I suppose if you really wanted to do it in one pass pysam would be an option. Courtesy of ChatGPT with a few modifications.

import pysam
import gzip

bam_file = 'path_to_your.bam'  # Replace with your BAM file path

# Function to convert a BAM read to a FASTQ entry
def bam_read_to_fastq(read):
    name = read.query_name
    seq = read.query_sequence
    qual = read.qual
    return f"@{name}\n{seq}\n+\n{qual}\n"

# Open the BAM file
bam = pysam.AlignmentFile(bam_file, "rb")

# Open output FASTQ files for writing
mapped_fastq = gzip.open('mapped.fastq.gz', 'wt')
unmapped_fastq = gzip.open('unmapped.fastq.gz', 'wt')

# Iterate over reads and write to appropriate FASTQ file
for read in bam:
    if read.is_unmapped:
        unmapped_fastq.write(bam_read_to_fastq(read))
    else:
        mapped_fastq.write(bam_read_to_fastq(read))

# Close the files
bam.close()
mapped_fastq.close()
unmapped_fastq.close()

This will be slower than using samtools to split the bam into into a mapped and unmapped bam, and then converting those two bams to fastq files.

samtools view -@6 -O BAM -F4 -o mapped.bam -U unmapped.bam input.bam

samtools fastq -@6 mapped.bam | gzip > mapped.fastq.gz
samtools fastq -@6 unmapped.bam | gzip > unmapped.fastq.gz