diff --git a/.github/workflows/CI.yaml b/.github/workflows/CI.yaml
index 393939c..77ac759 100644
--- a/.github/workflows/CI.yaml
+++ b/.github/workflows/CI.yaml
@@ -23,6 +23,12 @@ jobs:
           cache-dependency-glob: "uv.lock"
       - name: Sync dependencies
         run: uv sync --locked --all-extras --all-groups
+      - name: Build Docs
+        run: uv run sphinx-build -b html docs/source docs/build
+      - name: Check README rendering
+        run: |
+          uv build
+          uv run twine check dist/*
       - name: Run pre-commit
         run: uv run pre-commit run --all-files
       - name: Run tests
diff --git a/README.md b/README.md
deleted file mode 100644
index f4a33df..0000000
--- a/README.md
+++ /dev/null
@@ -1,226 +0,0 @@
-<div align="center">
-  <img src="https://ramppdev.github.io/ablate/_images/logo_banner.png" alt="ablate turns deep learning experiments into structured, human-readable reports.">
-</div>
-
-# ablate
-
-[![ablate PyPI Version](https://img.shields.io/pypi/v/ablate?logo=pypi&logoColor=b4befe&color=b4befe)](https://pypi.org/project/ablate/)
-[![ablate Python Versions](https://img.shields.io/pypi/pyversions/ablate?logo=python&logoColor=b4befe&color=b4befe)](https://pypi.org/project/ablate/)
-[![ablate GitHub License](https://img.shields.io/badge/license-MIT-b4befe?logo=c)](https://github.com/ramppdev/ablate/blob/main/LICENSE)
-
-_ablate_ turns deep learning experiments into structured, human-readable reports. It is built around five principles:
-
-- **composability**: sources, queries, blocks, and exporters can be freely combined
-- **immutability**: query operations never mutate runs in-place, enabling safe reuse and functional-style chaining
-- **extensibility**: sources, blocks, and exporters are designed to be easily extended with custom implementations
-- **readability**: reports are generated with humans in mind: shareable, inspectable, and format-agnostic
-- **minimal friction**: no servers, no databases, no heavy integrations: just Python and your existing logs
-
-Currently, _ablate_ supports the following [sources](https://ramppdev.github.io/ablate/modules/sources.html)
-and [exporters](https://ramppdev.github.io/ablate/modules/exporters.html):
-
-- sources:
-  [autrainer](https://github.com/autrainer/autrainer),
-  [ClearML](https://clear.ml/),
-  [MLflow](https://mlflow.org/),
-  [TensorBoard](https://www.tensorflow.org/tensorboard),
-  and [WandB](https://www.wandb.ai/)
-- exporters: [Markdown](https://www.markdownguide.org) and [Jupyter](https://jupyter.org/)
-
-## Installation
-
-Install _ablate_ using _pip_:
-
-```bash
-pip install ablate
-```
-
-The following optional dependencies can be installed to enable additional features:
-
-- `ablate[clearml]` to use [ClearML](https://clear.ml/) as an experiment source
-- `ablate[mlflow]` to use [MLflow](https://mlflow.org/) as an experiment source
-- `ablate[tensorboard]` to use [TensorBoard](https://www.tensorflow.org/tensorboard) as an experiment source
-- `ablate[wandb]` to use [WandB](https://www.wandb.ai/) as an experiment source
-- `ablate[jupyter]` to use _ablate_ in a [Jupyter](https://jupyter.org/) notebook
-
-## Quickstart
-
-_ablate_ is built around five composable modules:
-
-- [ablate.sources](https://ramppdev.github.io/ablate/modules/sources.html): load experiment runs from various sources
-- [ablate.queries](https://ramppdev.github.io/ablate/modules/queries.html): apply queries and transformations to the runs
-- [ablate.blocks](https://ramppdev.github.io/ablate/modules/blocks.html): structure content as tables, text, figures, and other blocks
-- [ablate.Report](https://ramppdev.github.io/ablate/modules/report.html): create a report from the runs and blocks
-- [ablate.exporters](https://ramppdev.github.io/ablate/modules/exporters.html): export a report to various formats
-
-### Creating a Report
-
-To create your first [Report](https://ramppdev.github.io/ablate/modules/report.html), define one or more experiment sources.
-For example, the built in [Mock](https://ramppdev.github.io/ablate/modules/sources.html#mock-source) can be used to simulate runs:
-
-```python
-from ablate.sources import Mock
-
-source = Mock(
-  grid={"model": ["vgg", "resnet"], "lr": [0.01, 0.001]},
-  num_seeds=2,
-)
-```
-
-Each run in the mock source has _accuracy_, _f1_, and _loss_ metrics, along with a _seed_ parameter
-as well as the manually defined parameters _model_ and _lr_.
-Next, the runs can be loaded and processed using functional-style queries to e.g., sort by accuracy,
-group by seed, aggregate the results by mean, and finally collect all results into a single list:
-
-```python
-from ablate.queries import Query, Metric, Param
-
-runs = (
-    Query(source.load())
-    .sort(Metric("accuracy", direction="max"))
-    .groupdiff(Param("seed"))
-    .aggregate("mean")
-    .all()
-)
-
-```
-
-Now that the runs are loaded and processed, a [Report](https://ramppdev.github.io/ablate/modules/report.html)
-comprising multiple blocks can be created to structure the content:
-
-```python
-from ablate import Report
-from ablate.blocks import H1, Table
-
-report = Report(runs)
-report.add(H1("Model Performance"))
-report.add(
-    Table(
-        columns=[
-            Param("model", label="Model"),
-            Param("lr", label="Learning Rate"),
-            Metric("accuracy", direction="max", label="Accuracy"),
-            Metric("f1", direction="max", label="F1 Score"),
-            Metric("loss", direction="min", label="Loss"),
-        ]
-    )
-)
-```
-
-Finally, the report can be exported to a desired format such as [Markdown](https://ramppdev.github.io/ablate/modules/exporters.html#ablate.exporters.Markdown):
-
-```python
-from ablate.exporters import Markdown
-
-Markdown().export(report)
-```
-
-This will produce a `report.md` file with the following content:
-
-```markdown
-# Model Performance
-
-| Model  | Learning Rate | Accuracy | F1 Score |    Loss |
-| :----- | ------------: | -------: | -------: | ------: |
-| resnet |          0.01 |  0.94285 |  0.90655 |  0.0847 |
-| vgg    |          0.01 |  0.92435 |   0.8813 |  0.0895 |
-| resnet |         0.001 |   0.9262 |   0.8849 |  0.0743 |
-| vgg    |         0.001 |  0.92745 |  0.90875 | 0.08115 |
-```
-
-### Combining Sources
-
-To compose multiple sources, they can be added together using the `+` operator
-as they represent lists of [Run](https://ramppdev.github.io/ablate/modules/core.html#ablate.core.types.Run) objects:
-
-```python
-runs1 = Mock(...).load()
-runs2 = Mock(...).load()
-
-all_runs = runs1 + runs2 # combines both sources into a single list of runs
-```
-
-### Selector Expressions
-
-_ablate_ selectors are lightweight expressions that access attributes of experiment runs, such as parameters, metrics, or IDs.
-They support standard Python comparison operators and can be composed using logical operators to define complex query logic:
-
-```python
-accuracy = Metric("accuracy", direction="max")
-loss = Metric("loss", direction="min")
-
-runs = (
-    Query(source.load())
-    .filter((accuracy > 0.9) & (loss < 0.1))
-    .all()
-)
-```
-
-Selectors return callable predicates, so they can be used in any query operation that requires a condition.
-All standard comparisons are supported: `==`, `!=`, `<`, `<=`, `>`, `>=`.
-Logical operators `&` (and), `|` (or), and `~` (not) can be used to combine expressions:
-
-```python
-from ablate.queries import Id
-
-select = (Param("model") == "resnet") | (Param("lr") < 0.001) # select resnet or LR below 0.001
-
-exclude = ~(Id() == "run-42") # exclude a specific run by ID
-
-runs = Query(source.load()).filter(select & exclude).all()
-
-```
-
-### Functional Queries
-
-_ablate_ queries are functionally pure such that intermediate results are not modified and can be reused:
-
-```python
-runs = Mock(...).load()
-
-sorted_runs = Query(runs).sort(Metric("accuracy", direction="max"))
-
-filtered_runs = sorted_runs.filter(Metric("accuracy", direction="max") > 0.9)
-
-sorted_runs.all() # still contains all runs sorted by accuracy
-filtered_runs.all() # only contains runs with accuracy > 0.9
-```
-
-### Composing Reports
-
-By default, _ablate_ reports populate blocks based on the global list of runs passed to the report during initialization.
-To create more complex reports, blocks can be populated with a custom list of runs using the _runs_ parameter:
-
-```python
-report = Report(sorted_runs.all())
-report.add(H1("Report with Sorted Runs and Filtered Runs"))
-report.add(H2("Sorted Runs"))
-report.add(
-    Table(
-        columns=[
-            Param("model", label="Model"),
-            Param("lr", label="Learning Rate"),
-            Metric("accuracy", direction="max", label="Accuracy"),
-        ]
-    )
-)
-report.add(H2("Filtered Runs"))
-report.add(
-    Table(
-        runs = filtered_runs.all(), # use filtered runs only for this block
-        columns=[
-            Param("model", label="Model"),
-            Param("lr", label="Learning Rate"),
-            Metric("accuracy", direction="max", label="Accuracy"),
-        ]
-    )
-)
-```
-
-## Extending _ablate_
-
-_ablate_ is designed to be extensible, allowing you to create custom [sources](https://ramppdev.github.io/ablate/modules/sources.html),
-[blocks](https://ramppdev.github.io/ablate/modules/blocks.html),
-and [exporters](https://ramppdev.github.io/ablate/modules/exporters.html) by implementing their respective abstract classes.
-
-To contribute to _ablate_, please refer to the [contribution guide](https://ramppdev.github.io/ablate/development/contributing.html).
diff --git a/README.rst b/README.rst
index 486e9f6..6ed7055 100644
--- a/README.rst
+++ b/README.rst
@@ -1,4 +1,4 @@
-.. image:: _static/logo_banner.png
+.. image:: https://ramppdev.github.io/ablate/_images/logo_banner.png
    :alt: ablate turns deep learning experiments into structured, human-readable reports.
    :align: center
 
@@ -15,7 +15,8 @@ ablate
 * **readability**: reports are generated with humans in mind: shareable, inspectable, and format-agnostic
 * **minimal friction**: no servers, no databases, no heavy integrations: just Python and your existing logs
 
-Currently, `ablate` supports the following :ref:`sources <sources>` and :ref:`exporters <exporters>`:
+Currently, `ablate` supports the following `sources <https://ramppdev.github.io/ablate/modules/sources.html>`_
+and `exporters <https://ramppdev.github.io/ablate/modules/exporters.html>`_:
 
 * sources:
   `autrainer <https://github.com/autrainer/autrainer>`_,
@@ -23,7 +24,7 @@ Currently, `ablate` supports the following :ref:`sources <sources>` and :ref:`ex
   `MLflow <https://mlflow.org/>`_,
   `TensorBoard <https://www.tensorflow.org/tensorboard>`_,
   and `WandB <https://wandb.ai/>`_
-* exporters: `Markdown <https://www.markdownguide.org/>`_ and `Jupyter <https://jupyter.org/>`_
+* exporters: `Markdown <https://www.markdownguide.org/>`__ and `Jupyter <https://jupyter.org/>`_
 
 
 .. |pypi| image:: https://img.shields.io/pypi/v/ablate?logo=pypi&logoColor=b4befe&color=b4befe
@@ -46,17 +47,17 @@ Installation
 
 Install `ablate` using `pip`:
 
-.. code-block:: bash
+.. code:: bash
 
    pip install ablate
 
 The following optional dependencies can be installed to enable additional features:
 
-* :attr:`ablate[clearml]` to use `ClearML <https://clear.ml/>`_ as an experiment source
-* :attr:`ablate[mlflow]` to use `MLflow <https://mlflow.org/>`_ as an experiment source
-* :attr:`ablate[tensorboard]` to use `TensorBoard <https://www.tensorflow.org/tensorboard>`_ as an experiment source
-* :attr:`ablate[wandb]` to use `WandB <https://wandb.ai/>`_ as an experiment source
-* :attr:`ablate[jupyter]` to use `ablate` in a `Jupyter <https://jupyter.org/>`_ notebook
+* ``ablate[clearml]`` to use `ClearML <https://clear.ml/>`_ as an experiment source
+* ``ablate[mlflow]`` to use `MLflow <https://mlflow.org/>`_ as an experiment source
+* ``ablate[tensorboard]`` to use `TensorBoard <https://www.tensorflow.org/tensorboard>`_ as an experiment source
+* ``ablate[wandb]`` to use `WandB <https://wandb.ai/>`_ as an experiment source
+* ``ablate[jupyter]`` to use `ablate` in a `Jupyter <https://jupyter.org/>`_ notebook
 
 
 Quickstart
@@ -64,21 +65,20 @@ Quickstart
 
 `ablate` is built around five composable modules:
 
-* :ref:`ablate.sources <sources>`: load experiment runs from various sources
-* :ref:`ablate.queries <queries>`: apply queries and transformations to the runs
-* :ref:`ablate.blocks <blocks>`: structure content as tables, text, figures, and other blocks
-* :ref:`ablate.Report <reports>`: create a report from the runs and blocks
-* :ref:`ablate.exporters <exporters>`: export a report to various formats
+* `ablate.sources <https://ramppdev.github.io/ablate/modules/sources.html>`_: load experiment runs from various sources
+* `ablate.queries <https://ramppdev.github.io/ablate/modules/queries.html>`_: apply queries and transformations to the runs
+* `ablate.blocks <https://ramppdev.github.io/ablate/modules/blocks.html>`_: structure content as tables, text, figures, and other blocks
+* `ablate.Report <https://ramppdev.github.io/ablate/modules/report.html>`_: create a report from the runs and blocks
+* `ablate.exporters <https://ramppdev.github.io/ablate/modules/exporters.html>`_: export a report to various formats
 
 
 Creating a Report
 ~~~~~~~~~~~~~~~~~
 
-To create your first :class:`~ablate.Report`, define one or more experiment sources.
-For example, the built in :class:`~ablate.sources.Mock` can be used to simulate runs:
+To create your first `Report <https://ramppdev.github.io/ablate/modules/reports.html#ablate.Report>`_, define one or more experiment sources.
+For example, the built in `Mock <https://ramppdev.github.io/ablate/modules/sources.html#ablate.sources.Mock>`_ can be used to simulate runs:
 
-.. code-block:: python
-   :linenos:
+.. code:: python
 
    from ablate.sources import Mock
 
@@ -92,8 +92,7 @@ as well as the manually defined parameters `model` and `lr`.
 Next, the runs can be loaded and processed using functional-style queries to e.g., sort by accuracy,
 group by seed, aggregate the results by mean, and finally collect all results into a single list:
 
-.. code-block:: python
-   :linenos:
+.. code:: python
 
    from ablate.queries import Metric, Param, Query
 
@@ -105,11 +104,10 @@ group by seed, aggregate the results by mean, and finally collect all results in
        .all()
    )
 
-Now that the runs are loaded and processed, a :class:`~ablate.Report` comprising multiple blocks 
-can be created to structure the content:
+Now that the runs are loaded and processed, a `Report <https://ramppdev.github.io/ablate/modules/reports.html#ablate.Report>`_
+comprising multiple blocks can be created to structure the content:
 
-.. code-block:: python
-   :linenos:
+.. code:: python
 
    from ablate import Report
    from ablate.blocks import H1, Table
@@ -128,18 +126,18 @@ can be created to structure the content:
        )
    )
 
-Finally, the report can be exported to a desired format such as :class:`~ablate.exporters.Markdown`:
+Finally, the report can be exported to a desired format such as
+`Markdown <https://ramppdev.github.io/ablate/modules/exporters.html#ablate.exporters.Markdown>`_:
 
-.. code-block:: python
-   :linenos:
+.. code:: python
 
    from ablate.exporters import Markdown
 
    Markdown().export(report)
 
-This will produce a :file:`report.md` file with the following content:
+This will produce a ``report.md`` file with the following content:
 
-.. code-block:: markdown
+.. code:: markdown
 
    # Model Performance
 
@@ -154,11 +152,10 @@ This will produce a :file:`report.md` file with the following content:
 Combining Sources
 ~~~~~~~~~~~~~~~~~
 
-To compose multiple sources, they can be added together using the :attr:`+` operator
-as they represent lists of :class:`~ablate.core.types.Run` objects:
+To compose multiple sources, they can be added together using the ``+`` operator as they represent lists of
+`Run <https://ramppdev.github.io/ablate/modules/core.html#ablate.core.types.Run>`_ objects:
 
-.. code-block:: python
-   :linenos:
+.. code:: python
 
    runs1 = Mock(...).load()
    runs2 = Mock(...).load()
@@ -172,8 +169,7 @@ Selector Expressions
 `ablate` selectors are lightweight expressions that access attributes of experiment runs, such as parameters, metrics, or IDs.
 They support standard Python comparison operators and can be composed using logical operators to define complex query logic:
 
-.. code-block:: python
-   :linenos:
+.. code:: python
 
    accuracy = Metric("accuracy", direction="max")
    loss = Metric("loss", direction="min")
@@ -186,11 +182,10 @@ They support standard Python comparison operators and can be composed using logi
 
 
 Selectors return callable predicates, so they can be used in any query operation that requires a condition.
-All standard comparisons are supported: :attr:`==`, :attr:`!=`, :attr:`<`, :attr:`<=`, :attr:`>`, :attr:`>=`.
-Logical operators :attr:`&` (and), :attr:`|` (or), and :attr:`~~` (not) can be used to combine expressions:
+All standard comparisons are supported: ``==``, ``!=``, ``<``, ``<=``, ``>``, ``>=``.
+Logical operators ``&`` (and), ``|`` (or), and ``~`` (not) can be used to combine expressions:
 
-.. code-block:: python
-   :linenos:
+.. code:: python
 
    from ablate.queries import Id
 
@@ -206,8 +201,7 @@ Functional Queries
 
 `ablate` queries are functionally pure such that intermediate results are not modified and can be reused:
 
-.. code-block:: python
-   :linenos:
+.. code:: python
 
    runs = Mock(...).load()
 
@@ -225,8 +219,7 @@ Composing Reports
 By default, `ablate` reports populate blocks based on the global list of runs passed to the report during initialization.
 To create more complex reports, blocks can be populated with a custom list of runs using the `runs` parameter:
 
-.. code-block:: python
-   :linenos:
+.. code:: python
 
    report = Report(sorted_runs.all())
    report.add(H1("Report with Sorted Runs and Filtered Runs"))
@@ -256,7 +249,8 @@ To create more complex reports, blocks can be populated with a custom list of ru
 Extending `ablate`
 ------------------
 
-`ablate` is designed to be extensible, allowing you to create custom :ref:`sources <sources>`, :ref:`blocks <blocks>`,
-and :ref:`exporters <exporters>` by implementing their respective abstract classes.
+`ablate` is designed to be extensible, allowing you to create custom `sources <https://ramppdev.github.io/ablate/modules/sources.html>`_,
+`blocks <https://ramppdev.github.io/ablate/modules/blocks.html>`_,
+and `exporters <https://ramppdev.github.io/ablate/modules/exporters.html>`_ by implementing their respective abstract classes.
 
-To contribute to `ablate`, please refer to the :ref:`contribution guide <contributing>`.
\ No newline at end of file
+To contribute to `ablate`, please refer to the `contribution guide <https://ramppdev.github.io/ablate/development/contributing.html>`_.
\ No newline at end of file
diff --git a/docs/source/_static/external_links.js b/docs/source/_static/external_links.js
index d9dc880..5e46098 100644
--- a/docs/source/_static/external_links.js
+++ b/docs/source/_static/external_links.js
@@ -1,3 +1,10 @@
-$(document).ready(function () {
-  $("a.external").attr("target", "_blank").attr("rel", "noopener noreferrer");
+$(function () {
+  $("a.external").each(function () {
+    const u = new URL(this.href, location.origin);
+    if (
+      u.hostname !== "ramppdev.github.io" ||
+      !u.pathname.startsWith("/ablate")
+    )
+      $(this).attr({ target: "_blank", rel: "noopener noreferrer" });
+  });
 });
diff --git a/pyproject.toml b/pyproject.toml
index 32f27fb..c746439 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,7 +4,7 @@ version = "0.2.1"
 description = "ablate turns deep learning experiments into structured, human-readable reports."
 authors = [{ name = "Simon Rampp", email = "simon@rampp.dev" }]
 license = { text = "MIT" }
-readme = "README.md"
+readme = "README.rst"
 requires-python = ">=3.10"
 keywords = [
     "machine learning",
@@ -42,6 +42,7 @@ dev = [
     "pytest-cov>=6.1.1",
     "ruff==0.11.8",
     "tomli>=2.2.1",
+    "twine>=6.2.0",
     "types-pyyaml>=6.0.12.20250516",
     "types-seaborn>=0.13.2.20250516",
 ]
diff --git a/uv.lock b/uv.lock
index b4e712f..b9728d1 100644
--- a/uv.lock
+++ b/uv.lock
@@ -2,7 +2,9 @@ version = 1
 revision = 2
 requires-python = ">=3.10"
 resolution-markers = [
-    "python_full_version >= '3.13' and sys_platform == 'linux'",
+    "python_full_version >= '3.14' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
+    "python_full_version == '3.13.*' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
+    "python_full_version >= '3.13' and platform_python_implementation == 'PyPy' and sys_platform == 'linux'",
     "python_full_version == '3.12.*' and sys_platform == 'linux'",
     "python_full_version >= '3.13' and sys_platform != 'linux' and sys_platform != 'win32'",
     "python_full_version == '3.12.*' and sys_platform != 'linux' and sys_platform != 'win32'",
@@ -56,6 +58,7 @@ dev = [
     { name = "pytest-cov" },
     { name = "ruff" },
     { name = "tomli" },
+    { name = "twine" },
     { name = "types-pyyaml" },
     { name = "types-seaborn" },
 ]
@@ -100,6 +103,7 @@ dev = [
     { name = "pytest-cov", specifier = ">=6.1.1" },
     { name = "ruff", specifier = "==0.11.8" },
     { name = "tomli", specifier = ">=2.2.1" },
+    { name = "twine", specifier = ">=6.2.0" },
     { name = "types-pyyaml", specifier = ">=6.0.12.20250516" },
     { name = "types-seaborn", specifier = ">=0.13.2.20250516" },
 ]
@@ -278,6 +282,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/b7/b8/3fe70c75fe32afc4bb507f75563d39bc5642255d1d94f1f23604725780bf/babel-2.17.0-py3-none-any.whl", hash = "sha256:4d0b53093fdfb4b21c92b5213dba5a1b23885afa8383709427046b21c366e5f2", size = 10182537, upload-time = "2025-02-01T15:17:37.39Z" },
 ]
 
+[[package]]
+name = "backports-tarfile"
+version = "1.2.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/86/72/cd9b395f25e290e633655a100af28cb253e4393396264a98bd5f5951d50f/backports_tarfile-1.2.0.tar.gz", hash = "sha256:d75e02c268746e1b8144c278978b6e98e85de6ad16f8e4b0844a154557eca991", size = 86406, upload-time = "2024-05-28T17:01:54.731Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/b9/fa/123043af240e49752f1c4bd24da5053b6bd00cad78c2be53c0d1e8b975bc/backports.tarfile-1.2.0-py3-none-any.whl", hash = "sha256:77e284d754527b01fb1e6fa8a1afe577858ebe4e9dad8919e34c862cb399bc34", size = 30181, upload-time = "2024-05-28T17:01:53.112Z" },
+]
+
 [[package]]
 name = "beautifulsoup4"
 version = "4.13.4"
@@ -684,6 +697,102 @@ toml = [
     { name = "tomli", marker = "python_full_version <= '3.11'" },
 ]
 
+[[package]]
+name = "cryptography"
+version = "45.0.7"
+source = { registry = "https://pypi.org/simple" }
+resolution-markers = [
+    "python_full_version >= '3.14' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
+]
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+]
+
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 name = "roman-numerals-py"
 version = "3.1.0"
@@ -3233,6 +3539,20 @@ wheels = [
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 ]
 
+[[package]]
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+version = "3.4.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
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+    { name = "cryptography", version = "46.0.0", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version < '3.14' and sys_platform == 'linux') or (platform_python_implementation == 'PyPy' and sys_platform == 'linux')" },
+    { name = "jeepney", marker = "sys_platform == 'linux'" },
+]
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+wheels = [
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+]
+
 [[package]]
 name = "send2trash"
 version = "1.8.3"
@@ -3419,7 +3739,9 @@ name = "sphinx"
 version = "8.2.3"
 source = { registry = "https://pypi.org/simple" }
 resolution-markers = [
-    "python_full_version >= '3.13' and sys_platform == 'linux'",
+    "python_full_version >= '3.14' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
+    "python_full_version == '3.13.*' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
+    "python_full_version >= '3.13' and platform_python_implementation == 'PyPy' and sys_platform == 'linux'",
     "python_full_version == '3.12.*' and sys_platform == 'linux'",
     "python_full_version >= '3.13' and sys_platform != 'linux' and sys_platform != 'win32'",
     "python_full_version == '3.12.*' and sys_platform != 'linux' and sys_platform != 'win32'",
@@ -3489,7 +3811,9 @@ name = "sphinx-autodoc-typehints"
 version = "3.2.0"
 source = { registry = "https://pypi.org/simple" }
 resolution-markers = [
-    "python_full_version >= '3.13' and sys_platform == 'linux'",
+    "python_full_version >= '3.14' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
+    "python_full_version == '3.13.*' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
+    "python_full_version >= '3.13' and platform_python_implementation == 'PyPy' and sys_platform == 'linux'",
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     "python_full_version >= '3.13' and sys_platform != 'linux' and sys_platform != 'win32'",
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 ]
 
+[[package]]
+name = "twine"
+version = "6.2.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "id" },
+    { name = "keyring", marker = "platform_machine != 'ppc64le' and platform_machine != 's390x'" },
+    { name = "packaging" },
+    { name = "readme-renderer" },
+    { name = "requests" },
+    { name = "requests-toolbelt" },
+    { name = "rfc3986" },
+    { name = "rich" },
+    { name = "urllib3" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/e0/a8/949edebe3a82774c1ec34f637f5dd82d1cf22c25e963b7d63771083bbee5/twine-6.2.0.tar.gz", hash = "sha256:e5ed0d2fd70c9959770dce51c8f39c8945c574e18173a7b81802dab51b4b75cf", size = 172262, upload-time = "2025-09-04T15:43:17.255Z" }
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+]
+
 [[package]]
 name = "types-python-dateutil"
 version = "2.9.0.20241206"