November 20, 2023
Memory Usage
#
def memory():
with open('/proc/meminfo', 'r') as mem:
ret = {}
tmp = 0
for i in mem:
sline = i.split()
if str(sline[0]) == 'MemTotal:':
ret['total'] = int(sline[1])
elif str(sline[0]) in ('MemFree:', 'Buffers:', 'Cached:'):
tmp += int(sline[1])
ret['free'] = tmp
ret['used'] = int(ret['total']) - int(ret['free'])
return ret
No Hang Up
#
nohup jupyter notebook --no-browser > notebook.log 2>&1 &
Workaround: no cells output
#
se = time.time()
print(train.rdd.getNumPartitions())
print(test.rdd.getNumPartitions())
e = time.time()
print("Training time = {}".format(e - se))
your_float_variable = (e - se)
comment = "Training time for getnumpartition:"
# Open the file in append mode and write the comment and variable
with open('output.txt', 'a') as f:
f.write(f"{comment} {your_float_variable}\n")
June 20, 2023
1- Download packages locally using a requirements file or download a single package
pip download -r requirements.txt
## Example - single package
python -m pip download \
--only-binary=:all: \
--platform manylinux1_x86_64 --platform linux_x86_64 --platform any \
--python-version 39 \
--implementation cp \
--abi cp39m --abi cp39 --abi abi3 --abi none \
scipy
2- Copy them to the a temporary folder in your remote machine
3- On your machine, Activate conda and then install them using pip - specify installation options
...