assetid 1.0.0

# assetid [](https://travis-ci.org/axiom-data-science/assetid)

Axiom数据科学开发和使用的海洋数据资产ID解析器


## 安装

##### 稳定版本

pip安装assetid

##### 开发版本

pip install git+https://github.com/axiom-data-science/assetid.git


### IOOS URNs
[更多信息](https://geo-ide.noaa.gov/wiki/index.php?title=IOOS_Conventions_for_Observing_Asset_Identifiers)

###### URN标准化

示例

```python
from assetid.urn import IoosUrn

u = IoosUrn(asset_type='station', authority='axiom', label='station1')

print(u.__dict__)
# {'asset_type': 'station',
# 'authority': 'axiom',
# 'component': None,
# 'label': 'station1',
# 'discriminant': None}

print(u.urn)
# 'urn:ioos:station:axiom:station1'
```

```python
from assetid.urn import IoosUrn

u = IoosUrn.from_string('urn:ioos:station:axiom:station1')

print(u.__dict__)
# {'asset_type': 'station',
# 'authority': 'axiom',
# 'component': None,
# 'label': 'station1',
# 'discriminant': None}

print(u.urn)
# 'urn:ioos:station:axiom:station1'
```

```python
from assetid.urn import IoosUrn

# NetCDF变量属性来自一个“sensor”URN
print(IoosUrn.from_string('urn:ioos:sensor:axiom:station1').attributes())
# {'standard_name': 'wind_speed'}

print(IoosUrn.from_string('urn:ioos:sensor:axiom:foo:lwe_thickness_of_precipitation_amount#cell_methods=time:mean,time:variance;interval=pt1h').attributes())
# {'standard_name': 'lwe_thickness_of_precipitation_amount',
# 'cell_methods': 'time: mean time: variance (interval: PT1H)'}

# URN来自`dict`变量属性
attributes = {'standard_name': 'wind_speed',
'cell_methods': 'time: mean (interval: PT24H)'}
打印(IoosUrn.from_dict('authority', 'label', attributes).urn)
# 'urn:ioos:sensor:authority:label:wind_speed#cell_methods=time:mean;interval=pt24h'

# 来自`netCDF4`变量对象的URN
nc = netCDF4.Dataset('http://thredds45.pvd.axiomalaska.com/thredds/dodsC/grabbag/USGS_CMG_WH_OBS/WFAL/9001rcm-a.nc')
打印(IoosUrn.from_dict('authority', 'label', nc.variables['T_28'].dict).urn)
# 'urn:ioos:sensor:authority:label:sea_water_temperature'
```