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Project description
sparrow-python
Install
pip install sparrow-python
# Or dev version
pip install sparrow-python[dev]
# Or
pip install -e .
# Or
pip install -e .[dev]
Usage
Multiprocessing SyncManager
Open server first:
$ spr start-server
The defualt port 50001.
(Process1) productor:
from sparrow.multiprocess.client import Client
client = Client(port=50001)
client.update_dict({'a': 1, 'b': 2})
(Process2) consumer:
from sparrow.multiprocess.client import Client
client = Client(port=50001)
print(client.get_dict_data())
>> > {'a': 1, 'b': 2}
Common tools
- Kill process by port
$ spr kill {port}
- pack & unpack
support archive format: "zip", "tar", "gztar", "bztar", or "xztar".
$ spr pack pack_dir
$ spr unpack filename extract_dir
- Scaffold
$ spr create awosome-project
Some useful functions
sparrow.relp
Relative path, which is used to read or save files more easily.
sparrow.performance.MeasureTime
For measuring time (including gpu time)
sparrow.performance.get_process_memory
Get the memory size occupied by the process
sparrow.performance.get_virtual_memory
Get virtual machine memory information
sparrow.add_env_path
Add python environment variable (use relative file path)
Safe logger in multiprocessing
from sparrow.log import Logger
import numpy as np
logger = Logger(name='train-log', log_dir='./logs', )
logger.info("hello", "numpy:", np.arange(10))
logger2 = Logger.get_logger('train-log')
print(id(logger2) == id(logger))
>> > True
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