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python-3.x - 路易吉全局变量

转载 作者:行者123 更新时间:2023-12-05 06:32:41 27 4
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我想在 Luigi 中将一些目标路径设置为全局变量。

原因是我使用的目标路径是基于给定数值天气预报 (NWP) 的最后一次运行,并且需要一些时间才能获得该值。一旦我检查了哪个是最后一次运行,我就创建了一个路径,我将在其中放置几个​​目标文件(具有相同的父文件夹)。

我目前正在重复类似的调用以获取多个任务的父路径的值,将此路径设置为全局变量会更有效。我试图从一个由 luigi 类调用的函数 (get_target_path) 中定义全局变量,但当我返回到 Luigi 管道时,该全局变量似乎不再存在。

这也是我的代码的样子:

class GetNWP(luigi.Task):
"""
Download the NWP data.
"""
product_id = luigi.Parameter()
date = luigi.Parameter(default=datetime.today().strftime('%Y%m%d'))
run_hr = luigi.Parameter(default='latest')

def requires(self):
return None
def output(self):
path = get_target_path(self.product_id, self.date, self.run_hr,
type='getNWP')
return luigi.LocalTarget(path)
def run(self):
download_nwp_data(self.product_id, self.date, self.run_hr)


class GetNWP_GFS(luigi.Task):
"""
GFS data.
"""
product_id = luigi.Parameter()
date = luigi.Parameter(default=datetime.today().strftime('%Y%m%d'))
run_hr = luigi.Parameter(default='latest')

def requires(self):
return None
def output(self):
path = get_target_path(self.product_id_PV, self.date, self.run_hr,
type='getNWP_GFS')
return luigi.LocalTarget(path)
def run(self):
download_nwp_data(self.product_id, self.date, self.run_hr,
type='getNWP_GFS')


class Predict(luigi.Task):
"""
Create forecast.
"""
product_id = luigi.Parameter(default=None)
date = luigi.Parameter(default=datetime.today().strftime('%Y%m%d'))
run_hr = luigi.Parameter(default='latest')
horizon = luigi.Parameter(default='DA')

def requires(self):
return [
GetNWP_GFS(self.product_id, self.date, self.run_hr),
GetNWP(self.product_id, self.date, self.run_hr)
]
def output(self):
path = get_target_path(self.product_id, self.date, self.run_hr,
type='predict', horizon=self.horizon)
return luigi.LocalTarget(path)
def run(self):
get_forecast(self.product_id, self.date, self.run_hr)

函数 get_target_path 根据输入参数定义目标路径。我希望此函数设置可从 Luigi 访问的全局变量。例如如下(只是getNWP任务的代码):

def get_target_path(product_id, date, run_hr, type=None, horizon='DA'):
"""
Obtain target path.
"""
if type == 'getNWP_GFS':
if 'path_nwp_gfs' in globals():
return path_nwp_gfs
else:
...
elif type == 'getNWP':
if 'path_nwp_model' in globals():
return path_nwp_model
else:
filename = f'{nwp_model}_{date}_{run_hr}_{horizon}.{ext}'
path = Path(db_dflt['app_data']['nwp_folder'])
create_directory(path)
global path_nwp_model
path_nwp_model = Path(path) / filename
elif type == 'predict':
if 'path_predict' in globals():
return path_predict
else:
...

当我回到 Luigi 时,这个函数中定义的全局变量不存在。

任何关于如何解决这个问题的想法将不胜感激!

最佳答案

由于似乎没有内置方法来存储 Luigi 目标的路径,我最终决定创建一个类来保存与 Luigi 目标/路径相关的所有信息。当调用需要知道哪些是目标路径的外部函数时,此类在 Luigi 的任务中使用。

这个类在主要的 luigy 脚本中导入,并在定义任务之前实例化:

from .utils import Targets
paths = Targets()

class GetNWP(luigi.Task):
"""Download NWP data required to prepare the prediction."""

product_id = luigi.Parameter()
date = luigi.Parameter(default=datetime.today().strftime('%Y%m%d'))
run_hr = luigi.Parameter(default='latest')

def requires(self):
return GetProductInfo(self.product_id)
def output(self):
path = paths.getpath_nwp(self.product_id, self.date, self.run_hr)
path_gfs = paths.getpath_nwp_GFS(self.product_id, self.date, self.run_hr)
return [luigi.LocalTarget(path),
luigi.LocalTarget(path_gfs)]
def run(self):
download_nwp_data(self.product_id, date=self.date, run_hr=self.run_hr,
paths=paths, nwp_model=paths.nwp_model)
download_nwp_data(self.product_id, date=self.date, run_hr=self.run_hr,
paths=paths, nwp_model=paths.gfs_model)

class Predict(luigi.Task):
"""Create forecast based on the product information and NWP data."""

product_id = luigi.Parameter()
date = luigi.Parameter(default=datetime.today().strftime('%Y%m%d'))
run_hr = luigi.Parameter(default='latest')

def requires(self):
return GetNWP(self.product_id, self.date, self.run_hr)
def output(self):
path = paths.getpath_predict(self.product_id, self.date, self.run_hr)
path_gfs = paths.getpath_predict_GFS(self.product_id, self.date,
self.run_hr)
return [luigi.LocalTarget(path),
luigi.LocalTarget(path_gfs)]
def run(self):
get_forecast(product_id=self.product_id, date=self.date,
run_hr=self.run_hr, paths=paths, nwp_model=paths.nwp_model)
get_forecast(product_id=self.product_id, date=self.date,
run_hr=self.run_hr, paths=paths, nwp_model=paths.gfs_model)

其中 Targets 类具有以下结构:

class Targets:
"""Store Luigi's target paths."""

def __init__(self):
"""Initialize paths and variables."""
self.path1 = None
self.path2 = None
self.path3 = None

def update_object(self, product_id, date=None, run_hr=None):
"""Update object based on inputs."""
if self.prod_id is None:
self.prod_id = product_id
if self.path_1 is None:
self.get_path_1(product_id)
if self.path_2 is None:
self.get_path_2(product_id)
if self.path_3 is None:
self.get_path_3(product_id)

def get_path_1(self, product_id, ...)
"""Generate a path 1 for a luigi Task."""
... define self.path_1...

def get_path_2(self, product_id, ...)
"""Generate a path 2 for a luigi Task."""
... define self.path_2...

def get_path_3(self, product_id, ...)
"""Generate a path 3 for a luigi Task."""
... define self.path_3...

主要思想是只设置一次目标路径,并在每个 Luigi 任务中使用它们作为输入参数。这允许:

  • 更快地执行任务,并且
  • 避免由于新的 NWP 可用而导致目标路径发生变化的错误。

关于python-3.x - 路易吉全局变量,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/51152485/

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