python-configuration | A Python library to load configuration parameters | Configuration Management library
kandi X-RAY | python-configuration Summary
kandi X-RAY | python-configuration Summary
python-configuration is a Python library typically used in Devops, Configuration Management applications. python-configuration has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However python-configuration build file is not available. You can install using 'pip install python-configuration' or download it from GitHub, PyPI.
A Python library to load configuration parameters
A Python library to load configuration parameters
Support
Quality
Security
License
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Support
python-configuration has a low active ecosystem.
It has 68 star(s) with 19 fork(s). There are 3 watchers for this library.
There were 2 major release(s) in the last 12 months.
There are 18 open issues and 31 have been closed. On average issues are closed in 31 days. There are 4 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of python-configuration is 0.11.0
Quality
python-configuration has 0 bugs and 0 code smells.
Security
python-configuration has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
python-configuration code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
python-configuration is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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python-configuration releases are not available. You will need to build from source code and install.
Deployable package is available in PyPI.
python-configuration has no build file. You will be need to create the build yourself to build the component from source.
Installation instructions, examples and code snippets are available.
python-configuration saves you 1735 person hours of effort in developing the same functionality from scratch.
It has 4008 lines of code, 289 functions and 30 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed python-configuration and discovered the below as its top functions. This is intended to give you an instant insight into python-configuration implemented functionality, and help decide if they suit your requirements.
- Return the configuration
- Get a key from the Secret
- Return the secret version of the key
- List of GCP secrets
- Return config dictionary
- Return a list of configuration items
- Get the value of a key
- Get a secret from the cache
- Get the subset of the given item
- Return the value of a key
- Filter a dictionary based on prefix
- Get a subset of the config
- Reload the data
- Reload data
- Reload configuration from data
- Flatten nested dictionary
- Load configuration from data
- Load configuration from file
Get all kandi verified functions for this library.
python-configuration Key Features
No Key Features are available at this moment for python-configuration.
python-configuration Examples and Code Snippets
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{
'a': {
'b': 'value'
}
}
cfg['a.b']
cfg['a']['b']
cfg['a'].b
cfg.a.b
cfg['a'].as_dict == {'b': 'value'}
{
"database.host": "something",
"database.port": 12345,
"database.driver": "name",
"app.debug": true,
"app.environme
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config_from_python('foo.bar', prefix='CONFIG', separator='__')
# foo.bar
CONFIG__AA__BB_C = 1
CONFIG__AA__BB__D = 2
CONF__AA__BB__D = 3
{
'aa.bb_c': 1,
'aa.bb.d': 2,
}
{
'a': {
'b': 'value'
}
}
{
'a.b': 'value'
}
conf
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cfg = ConfigurationSet(
config_from_env(prefix=PREFIX),
config_from_json(path, read_from_file=True),
config_from_dict(DICT),
)
cfg = config(
('env', PREFIX),
('json', path, True),
('dict', DICT),
)
cfg = config('env', path,
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c.TerminalInteractiveShell.autoformatter = None
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process.env.PATH = ['usr/local/bin/', process.env.PATH].join(':')
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numpy-1.15.4-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
$ pip install \
--target lib \
--python-version 36 \
--platform manylinux1_x86_6
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try:
from Tkinter import * # for Python2
except ImportError:
from tkinter import * # for Python3
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# This is /usr/bin/python
which python
# Activate miniconda3 optional component.
cat >>/etc/google-dataproc/dataproc.properties <
conda install -y
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{
"name": "inputBlob",
"type": "blob",
"path": "test/test.csv",
"connection": "AzureWebJobsStorage",
"direction": "in"
}
import logging
import azure.functions as func
import csv
im
Community Discussions
Trending Discussions on python-configuration
QUESTION
How to install and run pip in Google Dataproc cluster
Asked 2020-Jan-29 at 01:28
I created a cluster in Google DataProc with the following commands:
...ANSWER
Answered 2020-Jan-29 at 01:28I changed --metadata PIP_PACKAGES=numpy:scipy:pandas:scikit-learn:matplotlib:seaborn
to --metadata PIP_PACKAGES="numpy scipy pandas scikit-learn matplotlib seaborn"
in your command and was able to use the pip-install.sh
initialization script.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install python-configuration
This library converts the config types above into dictionaries with dotted-based keys. That is, given a config cfg from the structure. we are able to refer to the parameter above as any of.
Support
If you'd like to contribute, please fork the repository and use a feature branch. Pull requests are welcome.
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