MySQL : retrieve a large select by chunks

You could try using the LIMIT feature. If you do this: SELECT * FROM MyTable ORDER BY whatever LIMIT 0,1000 You’ll get the first 1,000 rows. The first LIMIT value (0) defines the starting row in the result set. It’s zero-indexed, so 0 means “the first row”. The second LIMIT value is the maximum number … Read more

Store and read hash and array in files in Perl

You’re looking for data serialisation. Popular choices that are robust are Sereal, JSON::XS and YAML::XS. Lesser known formats are: ASN.1, Avro, BERT, BSON, CBOR, JSYNC, MessagePack, Protocol Buffers, Thrift. Other often mentioned choices are Storable and Data::Dumper (or similar)/eval, but I cannot recommend them because Storable’s format is Perl version dependent, and eval is unsafe … Read more

How to generate and prompt to save a file from content in the client browser? [duplicate]

This “FileSaver” library may help. If you want it to be reasonably cross-browser, you’ll also need this to implement the W3C Blob API in places it’s not already implemented. Both respect namespaces, and are completely framework agnostic, so don’t worry about naming issues. Once you’ve got those included, and as long as you’re only saving … Read more

Saving the highscore for a game?

I recommend you use shelve. For example: import shelve d =‘score.txt’) # here you will save the score variable d[‘score’] = score # thats all, now it is saved on disk. d.close() Next time you open your program use: import shelve d =‘score.txt’) score = d[‘score’] # the score is read from disk … Read more

Best method of saving data

If your data are pretty simple, like just collections of collections of strings or numbers, I would use json. What JSON is, is a string representation of simple data types and combinations of simple data types. Once you use the json module to convert your data to a string, you write it to a file … Read more

save numpy array in append mode

The build-in .npy file format is perfectly fine for working with small datasets, without relying on external modules other then numpy. However, when you start having large amounts of data, the use of a file format, such as HDF5, designed to handle such datasets, is to be preferred [1]. For instance, below is a solution … Read more