Hey, I agree, after going a bit through both the candidates I can see we can unload a lot of work by using a well-implemented existing parser. I think I should start by comparing both the mentioned libraries to decide which one to use. I will use the same benchmark strategy that was discussed in the issue. Does that sound good?
And also I think I can work on replacing boost spirits in GSoC then. This will be a start to the data frame idea. Even if we are left with time after this, I can start the work on the data frame as well. Is it considerable? Thanks, Gopi On Mon, Mar 29, 2021 at 7:33 PM Omar Shrit <[email protected]> wrote: > Hey Gopi, > > I totally agree with Ryan, using existing parser will accelerate the > project and allow to move forward with the dataframe class. Also, I > do believe that replacing boost Spirit with an existing parser will take > a considerable amount of the summer. > > Thanks, > > Omar > > On 03/29, Ryan Curtin wrote: > > On Mon, Mar 29, 2021 at 04:17:35PM +0530, Gopi Manohar Tatiraju wrote: > > > Would love to hear your thoughts on whether to go with an already > > > implemented parser or build a new one. Also if we are planning to > build a > > > data frame here then > > > maybe going with an in-house parser would be better as we will have the > > > ability to design it in such a way that it can extend maximum support > to > > > the new data frame > > > which we are planning to build ahead. > > > > Hey Gopi, > > > > Honestly I think it's best to use another package. Not only will this > > free up time to actually work on the dataframe class, but also it means > > we are not responsible for maintenance of the CSV parser. There are > > lots of little complexities and edge cases in parsing (not to mention > > efficiency!) and so we can probably get a lot more bang for our buck > > here by using an implementation from someone who has already put down > > the time to consider all those details. > > > > Hope this is helpful. :) > > > > Thanks, > > > > Ryan > > > > -- > > Ryan Curtin | "Kill them, Machine... kill them all." > > [email protected] | - Dino Velvet >
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