Its not clear what you mean by using them one by one. but to get these values into a list. you can use regex.
depending on your needs you can process the comments further to clean them up.
Added a simple comprehension to clean the spaces and add to a dictionary.
s = '''#StationCode:4845
#InstrumentKind: CSV (20191216114518_4845)
#StartTime:2019/12/16 11:45:28.010
#RecordLength(sec):103.00
#SampleRate(Hz): 100
#AmplitudeUnit: gal. DCoffset(corr)
#AmplitudeMAX. a: 15.133 ~ -22.371
#AmplitudeMAX. b: 70.222 ~ -37.683
#AmplitudeMAX. c: 13.398 ~ -11.425
#Intensity:5.0 touC:0.059 PGA:74.4gal PGV:27.7mm/s
#Time sync.:NTP
#DataSequence: Time; a; b; c; Pd; Displacement
#Data: 4F10.3 '''
import re
comments = re.findall(r'#(.*)', s)
keys = [x.split(':')[0].strip() for x in comments]
values = [x.split(':')[1].strip() for x in comments]
comments = dict(zip(keys,values))
for k,v in comments.items():
print(f"key: {k} ---- value: {v}")
# Output:
#key: StationCode ---- value: 4845
#key: InstrumentKind ---- value: CSV (20191216114518_4845)
#key: StartTime ---- value: 2019/12/16 11
#key: RecordLength(sec) ---- value: 103.00
#key: SampleRate(Hz) ---- value: 100
#key: AmplitudeUnit ---- value: gal. DCoffset(corr)
#key: AmplitudeMAX. a ---- value: 15.133 ~ -22.371
#key: AmplitudeMAX. b ---- value: 70.222 ~ -37.683
#key: AmplitudeMAX. c ---- value: 13.398 ~ -11.425
#key: Intensity ---- value: 5.0 touC
#key: Time sync. ---- value: NTP
#key: DataSequence ---- value: Time; a; b; c; Pd; Displacement
#key: Data ---- value: 4F10.3
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