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config.py
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config.py
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from __future__ import print_function, division, absolute_import
import ast
import os
import sys
import threading
try:
import yaml
except ImportError:
yaml = None
from .compatibility import makedirs, builtins, Mapping, string_types
no_default = '__no_default__'
paths = [
os.getenv('DASK_ROOT_CONFIG', '/etc/dask'),
os.path.join(sys.prefix, 'etc', 'dask'),
os.path.join(os.path.expanduser('~'), '.config', 'dask'),
os.path.join(os.path.expanduser('~'), '.dask')
]
if 'DASK_CONFIG' in os.environ:
PATH = os.environ['DASK_CONFIG']
paths.append(PATH)
else:
PATH = os.path.join(os.path.expanduser('~'), '.config', 'dask')
global_config = config = {}
config_lock = threading.Lock()
defaults = []
def update(old, new, priority='new'):
""" Update a nested dictionary with values from another
This is like dict.update except that it smoothly merges nested values
This operates in-place and modifies old
Parameters
----------
priority: string {'old', 'new'}
If new (default) then the new dictionary has preference.
Otherwise the old dictionary does.
Examples
--------
>>> a = {'x': 1, 'y': {'a': 2}}
>>> b = {'x': 2, 'y': {'b': 3}}
>>> update(a, b) # doctest: +SKIP
{'x': 2, 'y': {'a': 2, 'b': 3}}
>>> a = {'x': 1, 'y': {'a': 2}}
>>> b = {'x': 2, 'y': {'b': 3}}
>>> update(a, b, priority='old') # doctest: +SKIP
{'x': 1, 'y': {'a': 2, 'b': 3}}
See Also
--------
dask.config.merge
"""
for k, v in new.items():
if k not in old and isinstance(v, Mapping):
old[k] = {}
if isinstance(v, Mapping):
if old[k] is None:
old[k] = {}
update(old[k], v, priority=priority)
else:
if priority == 'new' or k not in old:
old[k] = v
return old
def merge(*dicts):
""" Update a sequence of nested dictionaries
This prefers the values in the latter dictionaries to those in the former
Examples
--------
>>> a = {'x': 1, 'y': {'a': 2}}
>>> b = {'y': {'b': 3}}
>>> merge(a, b) # doctest: +SKIP
{'x': 1, 'y': {'a': 2, 'b': 3}}
See Also
--------
dask.config.update
"""
result = {}
for d in dicts:
update(result, d)
return result
def normalize_key(key):
""" Replaces underscores with hyphens in string keys
Parameters
----------
key : string, int, or float
Key to assign.
"""
if isinstance(key, string_types):
key = key.replace('_', '-')
return key
def normalize_nested_keys(config):
""" Replaces underscores with hyphens for keys for a nested Mapping
Examples
--------
>>> a = {'x': 1, 'y_1': {'a_2': 2}}
>>> normalize_nested_keys(a)
{'x': 1, 'y-1': {'a-2': 2}}
"""
config_norm = {}
for key, value in config.items():
if isinstance(value, Mapping):
value = normalize_nested_keys(value)
key_norm = normalize_key(key)
config_norm[key_norm] = value
return config_norm
def collect_yaml(paths=paths):
""" Collect configuration from yaml files
This searches through a list of paths, expands to find all yaml or json
files, and then parses each file.
"""
# Find all paths
file_paths = []
for path in paths:
if os.path.exists(path):
if os.path.isdir(path):
try:
file_paths.extend(sorted([
os.path.join(path, p)
for p in os.listdir(path)
if os.path.splitext(p)[1].lower() in ('.json', '.yaml', '.yml')
]))
except OSError:
# Ignore permission errors
pass
else:
file_paths.append(path)
configs = []
# Parse yaml files
for path in file_paths:
try:
with open(path) as f:
data = yaml.safe_load(f.read()) or {}
data = normalize_nested_keys(data)
configs.append(data)
except (OSError, IOError):
# Ignore permission errors
pass
return configs
def collect_env(env=None):
""" Collect config from environment variables
This grabs environment variables of the form "DASK_FOO__BAR_BAZ=123" and
turns these into config variables of the form ``{"foo": {"bar-baz": 123}}``
It transforms the key and value in the following way:
- Lower-cases the key text
- Treats ``__`` (double-underscore) as nested access
- Replaces ``_`` (underscore) with a hyphen.
- Calls ``ast.literal_eval`` on the value
"""
if env is None:
env = os.environ
d = {}
for name, value in env.items():
if name.startswith('DASK_'):
varname = name[5:].lower().replace('__', '.')
varname = normalize_key(varname)
try:
d[varname] = ast.literal_eval(value)
except (SyntaxError, ValueError):
d[varname] = value
result = {}
set(d, config=result)
return result
def ensure_file(
source,
destination=None,
comment=True):
"""
Copy file to default location if it does not already exist
This tries to move a default configuration file to a default location if
if does not already exist. It also comments out that file by default.
This is to be used by downstream modules (like dask.distributed) that may
have default configuration files that they wish to include in the default
configuration path.
Parameters
----------
source : string, filename
Source configuration file, typically within a source directory.
destination : string, directory
Destination directory. Configurable by ``DASK_CONFIG`` environment
variable, falling back to ~/.config/dask.
comment : bool, True by default
Whether or not to comment out the config file when copying.
"""
if destination is None:
destination = PATH
# destination is a file and already exists, never overwrite
if os.path.isfile(destination):
return
# If destination is not an existing file, interpret as a directory,
# use the source basename as the filename
directory = destination
destination = os.path.join(directory, os.path.basename(source))
try:
if not os.path.exists(destination):
makedirs(directory, exist_ok=True)
# Atomically create destination. Parallel testing discovered
# a race condition where a process can be busy creating the
# destination while another process reads an empty config file.
tmp = '%s.tmp.%d' % (destination, os.getpid())
with open(source) as f:
lines = list(f)
if comment:
lines = ['# ' + line
if line.strip() and not line.startswith('#')
else line
for line in lines]
with open(tmp, 'w') as f:
f.write(''.join(lines))
try:
os.rename(tmp, destination)
except OSError:
os.remove(tmp)
except OSError:
pass
class set(object):
""" Temporarily set configuration values within a context manager
Examples
--------
>>> import dask
>>> with dask.config.set({'foo': 123}):
... pass
See Also
--------
dask.config.get
"""
def __init__(self, arg=None, config=config, lock=config_lock, **kwargs):
if arg and not kwargs:
kwargs = arg
with lock:
self.config = config
self.old = {}
for key, value in kwargs.items():
self._assign(key.split('.'), value, config, old=self.old)
def __enter__(self):
return self.config
def __exit__(self, type, value, traceback):
for keys, value in self.old.items():
if value == '--delete--':
d = self.config
try:
while len(keys) > 1:
d = d[keys[0]]
keys = keys[1:]
del d[keys[0]]
except KeyError:
pass
else:
self._assign(keys, value, self.config)
@classmethod
def _assign(cls, keys, value, d, old=None, path=[]):
""" Assign value into a nested configuration dictionary
Optionally record the old values in old
Parameters
----------
keys: Sequence[str]
The nested path of keys to assign the value, similar to toolz.put_in
value: object
d: dict
The part of the nested dictionary into which we want to assign the
value
old: dict, optional
If provided this will hold the old values
path: List[str]
Used internally to hold the path of old values
"""
key = normalize_key(keys[0])
if len(keys) == 1:
if old is not None:
path_key = tuple(path + [key])
if key in d:
old[path_key] = d[key]
else:
old[path_key] = '--delete--'
d[key] = value
else:
if key not in d:
d[key] = {}
if old is not None:
old[tuple(path + [key])] = '--delete--'
old = None
cls._assign(keys[1:], value, d[key], path=path + [key], old=old)
def collect(paths=paths, env=None):
"""
Collect configuration from paths and environment variables
Parameters
----------
paths : List[str]
A list of paths to search for yaml config files
env : dict
The system environment variables
Returns
-------
config: dict
See Also
--------
dask.config.refresh: collect configuration and update into primary config
"""
if env is None:
env = os.environ
configs = []
if yaml:
configs.extend(collect_yaml(paths=paths))
configs.append(collect_env(env=env))
return merge(*configs)
def refresh(config=config, defaults=defaults, **kwargs):
"""
Update configuration by re-reading yaml files and env variables
This mutates the global dask.config.config, or the config parameter if
passed in.
This goes through the following stages:
1. Clearing out all old configuration
2. Updating from the stored defaults from downstream libraries
(see update_defaults)
3. Updating from yaml files and environment variables
Note that some functionality only checks configuration once at startup and
may not change behavior, even if configuration changes. It is recommended
to restart your python process if convenient to ensure that new
configuration changes take place.
See Also
--------
dask.config.collect: for parameters
dask.config.update_defaults
"""
config.clear()
for d in defaults:
update(config, d, priority='old')
update(config, collect(**kwargs))
def get(key, default=no_default, config=config):
"""
Get elements from global config
Use '.' for nested access
Examples
--------
>>> from dask import config
>>> config.get('foo') # doctest: +SKIP
{'x': 1, 'y': 2}
>>> config.get('foo.x') # doctest: +SKIP
1
>>> config.get('foo.x.y', default=123) # doctest: +SKIP
123
See Also
--------
dask.config.set
"""
keys = key.split('.')
result = config
for k in keys:
k = normalize_key(k)
try:
result = result[k]
except (TypeError, IndexError, KeyError):
if default is not no_default:
return default
else:
raise
return result
def rename(aliases, config=config):
""" Rename old keys to new keys
This helps migrate older configuration versions over time
"""
old = list()
new = dict()
for o, n in aliases.items():
value = get(o, None, config=config)
if value is not None:
old.append(o)
new[n] = value
for k in old:
del config[k] # TODO: support nested keys
set(new, config=config)
def update_defaults(new, config=config, defaults=defaults):
""" Add a new set of defaults to the configuration
It does two things:
1. Add the defaults to a global collection to be used by refresh later
2. Updates the global config with the new configuration
prioritizing older values over newer ones
"""
defaults.append(new)
update(config, new, priority='old')
def expand_environment_variables(config):
''' Expand environment variables in a nested config dictionary
This function will recursively search through any nested dictionaries
and/or lists.
Parameters
----------
config : dict, iterable, or str
Input object to search for environment variables
Returns
-------
config : same type as input
Examples
--------
>>> expand_environment_variables({'x': [1, 2, '$USER']}) # doctest: +SKIP
{'x': [1, 2, 'my-username']}
'''
if isinstance(config, Mapping):
return {k: expand_environment_variables(v) for k, v in config.items()}
elif isinstance(config, str):
return os.path.expandvars(config)
elif isinstance(config, (list, tuple, builtins.set)):
return type(config)([expand_environment_variables(v) for v in config])
else:
return config
refresh()