How to use the pyfaidx.Faidx function in pyfaidx

def test_key_function_by_fetch(self):
        faidx = Faidx('data/genes.fasta', split_char='|', duplicate_action="drop")
        expect = 'TTGAAGATTTTGCATGCAGCAGGTGCGCAAGGTGAAATGTTCACTGTTAAA'
        result = faidx.fetch('KF435150.1',
                             100, 150)
        assert str(result) == expect

def test_fetch_middle(self):
        faidx = Faidx('data/genes.fasta')
        expect = 'TTGAAGATTTTGCATGCAGCAGGTGCGCAAGGTGAAATGTTCACTGTTAAA'
        result = faidx.fetch('gi|557361099|gb|KF435150.1|',
                             100, 150)
        assert str(result) == expect

fasta = genes.readlines()
        n_lines = sum(1 for line in fasta)
        for n in range(n_lines):
            with NamedTemporaryFile(mode='w') as lines:
                for i, line in enumerate(fasta):
                    if i == n and line[0] != '>' and len(line) == 71:
                        line = line[:-3] + '\n'
                        full_line = True
                    elif i == n:
                        full_line = False
                    lines.write(line)
                    lines.flush()
                name = lines.name
                if full_line:
                    try:
                        Faidx(name)
                        indexed.append(True)
                    except FastaIndexingError:
                        indexed.append(False)
        assert not any(indexed)

def test_reindex_on_modification(self):
        """ This test ensures that the index is regenerated when the FASTA
        modification time is newer than the index modification time.
        mdshw5/pyfaidx#50 """
        faidx = Faidx('data/genes.fasta')
        index_mtime = getmtime(faidx.indexname)
        faidx.close()
        os.utime('data/genes.fasta', (index_mtime + 10, ) * 2)
        time.sleep(2)
        faidx = Faidx('data/genes.fasta')
        assert getmtime(faidx.indexname) > index_mtime

def __init__(self):
        self.fasta = os.path.join(path, 'data/genes.fasta')
        self.faidx = Faidx(self.fasta, default_seq='N')

default='tumor_fa'
    parser.add_argument('-o','--output',default=default,type=check_output_folder,metavar='DIR',
        help='output directory [{}]'.format(default))
    default=50
    parser.add_argument('-w','--width',default=default,type=int,metavar='INT',
        help='the line width of output fasta files [{}]'.format(default))
    default=1
    parser.add_argument('--cores',type=int,default=default,metavar='INT',
        help='number of cores used to run the program [{}]'.format(default))

    args=parser.parse_args()

    os.mkdir(args.output,mode=0o755)
    normal_fa=args.normal.split(',')
    for fa in normal_fa:
        pyfaidx.Faidx(fa)
    pool=multiprocessing.Pool(processes=args.cores)
    results=[]
    for node_chain in glob.glob(os.path.join(args.chain,'node*.chain')):
        results.append(pool.apply_async(build_fasta,args=(args.output,node_chain,normal_fa,args.width)))
    pool.close()
    pool.join()
#handle exceptions if any
    for result in results:
        result.get()

    t1 = time.time()
    print ("Total time running {}: {} seconds".format
       (prog, str(t1-t0)))

def pyfaidx_faidx(n):
        print('timings for pyfaidx.Faidx')
        ti = []
        tf = []
        for _ in range(n):
            t = time.time()
            f = pyfaidx.Faidx(fa_file.name)
            ti.append(time.time() - t)

            t = time.time()
            read_faidx(f, headers)
            tf.append(time.time() - t)
            os.remove(index)
        # profile memory usage and report timings
        tracemalloc.start()
        f = pyfaidx.Faidx(fa_file.name)
        read_faidx(f, headers)
        os.remove(index)
        print(tracemalloc.get_traced_memory())
        print(mean(ti))
        print(mean(tf)/nreads/10*1000*1000)
        tracemalloc.stop()

def pyfaidx_bgzf_faidx(n):
        print('timings for pyfaidx.Faidx with bgzf compression')
        ti = []
        tf = []
        for _ in range(n):
            t = time.time()
            f = pyfaidx.Faidx(fa_file.name + '.gz')
            ti.append(time.time() - t)

            t = time.time()
            read_faidx(f, headers)
            tf.append(time.time() - t)
            os.remove(index)
        # profile memory usage and report timings
        tracemalloc.start()
        f = pyfaidx.Faidx(fa_file.name + '.gz')
        read_faidx(f, headers)
        os.remove(index)
        print(tracemalloc.get_traced_memory())
        print(mean(ti))
        print(mean(tf)/nreads/10*1000*1000)
        tracemalloc.stop()

def genomesize(fasta=None):
    '''
    Extract genome size from .fa file.
    '''
    fa=pyfaidx.Faidx(fasta)
    gsize=0
    for chroms in fa.index.keys():
        gsize+=fa.index[chroms].rlen
    return gsize