Input/Output transport utility objects
Project description
Input/Output Data Transport
The Input/Output Data Transport utility objects was created for full managed
engine of configuration file that include load
from any config file format types
like .yaml
, .json
, or .toml
, and manage retention and version of config files
lifecycle.
This package has 3 parts of core module; Register, Config, and File. The base module is the file module that is open file objects with specific format that want to open include open directory objects (I think the open dir object do not should to use now because I do not done with its code.)
:round_pushpin: Installation
pip install -U ddeutil-io
Python version supported:
Python Version | Installation | Support Fixed Bug |
---|---|---|
>=3.9,<3.14 |
pip install -U ddeutil-io |
:heavy_check_mark: |
[!NOTE] This package need to install
ddeutil
first to be core package namespace. You do not need to pip it because I include this package to the required list.For optional dependencies that should to additional install;
Module Additional dependencies YamlFl pip install PyYaml
TomlFl pip install toml
MsgpackFl pip install msgpack
:dart: Features
The features of this package is Input/Output data transport utility objects.
Module | Name | Description | Remark |
---|---|---|---|
files.base | PathSearch | ||
RegexConf | |||
files.file | Fl | Open File object that use to open any normal or compression file from current local file system | |
EnvFlMixin | |||
EnvFl | |||
YamlEnvFl | |||
YamlFl | |||
YamlFlResolve | |||
JsonEnvFl | |||
JsonFl | |||
CsvFl | |||
CsvPipeFl | |||
TomlEnvFl | |||
TomlFl | |||
PickleFl | no cover | ||
MarshalFl | no cover | ||
MsgpackFl | no cover | ||
config | ConfFl | ||
ConfSQLite | |||
register | Register | Register Object that contain configuration loading methods and metadata management. | |
FullRegister |
:beers: Usages
I will show some usage example of function in this package. If you want to use complex or adjust some parameter, please see doc-string or real source code (I think it do not complex and you can see how that function work).
Files
For example, I will represent YamlEnvFl
object that passing environment variable
to reading content before passing to the Yaml loader.
data:
get: HELLO ${HELLO}
import os
from ddeutil.io import YamlEnvFl
os.environ["HELLO"] = "WORLD"
content = YamlEnvFl('./.pre-commit-config.yaml').read(safe=True)
assert content['data']['get'] == "HELLO WORLD"
Config
Config Object is the dir system handler object that manage any files in that
input dir path like load
, save
, load_stage
, save_stage
, or files
.
from pathlib import Path
from ddeutil.io.config import ConfFl
config: ConfFl = ConfFl(path=Path('./conf'), compress="gzip")
data = config.load('config_file.yaml')
config.save_stage('./stage/file.json', data)
Register
The Register Object is the metadata generator object for the config data. If you passing name and configs to this object, it will find the config name in any stage storage and generate its metadata to you.
from ddeutil.io.register import Register
from ddeutil.io.param import Params
registry: Register = Register(
name='examples:conn_data_local_file',
params=Params.model_validate({
"stages": {
"raw": {"format": "{naming:%s}.{timestamp:%Y%m%d_%H%M%S}"},
},
}),
)
registry.move(stage="raw")
The raw data of this config was written in conn_file.yaml
file.
conf/
examples/
conn_file.yaml
When call move
method, it will transfer data from .yaml
file to json
file
with the data hashing algorithm.
data/
raw/
conn_file_20240101_000000.json
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