| Name | dataclass-settings JSON |
| Version |
0.6.1
JSON |
| download |
| home_page | None |
| Summary | Declarative dataclass settings. |
| upload_time | 2025-09-08 16:44:43 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | <4,>=3.8 |
| license | Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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| keywords |
attrs
dataclass
env
msgspec
pydantic
settings
|
| VCS |
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|
# dataclass-settings
[](https://github.com/dancardin/dataclass-settings/actions)
[](https://coveralls.io/github/DanCardin/dataclass-settings?branch=main)
[](https://dataclass-settings.readthedocs.io/en/latest/?badge=latest)
- [Full documentation here](https://dataclass-settings.readthedocs.io/en/latest/).
- [Bundled Loaders](https://dataclass-settings.readthedocs.io/en/latest/loaders.html).
`dataclass-settings` intends to work with any
[PEP-681](https://peps.python.org/pep-0681/)-compliant dataclass-like object,
including but not limited to:
- [Pydantic models](https://pydantic-docs.helpmanual.io/) (v1/v2),
- [dataclasses](https://docs.python.org/3/library/dataclasses.html)
- [attrs classes](https://www.attrs.org/en/stable/).
- [msgspec models](https://jcristharif.com/msgspec/).
`dataclass-settings` owes its existence
[pydantic-settings](https://github.com/pydantic/pydantic-settings), in that
pydantic-settings will be a benchmark for `dataclass-settings`'s featureset.
However it was bourne out of frustration with pydantic-setting's approach to
implementing that featureset.
## Example
```python
from __future__ import annotations
from dataclass_settings import load_settings, Env, Secret
from pydantic import BaseModel
class Example(BaseModel):
env: Annotated[str, Env("ENVIRONMENT")] = "local"
dsn: Annotated[str, Env("DSN"), Secret('dsn')] = "dsn://"
sub_config: SubConfig
class SubConfig(BaseModel):
nested: Annotated[int, Env("NESTED")] = "4"
example: Example = load_settings(Example)
# or, if you want `nested` to be `SUB_CONFIG_NESTED`
example: Example = load_settings(Example, nested_delimiter='_')
```
## vs Pydantic Settings
### Simplicity
- `pydantic-settings` alters how you go about defining your normal pydantic
models. You need to switch (some of the) base classes, you need to configure
the magical `model_config = SettingsConfigDict(...)` object, etc.
The model becomes inherently entangled with the settings-loading library.
- `dataclass-settings` attaches targeted Annotations metadata to a vanilla
pydantic model. You can **choose** to not use `load_settings` (for example, in
tests), and construct the model instance however you'd like.
### Clarity
- `pydantic-settings` makes it really, really difficult to intuit what the
concrete environment variable that's going to be loaded for a given field is
**actually** going to be. Based on my own experience, and from perusing their
issue tracker, it seems like this is not an uncommon experience.
The combination of field name, `SettingsConfigDict` settings, casing,
`alias`/`validation_alias`/`serialization_alias`, and relative position of the
env var in the greater config all contribute to it being a **task** to deduce
which concrete name will be used when loading.
- `dataclass-settings` by **default** requires an explicit, concrete name, which
maps directly to the value being loaded (`Env('FOO')` loads `FOO`, for sure!)
If you want to opt into a less explcict, more inferred setup (like
pydantic-settings), you can do so by utilizing the `nested_delimiter='_'` and
`infer_name=True` arguments.
### Typing
- `pydantic-settings` does not play **super** well with type checkers,
necessitating the use of a mypy plugin for it to not emit type errors into
user code.
The code recommended in their documentation for namespacing settings, looks
like:
```python
class Settings(BaseSettings):
more_settings: SubModel = SubModel()
```
This only type-checks with mypy (after using the plugin), but not
pyright/pylance. Additionally, this **actually** evaluates the `SubModel`
constructor during module parsing!
These issues seem(?) to be inherent to the strategy of subclassing
`BaseModel`, and building in its logic into the object construction process
- `dataclass-settings` sidesteps this problem by decoupling the definition of
the settings from the loading of settings.
As such, you're more able to define the model, exactly as you would have with
vanilla pydantic:
```python
class Settings(BaseModel):
more_settings: SubModel
```
Internally, the `load_settings` function handles the work of constructing the
requisite input structure pydantic expects to construct the whole object tree.
### Compatibility
- `pydantic-settings`'s `BaseSettings` inherits from pydantic's `BaseModel`. And
thus can only function against pydantic models, as the name would imply.
- `dataclass-settings`'s primary entrypoint is a function that accepts a
supportable type. As such, it can theoretically support any type that has a
well defined object structure, like all of `pydantic`, `dataclasses`, and
`attrs`.
Practically, `pydantic` has the most robust system for parsing/validating a
json-like structure into the models, so it's probably to be the most flexible
anyways. But for many simple cases, particularly those without nesting, or that
only deal in simple types (like int, float, str, etc); then dataclasses/attrs
can certainly provide a similar experience.
### Flexibility
- At time of writing, `pydantic-settings`'s strategy around "loaders", i.e.
supportable settings sources is relatively inflexible. Their issue tracker
contains a decent number of requests for a more flexible way of defining
settings priorities among different loaders, or even using different settings
from within a loader.
This, at least, doesn't seem to be an inherent issue to the library
necessarily. Just that at present, their API appears to try to reuse
pydantic's `Field` and `alias` mechanisms to infer the settings for all
loaders.
- `dataclass-settings` instead annotates each field individually, with the
loaders that field should use. That means you can have different priorities
(or entirely different loaders!) per field.
Raw data
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"home_page": null,
"name": "dataclass-settings",
"maintainer": null,
"docs_url": null,
"requires_python": "<4,>=3.8",
"maintainer_email": null,
"keywords": "attrs, dataclass, env, msgspec, pydantic, settings",
"author": null,
"author_email": "Dan Cardin <ddcardin@gmail.com>",
"download_url": "https://files.pythonhosted.org/packages/b8/af/d7c0cbd0bfcfb0466c3edf5770876e5a572f45ee6e1ca01d00fb3bd761e6/dataclass_settings-0.6.1.tar.gz",
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"description": "# dataclass-settings\n\n[](https://github.com/dancardin/dataclass-settings/actions)\n[](https://coveralls.io/github/DanCardin/dataclass-settings?branch=main)\n[](https://dataclass-settings.readthedocs.io/en/latest/?badge=latest)\n\n- [Full documentation here](https://dataclass-settings.readthedocs.io/en/latest/).\n- [Bundled Loaders](https://dataclass-settings.readthedocs.io/en/latest/loaders.html).\n\n`dataclass-settings` intends to work with any\n[PEP-681](https://peps.python.org/pep-0681/)-compliant dataclass-like object,\nincluding but not limited to:\n\n- [Pydantic models](https://pydantic-docs.helpmanual.io/) (v1/v2),\n- [dataclasses](https://docs.python.org/3/library/dataclasses.html)\n- [attrs classes](https://www.attrs.org/en/stable/).\n- [msgspec models](https://jcristharif.com/msgspec/).\n\n`dataclass-settings` owes its existence\n[pydantic-settings](https://github.com/pydantic/pydantic-settings), in that\npydantic-settings will be a benchmark for `dataclass-settings`'s featureset.\nHowever it was bourne out of frustration with pydantic-setting's approach to\nimplementing that featureset.\n\n## Example\n\n```python\nfrom __future__ import annotations\nfrom dataclass_settings import load_settings, Env, Secret\nfrom pydantic import BaseModel\n\n\nclass Example(BaseModel):\n env: Annotated[str, Env(\"ENVIRONMENT\")] = \"local\"\n dsn: Annotated[str, Env(\"DSN\"), Secret('dsn')] = \"dsn://\"\n\n sub_config: SubConfig\n\n\nclass SubConfig(BaseModel):\n nested: Annotated[int, Env(\"NESTED\")] = \"4\"\n\n\nexample: Example = load_settings(Example)\n\n# or, if you want `nested` to be `SUB_CONFIG_NESTED`\nexample: Example = load_settings(Example, nested_delimiter='_')\n```\n\n## vs Pydantic Settings\n\n### Simplicity\n\n- `pydantic-settings` alters how you go about defining your normal pydantic\n models. You need to switch (some of the) base classes, you need to configure\n the magical `model_config = SettingsConfigDict(...)` object, etc.\n\n The model becomes inherently entangled with the settings-loading library.\n\n- `dataclass-settings` attaches targeted Annotations metadata to a vanilla\n pydantic model. You can **choose** to not use `load_settings` (for example, in\n tests), and construct the model instance however you'd like.\n\n### Clarity\n\n- `pydantic-settings` makes it really, really difficult to intuit what the\n concrete environment variable that's going to be loaded for a given field is\n **actually** going to be. Based on my own experience, and from perusing their\n issue tracker, it seems like this is not an uncommon experience.\n\n The combination of field name, `SettingsConfigDict` settings, casing,\n `alias`/`validation_alias`/`serialization_alias`, and relative position of the\n env var in the greater config all contribute to it being a **task** to deduce\n which concrete name will be used when loading.\n\n- `dataclass-settings` by **default** requires an explicit, concrete name, which\n maps directly to the value being loaded (`Env('FOO')` loads `FOO`, for sure!)\n\n If you want to opt into a less explcict, more inferred setup (like\n pydantic-settings), you can do so by utilizing the `nested_delimiter='_'` and\n `infer_name=True` arguments.\n\n### Typing\n\n- `pydantic-settings` does not play **super** well with type checkers,\n necessitating the use of a mypy plugin for it to not emit type errors into\n user code.\n\n The code recommended in their documentation for namespacing settings, looks\n like:\n\n ```python\n class Settings(BaseSettings):\n more_settings: SubModel = SubModel()\n ```\n\n This only type-checks with mypy (after using the plugin), but not\n pyright/pylance. Additionally, this **actually** evaluates the `SubModel`\n constructor during module parsing!\n\n These issues seem(?) to be inherent to the strategy of subclassing\n `BaseModel`, and building in its logic into the object construction process\n\n- `dataclass-settings` sidesteps this problem by decoupling the definition of\n the settings from the loading of settings.\n\n As such, you're more able to define the model, exactly as you would have with\n vanilla pydantic:\n\n ```python\n class Settings(BaseModel):\n more_settings: SubModel\n ```\n\n Internally, the `load_settings` function handles the work of constructing the\n requisite input structure pydantic expects to construct the whole object tree.\n\n### Compatibility\n\n- `pydantic-settings`'s `BaseSettings` inherits from pydantic's `BaseModel`. And\n thus can only function against pydantic models, as the name would imply.\n\n- `dataclass-settings`'s primary entrypoint is a function that accepts a\n supportable type. As such, it can theoretically support any type that has a\n well defined object structure, like all of `pydantic`, `dataclasses`, and\n `attrs`.\n\n Practically, `pydantic` has the most robust system for parsing/validating a\n json-like structure into the models, so it's probably to be the most flexible\n anyways. But for many simple cases, particularly those without nesting, or that\n only deal in simple types (like int, float, str, etc); then dataclasses/attrs\n can certainly provide a similar experience.\n\n### Flexibility\n\n- At time of writing, `pydantic-settings`'s strategy around \"loaders\", i.e.\n supportable settings sources is relatively inflexible. Their issue tracker\n contains a decent number of requests for a more flexible way of defining\n settings priorities among different loaders, or even using different settings\n from within a loader.\n\n This, at least, doesn't seem to be an inherent issue to the library\n necessarily. Just that at present, their API appears to try to reuse\n pydantic's `Field` and `alias` mechanisms to infer the settings for all\n loaders.\n\n- `dataclass-settings` instead annotates each field individually, with the\n loaders that field should use. That means you can have different priorities\n (or entirely different loaders!) per field.\n",
"bugtrack_url": null,
"license": "Apache License\n Version 2.0, January 2004\n http://www.apache.org/licenses/\n \n TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION\n \n 1. Definitions.\n \n \"License\" shall mean the terms and conditions for use, reproduction,\n and distribution as defined by Sections 1 through 9 of this document.\n \n \"Licensor\" shall mean the copyright owner or entity authorized by\n the copyright owner that is granting the License.\n \n \"Legal Entity\" shall mean the union of the acting entity and all\n other entities that control, are controlled by, or are under common\n control with that entity. For the purposes of this definition,\n \"control\" means (i) the power, direct or indirect, to cause the\n direction or management of such entity, whether by contract or\n otherwise, or (ii) ownership of fifty percent (50%) or more of the\n outstanding shares, or (iii) beneficial ownership of such entity.\n \n \"You\" (or \"Your\") shall mean an individual or Legal Entity\n exercising permissions granted by this License.\n \n \"Source\" form shall mean the preferred form for making modifications,\n including but not limited to software source code, documentation\n source, and configuration files.\n \n \"Object\" form shall mean any form resulting from mechanical\n transformation or translation of a Source form, including but\n not limited to compiled object code, generated documentation,\n and conversions to other media types.\n \n \"Work\" shall mean the work of authorship, whether in Source or\n Object form, made available under the License, as indicated by a\n copyright notice that is included in or attached to the work\n (an example is provided in the Appendix below).\n \n \"Derivative Works\" shall mean any work, whether in Source or Object\n form, that is based on (or derived from) the Work and for which the\n editorial revisions, annotations, elaborations, or other modifications\n represent, as a whole, an original work of authorship. For the purposes\n of this License, Derivative Works shall not include works that remain\n separable from, or merely link (or bind by name) to the interfaces of,\n the Work and Derivative Works thereof.\n \n \"Contribution\" shall mean any work of authorship, including\n the original version of the Work and any modifications or additions\n to that Work or Derivative Works thereof, that is intentionally\n submitted to Licensor for inclusion in the Work by the copyright owner\n or by an individual or Legal Entity authorized to submit on behalf of\n the copyright owner. For the purposes of this definition, \"submitted\"\n means any form of electronic, verbal, or written communication sent\n to the Licensor or its representatives, including but not limited to\n communication on electronic mailing lists, source code control systems,\n and issue tracking systems that are managed by, or on behalf of, the\n Licensor for the purpose of discussing and improving the Work, but\n excluding communication that is conspicuously marked or otherwise\n designated in writing by the copyright owner as \"Not a Contribution.\"\n \n \"Contributor\" shall mean Licensor and any individual or Legal Entity\n on behalf of whom a Contribution has been received by Licensor and\n subsequently incorporated within the Work.\n \n 2. Grant of Copyright License. Subject to the terms and conditions of\n this License, each Contributor hereby grants to You a perpetual,\n worldwide, non-exclusive, no-charge, royalty-free, irrevocable\n copyright license to reproduce, prepare Derivative Works of,\n publicly display, publicly perform, sublicense, and distribute the\n Work and such Derivative Works in Source or Object form.\n \n 3. Grant of Patent License. Subject to the terms and conditions of\n this License, each Contributor hereby grants to You a perpetual,\n worldwide, non-exclusive, no-charge, royalty-free, irrevocable\n (except as stated in this section) patent license to make, have made,\n use, offer to sell, sell, import, and otherwise transfer the Work,\n where such license applies only to those patent claims licensable\n by such Contributor that are necessarily infringed by their\n Contribution(s) alone or by combination of their Contribution(s)\n with the Work to which such Contribution(s) was submitted. If You\n institute patent litigation against any entity (including a\n cross-claim or counterclaim in a lawsuit) alleging that the Work\n or a Contribution incorporated within the Work constitutes direct\n or contributory patent infringement, then any patent licenses\n granted to You under this License for that Work shall terminate\n as of the date such litigation is filed.\n \n 4. Redistribution. You may reproduce and distribute copies of the\n Work or Derivative Works thereof in any medium, with or without\n modifications, and in Source or Object form, provided that You\n meet the following conditions:\n \n (a) You must give any other recipients of the Work or\n Derivative Works a copy of this License; and\n \n (b) You must cause any modified files to carry prominent notices\n stating that You changed the files; and\n \n (c) You must retain, in the Source form of any Derivative Works\n that You distribute, all copyright, patent, trademark, and\n attribution notices from the Source form of the Work,\n excluding those notices that do not pertain to any part of\n the Derivative Works; and\n \n (d) If the Work includes a \"NOTICE\" text file as part of its\n distribution, then any Derivative Works that You distribute must\n include a readable copy of the attribution notices contained\n within such NOTICE file, excluding those notices that do not\n pertain to any part of the Derivative Works, in at least one\n of the following places: within a NOTICE text file distributed\n as part of the Derivative Works; within the Source form or\n documentation, if provided along with the Derivative Works; or,\n within a display generated by the Derivative Works, if and\n wherever such third-party notices normally appear. The contents\n of the NOTICE file are for informational purposes only and\n do not modify the License. You may add Your own attribution\n notices within Derivative Works that You distribute, alongside\n or as an addendum to the NOTICE text from the Work, provided\n that such additional attribution notices cannot be construed\n as modifying the License.\n \n You may add Your own copyright statement to Your modifications and\n may provide additional or different license terms and conditions\n for use, reproduction, or distribution of Your modifications, or\n for any such Derivative Works as a whole, provided Your use,\n reproduction, and distribution of the Work otherwise complies with\n the conditions stated in this License.\n \n 5. Submission of Contributions. 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