1. 11 — Localization
From Code to Product
gidgreen.com/course

2. Getting it wrong
From Code to Product Lecture 11 — Localization— Slide 2 gidgreen.com/course

3. Something we should know?
From Code to Product Lecture 11 — Localization— Slide 3 gidgreen.com/course

4. Lecture 11
• Countries and languages
• Character sets
• Unicode
• Text localization
• Outsourcing translation
• Other localization
From Code to Product Lecture 11 — Localization— Slide 4 gidgreen.com/course

5. Population
From Code to Product Lecture 11 — Localization— Slide 5 gidgreen.com/course
China 1,347 M 19.3%
India 1,210 M 17.3%
USA 313 M 4.5%
Indonesia 238 M 3.4%
Brazil 192 M 2.8%
Pakistan 179 M 2.6%
Nigeria 162 M 2.3%
Russia 143 M 2.0%
Bangladesh 142 M 2.0%
Japan 128 M 1.8%
Mandarin 845 M 12.1%
Spanish 329 M 4.7%
English 328 M 4.7%
Hindi-Urdu 240 M 3.4%
Arabic 221 M 3.2%
Bengali 181 M 2.6%
Portuguese 178 M 2.5%
Russian 144 M 2.1%
Japanese 122 M 1.7%
Punjabi 109 M 1.6%
2011-2012 from Wikipedia

6. Economic weight (nominal)
From Code to Product Lecture 11 — Localization— Slide 6 gidgreen.com/course
USA $14.4 T 23.7%
Japan $4.9 T 8.1%
China $4.3 T 7.1%
Germany $3.7 T 6.0%
France $2.9 T 4.7%
UK $2.7 T 4.4%
Italy $2.3 T 3.8%
Russia $1.7 T 2.8%
Spain $1.6 T 2.6%
Brazil $1.6 T 2.6%
English $21.3 T 34.9%
Chinese $5.2 T 8.4%
Japanese $4.9 T 8.1%
German $4.4 T 7.2%
Spanish $4.2 T 6.8%
French $4.0 T 6.5%
Italian $2.5 T 4.1%
Russian $2.2 T 3.7%
Portuguese $1.9 T 3.1%
Arabic $1.9 T 3.1%
2008 from globalization-group.com, IMF

7. Internet users
From Code to Product Lecture 11 — Localization— Slide 7 gidgreen.com/course
China 485 M 36%
USA 245 M 78%
India 100 M 8%
Japan 99 M 78%
Brazil 76 M 37%
Germany 65 M 80%
Russia 60 M 43%
UK 51 M 82%
France 45 M 70%
Nigeria 44 M 28%
English 565 M 43%
Chinese 510 M 37%
Spanish 165 M 39%
Japanese 99 M 78%
Portuguese 83 M 32%
German 75 M 80%
Arabic 65 M 19%
French 60 M 17%
Russian 60 M 43%
Korean 39 M 55%
2011 from internetworldstats.com

8. Internet penetration
From Code to Product Lecture 11 — Localization— Slide 8 gidgreen.com/course

9. E-commerce volumes
$135B
$51B
$37B
$36B$28B
$28B$19B
$16B
$15B
$13B
$123B
USA
Japan
China
Germany
France
UK
Italy
Canada
Spain
South Korea
Other
From Code to Product Lecture 11 — Localization— Slide 9 gidgreen.com/course
2009 from Everis

10. Multilingual countries
From Code to Product Lecture 11 — Localization— Slide 10 gidgreen.com/course
English
21M
French
8M
Canada
Germa
n
5.0M
French
1.6M
Italian
0.5M
Switzerland

11. Language variations
• US vs UK English
– color | colour
– vacation | holiday
– Where are you (at)?
• European vs Brazilian Portuguese
• French
• Spanish
From Code to Product Lecture 11 — Localization— Slide 11 gidgreen.com/course

12. Language codes (ISO-639-1)
From Code to Product Lecture 11 — Localization— Slide 12 gidgreen.com/course
ar Arabic
fr French
nl Dutch
de German
he Hebrew
it Italian
ja Japanese
pl Polish
ru Russian
es Spanish
zh-CN Chinese (simplified)
zh-TW Chinese (traditional)
en-GB English (UK)
en-US English (US)
pt-BR Portuguese (Brazilian)
pt-PT Portuguese (Portugal)
es-AR Spanish (Argentina)
es-CL Spanish (Chile)
es-MX Spanish (Mexico)
es-ES Spanish (Spain)

13. Lecture 11
• Countries and languages
• Character sets
• Unicode
• Text localization
• Outsourcing translation
• Other localization
From Code to Product Lecture 11 — Localization— Slide 13 gidgreen.com/course

14. Computer representation
From Code to Product Lecture X — SUBJECT— Slide 14 gidgreen.com/course
0 1 0 0 0 0 0 1
0 … 65 … 255
.,/?;:’!%abcdefghijklmnopqrstuvwxyz… A …BCDEFGHIJKMNOPQRSTUVWXYZ0123456789
00 … 41 … FF

15. US-ASCII
From Code to Product Lecture 11 — Localization— Slide 15 gidgreen.com/course
Image from czyborra.com

16. ISO-8859-1
From Code to Product Lecture 11 — Localization— Slide 16 gidgreen.com/course

17. Windows-1252
From Code to Product Lecture 11 — Localization— Slide 17 gidgreen.com/course

18. ISO-8859-5
From Code to Product Lecture 11 — Localization— Slide 18 gidgreen.com/course

19. ISO-8859-8
From Code to Product Lecture 11 — Localization— Slide 19 gidgreen.com/course

20. Problems with character sets
• Extra metadata
• Potential for misdisplay
• Mutually exclusive
• Little space to grow - e.g. €
• Ideographic languages
– 70,000+ Chinese characters
– Multibyte encoding
From Code to Product Lecture 11 — Localization— Slide 20 gidgreen.com/course

21. Lecture 11
• Countries and languages
• Character sets
• Unicode
• Text localization
• Outsourcing translation
• Other localization
From Code to Product Lecture 11 — Localization— Slide 21 gidgreen.com/course

22. The Unicode solution
• One global character set
– Over 110,000 characters
– Over 100 alphabets
• 1,114,112 code points
– 0…255 compatible with ISO-8859-1
– U+0041 = A
• Multiple encodings
From Code to Product Lecture X — SUBJECT— Slide 22 gidgreen.com/course

23. U+0000 … U+007F
From Code to Product Lecture 11 — Localization— Slide 23 gidgreen.com/course

24. U+0080 … U+00FF
From Code to Product Lecture 11 — Localization— Slide 24 gidgreen.com/course

25. U+0400 … U+047F
From Code to Product Lecture 11 — Localization— Slide 25 gidgreen.com/course

26. U+0590 … U+060F
From Code to Product Lecture X — SUBJECT— Slide 26 gidgreen.com/course

27. U+4E00 … U+4E7F
From Code to Product Lecture 11 — Localization— Slide 27 gidgreen.com/course

28. U+2190 … U+220F
From Code to Product Lecture 11 — Localization— Slide 28 gidgreen.com/course

29. U+2800 … U+267F
From Code to Product Lecture 11 — Localization— Slide 29 gidgreen.com/course

30. UTF-16 encoding
• 2 or 4 bytes per code point
• Simple for U+0000…D7FF and E000…FFFF
– “Basic Multilingual Pane”
• Higher code points use 4 bytes
• U+FEFF = byte-order mark
– No well-followed default
• Windows APIs since Windows 2000
– Also .NET, Android, iOS, Mac OS X
From Code to Product Lecture 11 — Localization— Slide 30 gidgreen.com/course

31. UTF-8 encoding
• 1 to 6 bytes per code point
• 1 byte for U+0000…007F
– Perfect compatibility with ASCII
• 2 bytes for U+0080…07FF
– etc…
• Byte order mark allowed
– But unnecessary, causes problems
• Dominant on web, email
From Code to Product Lecture 11 — Localization— Slide 31 gidgreen.com/course

32. UTF-8 encoding
From Code to Product Lecture 11 — Localization— Slide 32 gidgreen.com/course

33. UTF-8 advantages
• Natural compression for English
• English works in old tools/APIs
– HTML tags unaffected
• No shared values between byte types
– Easy to synchronize mid-stream
– Easy to search by byte value
• No zero bytes (good for C)
• Byte-sorting = codepoint-sorting
From Code to Product Lecture 11 — Localization— Slide 33 gidgreen.com/course

34. Unicode on the web
From Code to Product Lecture 11 — Localization— Slide 34 gidgreen.com/course
Source:
googleblog.blogspot.com

35. Lecture 11
• Countries and languages
• Character sets
• Unicode
• Text localization
• Outsourcing translation
• Other localization
From Code to Product Lecture 11 — Localization— Slide 35 gidgreen.com/course

36. The original source code
From Code to Product Lecture 11 — Localization— Slide 36 gidgreen.com/course
function Check_Username(username)
…
if Username_Taken(username)…
error="username is taken."
…
return error
end function

37. And now in Spanish…
function Check_Username(username)
…
if Username_Taken(username)…
error="username se toma."
…
return error
end function
From Code to Product Lecture 11 — Localization— Slide 37 gidgreen.com/course

38. Internationalized
function Check_Username(username)
…
if Username_Taken(username)…
error=Get_String("un-taken")
…
return error
end function
From Code to Product Lecture 11 — Localization— Slide 38 gidgreen.com/course

39. Internationalized
function Check_Username(username)
…
if Username_Taken(username)…
error=Translate("username is
taken")
…
return error
end function
From Code to Product Lecture 11 — Localization— Slide 39 gidgreen.com/course

40. IDs vs English strings
From Code to Product Lecture 11 — Localization— Slide 40 gidgreen.com/course
IDs English strings
More compact code More explicit code
English can be changed
Enforces sync between
languages
Less error-prone Easier for third parties

41. Concatenation is evil
print Translate("You will travel from ") +
from_city + Translate(" to ") + to_city
From Code to Product Lecture 11 — Localization— Slide 41 gidgreen.com/course
You will travel from London to Paris
Usted viajará de London a Paris
Sie wird von London nach Paris reisen

42. Substitutions
From Code to Product Lecture 11 — Localization— Slide 42 gidgreen.com/course
raw=Translate("You will travel from
%from% to %to%")
raw=replace(raw, "%from%", from_city)
print replace(raw, "%to%", to_city)
You will travel from %from% to %to%
Usted viajará de %from% a %to%
Sie wird von %from% nach %to% reisen

43. Singular/plural
if (credits is 1)
c_string=translate("1 credit")
else
c_string=replace(translate("%#% credits",
"%#%", credits)
raw=translate("You have %credits% left”)
print replace(raw, "%credits%", c_string)
From Code to Product Lecture 11 — Localization— Slide 43 gidgreen.com/course
You have 3 credits left You have 1 credit left

44. Text in images
From Code to Product Lecture 11 — Localization— Slide 44 gidgreen.com/course

45. Width in layouts
.‫اﻟﺪﻓﻊ‬ ‫ﻋﻠﻰ‬ ‫أﺷﻜﺮﻛﻢ‬
感谢 的付款。
Gracias por su pago.
.‫התשלום‬ ‫על‬ ‫לך‬ ‫מודים‬ ‫אנו‬
Спасибо за ваш платеж.
Thank you for your payment.
Vielen Dank für Ihre Bezahlung.
Σας ευχαριστούµε για την πληρωµή σας.
Nous vous remercions de votre paiement.
お支払いしていただきありがとうございます。
From Code to Product Lecture 11 — Localization— Slide 45 gidgreen.com/course
+57%!

46. LTR / RTL
From Code to Product Lecture 11 — Localization— Slide 46 gidgreen.com/course

47. Outsourcing translation quotes
From Code to Product Lecture 11 — Localization— Slide 47 gidgreen.com/course
Ibidem-translations.com
• Add 15-50% for specialized areas
• Clarify how words are counted
• Check for extra costs

48. Lecture 11
• Countries and languages
• Character sets
• Unicode
• Text localization
• Outsourcing translation
• Other localization
From Code to Product Lecture 11 — Localization— Slide 48 gidgreen.com/course

49. Numbers
1,234,567.89 — Japan, UK, USA
1 234 567,89 — France, Central Europe
1.234.567,89 — Germany, Scandinavia
1’234’567.89 — Switzerland
123,4567.89 — China
1’234,567.89 — Mexico
12,34,567.89 — India
From Code to Product Lecture X — SUBJECT— Slide 49 gidgreen.com/course

50. Date and Times
7/21/2012
21/7/2012
21.7.2012
2012-07-12
7. 21. 2012
7-12-2012
From Code to Product Lecture 11 — Localization— Slide 50 gidgreen.com/course
15:45
3.45 PM
3:45 pm

51. Time zones
From Code to Product Lecture 11 — Localization— Slide 51 gidgreen.com/course
Map from
wikipedia.org

52. Displaying times online
• Store times independent of zone
• Options for display
– Ask the user for their time zone
– Show an explicit time zone
– Use “ago” notation
• Javascript to get from browser
From Code to Product Lecture 11 — Localization— Slide 52 gidgreen.com/course

53. Currencies
• Biggest traded currencies: $ € ¥ £
– But there are almost 200
• How to display
– Number formatting
– Symbols: ₪ ₩ ฿ $
– Currency codes: USD EUR JPY GBP CAD AUD
• Also: currency conversion
– Live feed, e.g. from ECB
From Code to Product Lecture 11 — Localization— Slide 53 gidgreen.com/course

54. Names
• Surname can come first
– China, Japan, Korea, Hungary
• Multiple surnames
– José Santos Tavares Melo Silva
• Middle names/initials
• Double-barrelled names
– Sarah-Jane Darlington-Whit
• No spaces in CJK
From Code to Product Lecture 11 — Localization— Slide 54 gidgreen.com/course

55. Names
From Code to Product Lecture 11 — Localization— Slide 55 gidgreen.com/course
Full Name:
What should we call you?
Family name:
Other/given names:
• Or localize based on language
• Do you need names at all?
– Username or email can be enough

56. Addresses
From Code to Product Lecture 11 — Localization— Slide 56 gidgreen.com/course
John Doe
Acme, Inc
Suite 3B-3824
294 W Ronson
Dallas TX 75211
USA
John Smith
Acme, Ltd
Flat 384
33 Walton Road
Birmingham
B26 3QJ
UK
〒100-8994
東京都中央区八重洲一丁目5番3号
東京中央郵便局
Tokyo Central Post Office
1-5-3 Yaesu, Chuo-ku
Tokyo 100-8994
Japan
C/Pescadoro, 13, 2°, 3ª
28331 – Madrid
Spain

57. Addresses
• Single multi-line field
• Change in response to country
• Generic format
From Code to Product Lecture 11 — Localization— Slide 57 gidgreen.com/course

58. Indexing, sorting, searching
• Capitalization and accents
– Øyvind matches oyvind?
• Collation (sort order)
– Swedish: a b c … x y z å ä ö
– French: cote côte coté côté
• CJK (ideographic languages)
– No spaces between words
– Sort based on stroke count
From Code to Product Lecture 11 — Localization— Slide 58 gidgreen.com/course

59. Domain names
• Country-code top-level domains
– .fr .de .uk .in .br .jp .cn
• Need separate registrar for many
• Some countries have restrictions
– .com.au requires registered company
– .ca requires nationality/residence
– Also restricted: .fr .br .cn .ie .jp …
• Internationalized domain names
From Code to Product Lecture 11 — Localization— Slide 59 gidgreen.com/course

60. And there’s more…
• Phone numbers
• Units of measurement
• Colors
• Images of people
• Calendars
• Border disputes
• Culture
• Law
From Code to Product Lecture 11 — Localization— Slide 60 gidgreen.com/course

61. Google in China
• 2005: Chinese language google.com
• 2006: google.cn under censorship
• 2009: China blocks YouTube
• 2010: Google claims hacking attack
– Redirects google.cn to google.com.hk
– China blocks it for a day
• Today: Baidu 79%, Google 17%
– Baidu links to MP3/movie downloads
From Code to Product Lecture 11 — Localization— Slide 61 gidgreen.com/course

62. Getting real
• It’s time consuming and costly
• Cheap wins in version 1.0
– Parameterize + functionize
– Use Unicode throughout
– Flexible layouts
• See where there is demand
– Identify most important locales
From Code to Product Lecture 11 — Localization— Slide 62 gidgreen.com/course

63. Getting real
• Don’t skimp the details
– Needs to look native
• Use serious service providers
• Prepare for tech support
– Machine translation an option?
• It will slow development
– So wait for product maturity
From Code to Product Lecture 11 — Localization— Slide 63 gidgreen.com/course