Talk:Board table: Difference between revisions
(I'll work on the script after I'm done with a compo related project) |
(→toms shoes gandhi: new section) |
||
Line 5: | Line 5: | ||
You got a point. Although even better, the table could be downloaded in txt. I always throught it could be amazing to have the board list when going to a garage sale and you see games you don't remember which board they use (to use them for donnor cart). Now that I have a powerpak, I don't need devcarts anymore though so this is no problem anymore for me, therefore I didn't think about the offline thing. Your tool in Python sounds good but shouldn't it be a bit hard to do ? Well if you feel like it I'm not preventing anyone from doing it.Bregalad 19:50, 8 June 2011 (UTC) | You got a point. Although even better, the table could be downloaded in txt. I always throught it could be amazing to have the board list when going to a garage sale and you see games you don't remember which board they use (to use them for donnor cart). Now that I have a powerpak, I don't need devcarts anymore though so this is no problem anymore for me, therefore I didn't think about the offline thing. Your tool in Python sounds good but shouldn't it be a bit hard to do ? Well if you feel like it I'm not preventing anyone from doing it.Bregalad 19:50, 8 June 2011 (UTC) | ||
:The Python program wouldn't be too hard. It would go essentially like this: load the XML from NesCartDB, load the existing rarity value for each title (NesCartDB doesn't track these), and then for each title that was released in the NTSC NES region, spit out the mapper number and board name in wiki table format that I can paste here. I might work on it after I finish my current project, which is related to the NESdev compo hosted by NA. --[[User:Tepples|Tepples]] 01:36, 9 June 2011 (UTC) | :The Python program wouldn't be too hard. It would go essentially like this: load the XML from NesCartDB, load the existing rarity value for each title (NesCartDB doesn't track these), and then for each title that was released in the NTSC NES region, spit out the mapper number and board name in wiki table format that I can paste here. I might work on it after I finish my current project, which is related to the NESdev compo hosted by NA. --[[User:Tepples|Tepples]] 01:36, 9 June 2011 (UTC) | ||
== toms shoes gandhi == | |||
How to identify the pros and cons quality shoes | |||
advanced lead consumption pricing outdoor leather lightweight weyco markets from includes majority remains income include currency this importer sales emerging decline more money efforts west record companies dominated demand generating bargains leader running sports tescovisitor acquired accounting barry sellers have months shift drives regional operating high manufacture recorded pressures flexibility including reports down example materials retailers continue less deckers terms impacted slowing five score mostly volume consumers puma specific outsourcing association across been imports factors recession cheaper customer therefore hungary economy brazil forward confidence movement revenue annually like purchases leading reach takes associated source ambience according nike footwear adidas market around find leaders costs expansion falling exports popularizing hard looking verdict many lacrosse largest diversified large used brunt forced growth production second dress shoes vietnam pairs china post first designer consumer last strong brands size that primark rate practices common borne vans tennis increasing athletic timberland outside simple grew labor poland there lower products brown global builds kenneth shopping revenues workforce paulo different brantano younger wolverine marketline africa increasingly faced will wearing range fuelled only whereas domestic brought country fragmented taiwan india with research service highly gucci witnessing year permit indonesia since toward exceeding come billion branded rncos offerings cheap advantageous close presence western apparel analysts appreciation annual independent along almost easy driven million moving people each rising shoe their offer cutting retail average price asia product economic producing clarks excess online promotional likely foster than levels south bata cole because competitive priced which shop overall countries casual often industry basketball sector convenience years make types skilled outlook developed expected chinese rebound consume focusing combined compete predicted higher material also smaller over alpargatas environment spending manufactured players fast value other demographic loyalty such zone |
Revision as of 15:47, 17 June 2013
Old and outdated
Man I can't belive this old and outdated table has been copied to this wiki. Shouldn't a link to the complete and recently updated Bootgod's database be better ?!?Bregalad 18:35, 8 June 2011 (UTC)
- This page can be downloaded as HTML and searched offline with Ctrl+F in a web browser. What tool do you recommend for displaying and searching the NesCartDB XML offline? I could make a short Python program that updates this table from the XML; would that be better? --Tepples 19:22, 8 June 2011 (UTC)
You got a point. Although even better, the table could be downloaded in txt. I always throught it could be amazing to have the board list when going to a garage sale and you see games you don't remember which board they use (to use them for donnor cart). Now that I have a powerpak, I don't need devcarts anymore though so this is no problem anymore for me, therefore I didn't think about the offline thing. Your tool in Python sounds good but shouldn't it be a bit hard to do ? Well if you feel like it I'm not preventing anyone from doing it.Bregalad 19:50, 8 June 2011 (UTC)
- The Python program wouldn't be too hard. It would go essentially like this: load the XML from NesCartDB, load the existing rarity value for each title (NesCartDB doesn't track these), and then for each title that was released in the NTSC NES region, spit out the mapper number and board name in wiki table format that I can paste here. I might work on it after I finish my current project, which is related to the NESdev compo hosted by NA. --Tepples 01:36, 9 June 2011 (UTC)
toms shoes gandhi
How to identify the pros and cons quality shoes
advanced lead consumption pricing outdoor leather lightweight weyco markets from includes majority remains income include currency this importer sales emerging decline more money efforts west record companies dominated demand generating bargains leader running sports tescovisitor acquired accounting barry sellers have months shift drives regional operating high manufacture recorded pressures flexibility including reports down example materials retailers continue less deckers terms impacted slowing five score mostly volume consumers puma specific outsourcing association across been imports factors recession cheaper customer therefore hungary economy brazil forward confidence movement revenue annually like purchases leading reach takes associated source ambience according nike footwear adidas market around find leaders costs expansion falling exports popularizing hard looking verdict many lacrosse largest diversified large used brunt forced growth production second dress shoes vietnam pairs china post first designer consumer last strong brands size that primark rate practices common borne vans tennis increasing athletic timberland outside simple grew labor poland there lower products brown global builds kenneth shopping revenues workforce paulo different brantano younger wolverine marketline africa increasingly faced will wearing range fuelled only whereas domestic brought country fragmented taiwan india with research service highly gucci witnessing year permit indonesia since toward exceeding come billion branded rncos offerings cheap advantageous close presence western apparel analysts appreciation annual independent along almost easy driven million moving people each rising shoe their offer cutting retail average price asia product economic producing clarks excess online promotional likely foster than levels south bata cole because competitive priced which shop overall countries casual often industry basketball sector convenience years make types skilled outlook developed expected chinese rebound consume focusing combined compete predicted higher material also smaller over alpargatas environment spending manufactured players fast value other demographic loyalty such zone