# sparrow-python
[](https://pypi.org/project/sparrow-python)
[](https://www.python.org/)
[](LICENSE)
[](https://github.com/beidongjiedeguang)
-------------------------
## Install
```bash
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:
```bash
$ spr start-server
```
The defualt port `50001`.
(Process1) productor:
```python
from sparrow.multiprocess.client import Client
client = Client(port=50001)
client.update_dict({'a': 1, 'b': 2})
```
(Process2) consumer:
```python
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**
```bash
$ spr kill {port}
```
- **pack & unpack**
support archive format: "zip", "tar", "gztar", "bztar", or "xztar".
```bash
$ spr pack pack_dir
```
```bash
$ spr unpack filename extract_dir
```
- **Scaffold**
```bash
$ 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`
```python
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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