4 reactions
WTTSMJGPJRIFPBASClangstats: Languages stats with ISO codes, speakers count, countries list and its population
When I work on multi-lingual projects it's always takes time to score and prioritize localization process.
Even in case with machine translation, this is still a problem, because you can't just translate all languages in the world, because it takes long time, and will spend you money when LLM will generate grabage like chars "aa" repeated thousands times in row.
Now you may hit `npm i langstats` and fetch top languages, optionally filter out languages by target countries where your app is present, then leave top N languages and have a list of languages for translation.
Simple demo that is just draw stats of top 20 spoken languages:
```
Top languages:
#1 Chinese (zh,zho)
- Total speakers: 1299877520
#2 English (en,eng)
- Total speakers: 1132366680
- Top 10 countries where used: India, United States, Pakistan, Nigeria, Philippines, United Kingdom, South Africa, Tanzania, Kenya, Uganda
#3 hinese (cmn)
- Total speakers: 897071810
#4 panish (es,spa)
- Total speakers: 485000000
- Top 10 countries where used: Mexico, Colombia, Spain, Argentina, Venezuela, Chile, Guatemala, Ecuador, Bolivia, Honduras
#5 rabic (ar,ara)
- Total speakers: 422000000
- Top 10 countries where used: Egypt, Algeria, Afghanistan, Sudan, Iraq, Morocco, Morocco, Saudi Arabia, Yemen, Syria
#6 angla (bn,ben)
- Total speakers: 300000000
- Top 10 countries where used: Bangladesh
#7 ortuguese (pt,por)
- Total speakers: 254300000
- Top 10 countries where used: Brazil, Angola, Portugal, Timor-Leste, Cape Verde, São Tomé & PrÃncipe
#8 rench (fr,fra)
- Total speakers: 208157220
- Top 10 countries where used: Congo - Kinshasa, France, Canada, Côte d’Ivoire, Cameroon, Chad, Senegal, Rwanda, Benin, Burundi
#9 ndonesian (id,ind)
- Total speakers: 198996550
- Top 10 countries where used: Indonesia
#10 ussian (ru,rus)
- Total speakers: 171428900
- Top 10 countries where used: Russia, Kazakhstan, Tajikistan, Belarus
#11 apanese (ja,jpn)
- Total speakers: 128000000
- Top 10 countries where used: Japan, Palau
#12 unjabi (pa,pan)
- Total speakers: 125000000
#13 erman (de,deu)
- Total speakers: 105000000
- Top 10 countries where used: Germany, Belgium, Austria, Switzerland, Luxembourg, Liechtenstein
#14 Egyptian Arabic (arz)
- Total speakers: 100542400
#15 avanese (jv,jav)
- Total speakers: 84308740
#16 arathi (mr,mar)
- Total speakers: 83100000
#17 wahili (swh)
- Total speakers: 82300000
#18 urkish (tr,tur)
- Total speakers: 82231620
- Top 10 countries where used: Türkiye, Cyprus
#19 elugu (te,tel)
- Total speakers: 82000000
#20 u Chinese (wuu)
- Total speakers: 81400000
```
#programming #js #dev #technology
When I work on multi-lingual projects it's always takes time to score and prioritize localization process.
Even in case with machine translation, this is still a problem, because you can't just translate all languages in the world, because it takes long time, and will spend you money when LLM will generate grabage like chars "aa" repeated thousands times in row.
Now you may hit `npm i langstats` and fetch top languages, optionally filter out languages by target countries where your app is present, then leave top N languages and have a list of languages for translation.
Simple demo that is just draw stats of top 20 spoken languages:
```
Top languages:
#1 Chinese (zh,zho)
- Total speakers: 1299877520
#2 English (en,eng)
- Total speakers: 1132366680
- Top 10 countries where used: India, United States, Pakistan, Nigeria, Philippines, United Kingdom, South Africa, Tanzania, Kenya, Uganda
#3 hinese (cmn)
- Total speakers: 897071810
#4 panish (es,spa)
- Total speakers: 485000000
- Top 10 countries where used: Mexico, Colombia, Spain, Argentina, Venezuela, Chile, Guatemala, Ecuador, Bolivia, Honduras
#5 rabic (ar,ara)
- Total speakers: 422000000
- Top 10 countries where used: Egypt, Algeria, Afghanistan, Sudan, Iraq, Morocco, Morocco, Saudi Arabia, Yemen, Syria
#6 angla (bn,ben)
- Total speakers: 300000000
- Top 10 countries where used: Bangladesh
#7 ortuguese (pt,por)
- Total speakers: 254300000
- Top 10 countries where used: Brazil, Angola, Portugal, Timor-Leste, Cape Verde, São Tomé & PrÃncipe
#8 rench (fr,fra)
- Total speakers: 208157220
- Top 10 countries where used: Congo - Kinshasa, France, Canada, Côte d’Ivoire, Cameroon, Chad, Senegal, Rwanda, Benin, Burundi
#9 ndonesian (id,ind)
- Total speakers: 198996550
- Top 10 countries where used: Indonesia
#10 ussian (ru,rus)
- Total speakers: 171428900
- Top 10 countries where used: Russia, Kazakhstan, Tajikistan, Belarus
#11 apanese (ja,jpn)
- Total speakers: 128000000
- Top 10 countries where used: Japan, Palau
#12 unjabi (pa,pan)
- Total speakers: 125000000
#13 erman (de,deu)
- Total speakers: 105000000
- Top 10 countries where used: Germany, Belgium, Austria, Switzerland, Luxembourg, Liechtenstein
#14 Egyptian Arabic (arz)
- Total speakers: 100542400
#15 avanese (jv,jav)
- Total speakers: 84308740
#16 arathi (mr,mar)
- Total speakers: 83100000
#17 wahili (swh)
- Total speakers: 82300000
#18 urkish (tr,tur)
- Total speakers: 82231620
- Top 10 countries where used: Türkiye, Cyprus
#19 elugu (te,tel)
- Total speakers: 82000000
#20 u Chinese (wuu)
- Total speakers: 81400000
```
#programming #js #dev #technology
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