A bunch tools I have created over the years
Project description
Slurm
This is a collection of tools I have used over the years collected together.
Signal Catcher
SignalCatch
catches SIGINT
and SIGTERM
signals and sets
SignalCatch.kill
to True
.
from slurm import SignalCatch
sig = SignalCatch()
while True:
if sig.kill == True:
exit(0)
Simple Processes
from slurm import SimpleProcess
def func():
# some simple process that does something
for _ in range(10):
print(".", end="")
time.sleep(0.1)
print("")
def test_process():
p = SimpleProcess()
p.start(func)
print(p)
p.join(timeout=2.0) # if not ended in 2 sec, will terminate() the process
Storage
from slurm import storage
pick = storage.read("file.pickle")
yaml = storage.read("file.yaml")
json = storage.read("file.json")
json = storage.read("file", "json")
data = [1,2,3,4]
storage.write("tom.pickle", data)
storage.write("bob.json", data)
storage.write("guess.file", data, "yml")
Also, for YAML files, you can put comments in:
info = {
"a": 1
}
num = 5
comm = f"""
# hello {num} dogs!!
# there
# big boy
"""
storage.write("t.yaml", info, comments=comm)
which will produce:
# hello 5 dogs!!
# there
# big boy
a: 1
Science Storage
Over the years I have collected a lot of data, but not completely documented the sensors or their settings. I am trying to setup a data file that can:
- use primarly standard python libraries to read data files
- self documenting with info and
namedtuples
- can use
gzip
for compression of large files
from slurm import scistorage
from collections import namedtuple
Sensor = namedtuple("Sensor","x y z")
# document sensor setting in this data file
# there is no real format for this, just put good
# stuff here
info = {
"TFmini": {
"min": 0.3,
"max": 12.0,
"fov_deg": 4.6,
"units": "m"
},
"LSM6DSOX": {
"accel": {
"range": (-4,4),
"units": "g"
},
"gyro": {
"range": (-2000,2000),
"units": "dps"
}
},
"LIS3MDL": {
"range": (-4,4), # 4 gauss = 400 uT
"units": "gauss"
},
"DPS310": {
"sensors": ("temperature", "pressure")
}
}
data = [] # some data stored in an array or deque
for i in range(100):
data.append(Sensor(i,i,i)) # pretend you got some data from a sensor
scistorage.write(info, data, "data.pkl.gz") # *.gz uses gzip compression
bag = scistorage.read("data.pkl.gz")
print(bag["info"])
print(bag["data"])
Network
from slurm import network
print(network.get_ip()) # -> ip_address
print(network.host()) # -> (hostname, ip_address)
Sleep Rate
Will sleep for a prescribed amount of time inside of a loop irregardless of how long the loop takes
from slurm import Rate
rate = Rate(10) # let loop run at 10 Hz
while True:
# do some processing
rate.sleep()
Files
from slurm.files import rmdir, mkdir, run, rm, find
mkdir("some/path")
rmdir("some/path")
rm("/path/file.txt")
rm(["path/a.txt", "path/2/b.txt", "path/3/c.txt"])
find("/path/to/somewhere", "file_to_find") # -> list
find("/path/to/somewhere", "*.html") # -> list
run("ls -alh") # -> output
MIT License
Copyright (c) 2014 Kevin J. Walchko
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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