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Re: best way to handle this in Python

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On Fri, 20 Jul 2012 06:34:47 -0400, Rita <rmorgan466@gmail.com>
declaimed the following in gmane.comp.python.general:

> Thats an interesting data structure Dennis. I will actually be running this
> type of query many times preferable in an ad-hoc environment. That makes it
> tough for sqlite3 since there will be several hundred thousand tuples.
>
	Given the sample data, it wouldn't be that difficult...

table:
	ID			#primary key -- I always include an autoincrement ID
	timepoint	datetime	#the date/time info from the file name
	color		char	#the name of the color
	value		integer	#the count (or whatever that represented)

	You could reduce the table size some by adding a bit of runtime
processing...

	...
	timepoint	foreign key files (timepoint)
	...

files
	ID
	name	char	#path/name of the source file 
	timepoint	datetime	#the date/time from the file name


	Finding out which new files need to be loaded would involve

select max(timepoint) from files;

as that identifies the newest file already loaded.

	Depending on nature of queries you could then do things like

select color, sum(values) from table
	inner join files on table.timepoint = files.ID
group by table.color
where files.timepoint >= "first time of interest"
	and files.timepoint <= "last time of interest"
order by color

{The "where" clause might need to be a "having" clause}
-- 
	Wulfraed                 Dennis Lee Bieber         AF6VN
        wlfraed@ix.netcom.com    HTTP://wlfraed.home.netcom.com/

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Re: best way to handle this in Python Dennis Lee Bieber <wlfraed@ix.netcom.com> - 2012-07-20 14:22 -0400

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