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from tabulate import tabulate
from collections import OrderedDict
vals = """
#bcftools
986798
real 3m49.024s
user 3m48.620s
sys 0m7.848s
#cyvcf2
984214
real 4m5.190s
user 4m5.048s
sys 0m0.112s
#pysam
984214
real 33m12.417s
user 33m11.920s
sys 0m0.244s
""".split("#")
vals = [x.strip() for x in vals if x.strip()]
key = 'time (seconds)'
def parse_group(g):
lines = g.split("\n")
d = OrderedDict([
('name', lines[0].strip()),
('time', next(x for x in lines if x.startswith('user')).split()[1].rstrip('s'))
])
minutes = float(d['time'].split('m')[0])
seconds = float(d['time'].split('m')[1])
d[key] = 60 * minutes + seconds
del d['time']
return d
tbl = [parse_group(g) for g in vals]
base = next(d for d in tbl if d['name'] == 'cyvcf2')[key]
for d in tbl:
d['ratio'] = "%.2f" % (d[key] / base)
d[key] = "%.1f" % d[key]
print(r"\begin{table}[h]")
print(r"\caption{Timing VCF filtering}")
print(tabulate(tbl, headers="keys", tablefmt="latex"))
print(r"\end{table}")
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