It's common to filter repeated reads from a fastq or fasta file. With recent high-throughput sequencing output reaching ... hi throughput, it's no longer feasible to hold all reads in an in-memory datastructure to determine uniqueness.
fastq-unique.py is an example of using a bloom-filter as a pre-filter for a more memory intensive python set. It filters to unique sequences and prints information on the number of false positives in the bloom filter.
$ time python fastq-unique.py < /usr/local/src/methylcode/data/dme/en.wt.1.fastq > unique.fastq 36754782 records in file checking 2525155 potential duplicates in a python set 4699 false-positive duplicates in the bloom filter real 11m31.077s user 11m1.937s sys 0m23.093s