class, set properties such as countryCode, areaCode and number, and then create a method that formats the number based on the countryCode.
Here's a great example: http://the-lost-beauty.blogspot.com/2010/01/locale-sensitive-phone-number.html
As an aside: a friend told me about a gigantic regular expression he had to maintain that could pick telephone numbers out of intercepted communications from hundreds of countries around the world. It was very non-trivial.
Thankfully your problem is easier, as you can just have a table with the per-country formats:
format[usa] = "+d (ddd) ddd-dddd";
format[hk] = "+ddd ddd-ddd-dd";
format[china_mobile] = "+dd ddd-dddd-dddd";
...
Then when you're printing, you simply output one digit from the phone number string in each d spot as needed. This assumes you know the country, which is a safe enough assumption for telephone devices -- pick "default" formats for the few surrounding countries.
Since some countries have different formats with different lengths you might need to store your table with additional information:
format[germany][10] = "..."
format[germany][11] = "....."
Related
I understood the process to shorten the URL with base 62 at How do I create a URL shortener?.
Steps given are
Think of an alphabet we want to use. In your case, that's [a-zA-Z0-9]. It contains 62 letters.
Take an auto-generated, unique numerical key (the auto-incremented id of a MySQL table for example).
For this example, I will use 12510 (125 with a base of 10).
Now you have to convert 12510 to X62 (base 62)
My question is why not just create unique numerical key and return it ? What is the advantage of concerting numerical key > Base 62 > then Finally some alphanumeric number ?
Is it because final alphanumeric number will be much smaller than unique numerical key ?
Yes. The idea is to make it short and usable in a URL. A number in base 62 will use fewer characters than the same number in base 10. Notice also that URL shorteners use short hosts, such as g.co.
I can see you understand that, yes, a number written in base 62 takes less characters than a number in base 10 just like a number in base 10 takes less characters than a number in base 2 (e.g. 0101 is 3 characters longer than just '5').
So, I'll answer specifically "Why".
Sometimes a link is shortened to be more visually pleasing. A company worried about their public perception likely doesn't want their links to look like an error code due to how long they are so they resort to shortening. That's why some url shortening services allow you to add your own "vanity url" which customizes the domain name, so that a link can be shortened and branded.
Other times a link is shortened to minimize character count when working with constraints, like Twitter. For example, at my company we shortened the links in our automated Twilio messages because SMS messages that contain more than 160 characters are technically 2 concatenated messages so it is more expensive to send.
And finally if the link is being shared through a medium that cannot be directly clicked on (e.g. verbally, on paper), making it shorter makes it much easier to type into an address bar manually. (Imagine trying to type the url to this SO question when someone is reading it to you.) I assume this is also at least partially why the base used for these links usually stop at around 62. If you start including other arbitrary characters to higher the base and consequentially make the link marginally shorter, it'll become harder to communicate, read and type. ("domain.name/5omeC0d3" vs "domian.name/🈲}♠"
I am using google place to retrieve address, and somehow we want the street(route in google terminology) to be separated into street name and street type. We also want the street type to match an existing column in database.
But things get difficult when google place sometimes use XXXX Street and some times XXXX st
For instance, this is a typical google address
{
administrative_area_level_1: ['short_name', 'VIC'],
locality: ['long_name', 'Carlton'],
postal_code: ['long_name', '3053'],
route: ['long_name', 'Canada Ln'],
street_number: ['short_name', '12'],
subpremise: ['short_name', '13']
}
But it always shows Canada Lane in the suggestion box.
And sometimes even worse when the abbreviation does not match my local data model. For instance we use la instead of ln for short of lane.
It will be appreciated if anyone could tell me where to find a list of street type (and abbreviation) used by google API. Or Is there a way to disable the abbreviation option?
Sounds like you're after "street suffixes". These are complicated.
Not only they change across countries and languages, even within the same country and language they can be used in different ways; abbreviations can have multiple meanings: "St" can be "Street" of "Saint"; abbreviations are used or not depending on subtle rules that also change from place to place.
Same goes for cardinal points (North, South, East, West) that are parts of road / street names: "North St" or "N 11st Street"? It's complicated.
If you already have a good amount of addresses, and you only care about addresses in English, you could take the last word from each street name as the suffix. When matching to your own data, allow for abbreviations when matching, rather than trying to expand them.
For instance, don't try to expand "Canada La" into "Canada Lane" so that it matches "Lane". Instead, expand "Lane" into ["Lane", "La", "Ln"] and match suffixes to all values.
Then you'd need a strategy for "collisions", abbreviations that can mean 2+ suffixes. These seem to be rare, I can't remember any ("St" isn't, because "Saint" isn't a suffix) and USPS' http://pe.usps.gov/text/pub28/28apc_002.htm doesn't seem to have any.
Can I determine if the user entered a phone number that can be safely formatted into E164?
For Germany, this requires that the user started his entry with a local area code. For example, 123456 may be a subscriber number in his city, but it cannot be formatted into E164, because we don't know his local area code. Then I would like to keep the entry as it is. In contrast, the input 089123456 is independent of the area code and could be formatted into E164, because we know he's from Germany and we could convert this into +4989123456.
You can simply convert your number into E164 using libphonenumber
and after conversion checks if both the strings are same or not. If they're same means a number can not be formatted, otherwise the number you'll get from library will be formatted in E164.
Here's how you can convert
PhoneNumberUtil phoneUtil = PhoneNumberUtil.getInstance();
String formattedNumber = phoneUtil.format(inputNumber, PhoneNumberFormat.E164);
Finally compare formattedNumber with inputNumber
It looks as though you'll need to play with isValidNumber and isPossibleNumber for your case. format is certainly not guaranteed to give you something actually dialable, see the javadocs. This is suggested by the demo as well, where formatting is not displayed when isValidNumber is false.
I also am dealing with this FWIW. In the context of US numbers: The issue is I'd like to parse using isPossibleNumber in order to be as lenient as possible, and store the number in E164. However then we accept, e.g. +15551212. This string itself even passes isPossibleNumber despite clearly (I think) not being dialable anywhere.
I'm trying to generate UUIDs with the same style as bit.ly urls like:
http://bit [dot] ly/aUekJP
or cloudapp ones:
http://cl [dot] ly/1hVU
which are even smaller
how can I do it?
I'm now using UUID gem for ruby but I'm not sure if it's possible to limitate the length and get something like this.
I am currently using this:
UUID.generate.split("-")[0] => b9386070
But I would like to have even smaller and knowing that it will be unique.
Any help would be pretty much appreciated :)
edit note: replaced dot letters with [dot] for workaround of banned short link
You are confusing two different things here. A UUID is a universally unique identifier. It has a very high probability of being unique even if millions of them were being created all over the world at the same time. It is generally displayed as a 36 digit string. You can not chop off the first 8 characters and expect it to be unique.
Bitly, tinyurl et-al store links and generate a short code to represent that link. They do not reconstruct the URL from the code they look it up in a data-store and return the corresponding URL. These are not UUIDS.
Without knowing your application it is hard to advise on what method you should use, however you could store whatever you are pointing at in a data-store with a numeric key and then rebase the key to base32 using the 10 digits and 22 lowercase letters, perhaps avoiding the obvious typo problems like 'o' 'i' 'l' etc
EDIT
On further investigation there is a Ruby base32 gem available that implements Douglas Crockford's Base 32 implementation
A 5 character Base32 string can represent over 33 million integers and a 6 digit string over a billion.
If you are working with numbers, you can use the built in ruby methods
6175601989.to_s(30)
=> "8e45ttj"
to go back
"8e45ttj".to_i(30)
=>6175601989
So you don't have to store anything, you can always decode an incoming short_code.
This works ok for proof of concept, but you aren't able to avoid ambiguous characters like: 1lji0o. If you are just looking to use the code to obfuscate database record IDs, this will work fine. In general, short codes are supposed to be easy to remember and transfer from one medium to another, like reading it on someone's presentation slide, or hearing it over the phone. If you need to avoid characters that are hard to read or hard to 'hear', you might need to switch to a process where you generate an acceptable code, and store it.
I found this to be short and reliable:
def create_uuid(prefix=nil)
time = (Time.now.to_f * 10_000_000).to_i
jitter = rand(10_000_000)
key = "#{jitter}#{time}".to_i.to_s(36)
[prefix, key].compact.join('_')
end
This spits out unique keys that look like this: '3qaishe3gpp07w2m'
Reduce the 'jitter' size to reduce the key size.
Caveat:
This is not guaranteed unique (use SecureRandom.uuid for that), but it is highly reliable:
10_000_000.times.map {create_uuid}.uniq.length == 10_000_000
The only way to guarantee uniqueness is to keep a global count and increment it for each use: 0000, 0001, etc.
My problem:
I'm looking for a way to represent a person's name and address as an encoded id. The id should contain only alpha-numeric characters, be collision-proof, and be represented in a smallest number of characters possible. My first thought was to simply use a cryptographic hash function like MD5 or SHA1, but this seems like overkill (security isn't important - doesn't need to be one-way) and I'd prefer to find something that would produce a shorter id. Does anyone know of an existing algorithm that fits this problem?
In other words, what is the best way to implement the following function so that the return value is the same consistently for the same input, collisions are unlikely, and ids are less than 20 characters?
>>> make_fake_id(fname = 'Oscar', lname = 'Grouch', stnum = '1', stname = 'Sesame', zip = '12345')
N1743123734
Application Context (for those that are interested):
This will be used for a record linkage app. Given an input name and address we search a very large database for the best match and return the database id and other data (how we do this is not important here). If there isn't a match I need to generate this psuedo/generated/derived id from the search input (entity's name and address data). Every search record should result in an output record with either a real (the actual database id resulting from a match/link) or this generated psuedo/generated/derived id. The psuedo id will be prefixed with a character (e.g. N) to differentiate it from a real id.
I know you said no to MD5 and SHA1, but I think you should consider them anyway. As well as being well studied hashing algorithms, the length gives you more protection against possible collisions. No hash is collision-proof, but the cryptographic ones generally are less collision-prone than something you couuld come up with yourself.
Use a cryptographic hash for its collision resistance, not its other qualities
Use as many bytes from the hash as you want (truncate)
convert to alpha-numeric characters
You can also truncate the alpha-numeric string instead of the hash
An easy way to do this: hash the data, encode in base64, remove all non-alpha-numeric characters, truncate.
N_HASH_CHARS = 11
import hashlib, re
def digest(name, address):
hash = hashlib.md5(name + "|" + address).digest().encode("base64")
alnum_hash = re.sub(r'[^a-zA-Z0-9]', "", hash)
return alnum_hash[:N_HASH_CHARS]
How many alpha-numeric characters should you keep? Each character gives you around 5.95 bits of entropy (log(62,2)). 11 characters give you 65.5 bits of entropy, which should be enough to avoid a collision for the first 2**32.7 users (about 7 billion).
A good solution is somewhat dependent on your application. Do you know how many users and what the set of all users is? If you provide more details you would get better help.
I agree with the other poster suggesting serial numbers. OTOH, if you really, really really want to do something else:
Create a SHA1 hash from the data, and store it in a table with a serial number field.
Then, when you get the data, calculate the hash, look it up on the table, get the serial, and that's your id. If it's not on the table, insert it.
I wonder whether you intend to "assign" these ids to the users? If so, I would expect your users to hate anything that you propose; who would want a user id of "AAAAA01"?
So, if these ids are visible to the user, then you should just let them pick what they like and check them for uniqueness (easy). If they are not visible to the user (e.g., internal primary key), then just generate them sequentially using an appropriate technique such as an Oracle Sequence or SQL Server AutoNumber (also easy).
If these ids are an attempt to detect a user that is registering more than once, then I would agree that you should consider a cryptographic hash followed by a full comparison of the registration data (name, address, etc.). However, to be usable, you will need to translate the data into a canonical form (standardized letter case, whitespace, canonical street address, etc.) before computing the hash or making the comparison. Otherwise, you will mismatch based on trivial differences.
EDIT: Now that I understand the problem space better based on your edits, I think that it is highly unlikely that your algorithm (so far) will catch most matches. Beyond my suggestion to canonicalize the inputs, I recommend that you consider an approach that results in a ranked list of a handful of possible matches (to be resolved by a human if possible) rather than an all-or-nothing attempt at a single match. In other words, I recommend a search approach rather than a lookup approach.
Is that feasible in your situation?
Well, if there's more than one person at the same address with the same name, you're toast here, (w/o adding code to detect this and add a discriminator of some kind).
but assuming that issue is not, then the street address and zip code portion of the full addresss is sufficient to guaranteee uniqueness there, so adding enough data from the name should take care of the issue...
Do you have access to a database, or other persistence mechanism, where you could generate and maintain key values for each address? Then keep the address and individual entities in two keyed dictionary structures, where the key is autogenerated for each new distinct address, person encountered... and then use the autogenerated alpha-numeric key...
You could use AAAAA01 for first person at first address,
AAAAA02 for second person at first address,
AAAAB07 for the seventh resident at the second adresss, etc.
If you donlt have any way to generate and maintain these entity-Key mappings then you need to use the full street address/Zip and fullNAme, or a hash value of the same, although the Hash value approach has a smnall chance of generating duplicates...