hpc_summary.py

#!/usr/bin/env python
import subprocess
import pandas as pd
import re

result = subprocess.run(["pbsnodeinfo"], capture_output=True, text=True)
text_file = result.stdout
lines = text_file.split('\n')

GPUtype=[]
GPUusage=[]
max_avail=[]
cur_avail=[]
used=[]

for i in range(1,len(lines)):
    s=lines[i]
    it=re.split(';|:|\|',s)
    if len(it)<6:
        continue
    GPUtype.append(it[5])
    GPUusage.append(it[6])
    values=re.split(' ',it[6])
    max_avail.append(int(values[3]))
    used.append(int(values[1]))
    cur_avail.append(int(values[3])-int(values[1]))

uniqueGPUs = list(set(GPUtype))
df2= (zip(GPUtype,used,cur_avail,max_avail))

df = pd.DataFrame (df2,columns=['GPU Type','Used','Available','Max'])
print(df)

summary=[]
for itm in range(len(uniqueGPUs)):
    slc=df['GPU Type'].str.contains(uniqueGPUs[itm], regex=False)
    itms=df[slc]
    sum_used=itms['Used'].sum(axis=0)
    sum_max=itms['Max'].sum(axis=0)
    summary.append([uniqueGPUs[itm],sum_used,sum_max-sum_used,sum_max])

summary_df = pd.DataFrame (summary,columns=['GPU Type','Used','Available','Max'])
#GPUtype
print("summary")
print(summary_df)