[Pharo-users] NeoCSV and special handling for some columns

Sven Van Caekenberghe sven at stfx.eu
Sat Oct 3 03:39:53 EDT 2015


Yes, there are a couple of newer features that were added after the documentation was written. Keeping documentation up to date is also a PITA.

> On 03 Oct 2015, at 08:54, stepharo <stepharo at free.fr> wrote:
> 
> sven do you think that we should add this to the chapter?
> 
> 
> Le 28/9/15 16:42, Sven Van Caekenberghe a écrit :
>>> On 28 Sep 2015, at 15:04, Mariano Martinez Peck <marianopeck at gmail.com> wrote:
>>> 
>>> Imagine something like this:
>>> 
>>> neoCSVReader := (NeoCSVReader on: stream).
>>> 	neoCSVReader
>>> 		separator: $,;
>>> 		recordClass: PriceRecord;
>>> 	 	addIgnoredField; "<name>"
>>> 		addField:  #securityUniqueId: ; "<ticker>"	
>>> 		addField: #date: converter: [ :string | Date readFrom: string readStream pattern: 'yyyymmdd' ]; "<date>"
>>> 		addFloatField: #open: ; "<open>"
>>> 		addFloatField: #high: ; "<high>"
>>> 		addFloatField: #low: ; "<low>"
>>> 		addFloatField: #close: ; "<close>"
>>> 		addIntegerField: #volume: . "<vol>"
>>> 	neoCSVReader	skipHeader.
>>> 	priceRecords := neoCSVReader upToEnd.
>>> 
>>> 
>>> The #recordClass: is optional. If not, you can get an array of arrays instead.
>>> You can add #addIgnoredField for all the ones you want to ignore, then add the #addNumber: etc for the number ones, etc.
>> Correct.
>> 
>>> To write a default empty value, I would use my own converter. Something like:
>>> 
>>> addField: #stringcolumn: converter: [ :string | string isEmptyOrNil ifTrue: [ '' ]  ];
>>> addField: #numbercolumn: converter: [ :string | string isEmptyOrNil ifTrue: [ 0 ] ifFalse: [ NeoNumberParser parse: string ]  ];
>> Actually there is NeoCSVReader>>#emptyFieldValue: which you can use the configure the reader (but it counts for all fields).
>> 
>>> Hope this helps.
>>> 
>>> Cheers,
>>> 
>>> 
>>> 
>>> On Mon, Sep 28, 2015 at 9:06 AM, Nicolai Hess <nicolaihess at web.de> wrote:
>>> Hi,
>>> 
>>> I have two problems I could not solve:
>>> 
>>> 1. I would like to read only some columns: I have a large file with
>>>     ~30 colums, but I am only interested on ~5 columns
>>>     (not that important, I could pre-process the file) but anyway it would be
>>>     nice to do it in smalltalk.
>>> 
>>> 2. some columns will contain only strings (quoted values) and some only numbers,
>>>     but the field may be empty, is it possible to define the default "emptyValue" as an
>>>     - empty string for empty fields in the "string column"
>>>     - 0 for empty fields in the "number column"?
>>> 
>>> 
>>> thanks
>>>  in advance
>>> 
>>> nicolai
>>> 
>>> 
>>> 
>>> -- 
>>> Mariano
>>> http://marianopeck.wordpress.com
>> 
>> 
> 
> 





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