Delphi TQuery Save To Csv File
– Compiling project groups even of relatively small projects can generate ‘Out of Memory’ exceptions. I have been plagued with such errors since upgrading to XE3, and they are sadly still present in XE4. Reading the newsgroups I have found posts indicating some users are experiencing these errors in earlier versions as well.
Today I stumbled across a fix, which apparently has been out for a while (5 days), but was unknown to me. I read the Delphi blogs almost daily, and frequent the newsgroups weekly, yet I had never heard of a solution for this issue, so I thought I would let.
Delphi enables your applications to use SQL syntax directly though TQuery component to access data from: Paradox and dBase tables How to Embed Media Files into a Delphi Executable (RC/.RES). Creating a Delphi Notepad: Open and Save. Multithreaded Delphi Database Queries with dbGo (ADO). How to read a dbf file from Delphi 5 or above? I made an export-function to easily export a dataset to a csv-file. { Save a bookmark to return to.
KevinBlack 6-Nov-15 12:49 6-Nov-15 12:49 Hi Vladimir, Apologies for bothering you again, but a perplexing issue. If I call CSVRead.Free (and don't handle the exception) I get an App Crash - Runtime Error 216.
FWIW, this code is in a Delphi DLL. If I single step through the code, the CSVRead.Free causes an Access Violation when executing the CSVRead.Free statement: finally CSVRead.Close; CSVRead.Free; // AV Here if I single step through the code end; Unhandled I get this followed by the Runtime Error 216 Message. KevinBlack 3-Nov-15 14:24 3-Nov-15 14:24 Hi Vladimir, I've used your components to decode a CSV string and for the most part it works fine.
Where there is a significant issue (and maybe I'm just doing it wrong), but in the CSV file most lines have 10 fields HOWEVER one line in the middle of the CSV string has only 7 fields. Your component just aborts when it detects a line that has a different number of fields to that specified initially or autodetected in the first line. In a perfect world, all lines would have the same number of fields, but this is not a perfect world.
How can I either just process the line as is or ignore it (perhaps logging the fact that there was a discrepancy in the field count. That is essentially: If an error is detected in the field count DO NOT ABORT simply set an error variable (or whatever) and move on to the next line. OR: I know this would slow things down, but for me it would work. Have a property that calculates the fieldcount NOT using the first line, but for every line: FieldCount_AutoDetect_Always:= True; So if this is true it ignores and FieldCount_AutoDetect settings and calculates the field count on a line for line basis. As you know, it is always the edge cases that cause the grief. Thank you for an excellent unit, but with an issue for me.
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Thanks, Kevin. Hi Kevin, Thank you for a good question. The problem is in the fact that because of the nature of CSV format it is practically impossible to come up with general error recovery algorithm though other than that CSV format is very “compact” and elegant. Here are some examples to demonstrate scale of a problem: - Source has multiline field values. Error within multiline value before “internal” end of line. If try to recover and continue then this end of line will be considered as end of record and everything breaks loose with hard to imagine outcome.
- Error that leads to reading of “unpaired” double quote (no more double quotes in the source). Then algorithm will read rest of source as single value and will detect error only at the end of the source. The number of possible situations looks countless.
To deal with such a problem it probably needs development of some kind of Artificial Intelligence (AI), which, of course, is interesting but hardly practical. Even in simplest situations when some records seemingly have absolutely valid format and just have insufficient number of fields then it is still unclear how to interpret those records.
Which fields are missing: leading or trailing or mixed set? Obviously those records should not be trusted and probably should be discarded. But probably whole file containing those records cannot be trusted. And I am not even consider situation when number of field is greater because it complicates situation even more. In other words, so far I do not see any other “efficient” approach in dealing with CSV error except “manual” human intervention in fixing CSV source. I actually already had plans to implement everything you proposed (indeed, I also live in real world). I just need to find time to present it all in one “sane package”.
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