diff --git a/.github/workflows/build-test-release.yml b/.github/workflows/build-test-release.yml
index eac421ac..2c3fc4c5 100644
--- a/.github/workflows/build-test-release.yml
+++ b/.github/workflows/build-test-release.yml
@@ -2,7 +2,6 @@
 #
 # SPDX-License-Identifier: MPL-2.0
 
-
 name: Build and Test
 
 on:
@@ -28,20 +27,16 @@ concurrency:
   cancel-in-progress: true
 
 jobs:
-
   build-python:
     runs-on: ubuntu-latest
     outputs:
       version: ${{ steps.version.outputs.version }}
     steps:
-
       - name: Checkout source code
         uses: actions/checkout@v6
 
-      - name: Setup Python 3.13
-        uses: actions/setup-python@v6
-        with:
-          python-version: "3.13"
+      - name: Install uv
+        uses: astral-sh/setup-uv@v7
 
       - name: Set PyPI version
         uses: PowerGridModel/pgm-version-bump@main
@@ -51,8 +46,7 @@ jobs:
       - name: Build
         run: |
           cat PYPI_VERSION
-          pip install build
-          python -m build --outdir wheelhouse .
+          uv build --sdist --no-create-gitignore --out-dir wheelhouse .
 
       - name: Save version
         id: version
@@ -74,12 +68,11 @@ jobs:
     runs-on: ${{ matrix.os }}
 
     steps:
-
       - name: Checkout source code
         uses: actions/checkout@v6
 
-      - name: Setup Python ${{ matrix.python }}
-        uses: actions/setup-python@v6
+      - name: Install uv
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ matrix.python }}
 
@@ -89,11 +82,14 @@ jobs:
           name: power-grid-model-io
           path: wheelhouse/
 
+      - name: Create environment
+        run: uv venv
+
       - name: Install built wheel file
-        run: pip install power-grid-model-io[dev]==${{ needs.build-python.outputs.version }} --find-links=wheelhouse
+        run: uv pip install power-grid-model-io==${{ needs.build-python.outputs.version }} --find-links=wheelhouse
 
       - name: Unit test and coverage
-        run: pytest --verbose
+        run: uv run --only-group test --no-editable pytest --verbose
 
   validation-tests:
     needs: build-python
@@ -105,12 +101,11 @@ jobs:
     runs-on: ${{ matrix.os }}
 
     steps:
-
       - name: Checkout source code
         uses: actions/checkout@v6
 
-      - name: Setup Python ${{ matrix.python }}
-        uses: actions/setup-python@v6
+      - name: Install uv
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ matrix.python }}
 
@@ -120,11 +115,14 @@ jobs:
           name: power-grid-model-io
           path: wheelhouse/
 
+      - name: Create environment
+        run: uv venv
+
       - name: Install built wheel file
-        run: pip install power-grid-model-io[dev]==${{ needs.build-python.outputs.version }} --find-links=wheelhouse
+        run: uv pip install power-grid-model-io==${{ needs.build-python.outputs.version }} --find-links=wheelhouse
 
       - name: Validation tests
-        run: pytest tests/validation --no-cov --verbose
+        run: uv run --only-group test --no-editable pytest tests/validation --no-cov --verbose
 
   github-release:
     needs:
@@ -135,10 +133,8 @@ jobs:
       contents: write
     runs-on: ubuntu-latest
     steps:
-      - name: Setup Python 3.13
-        uses: actions/setup-python@v6
-        with:
-          python-version: "3.13"
+      - name: Install uv
+        uses: astral-sh/setup-uv@v7
 
       - name: Load built wheel file
         uses: actions/download-artifact@v7
diff --git a/.github/workflows/check-code-quality.yml b/.github/workflows/check-code-quality.yml
index bf1eac10..eb62edc0 100644
--- a/.github/workflows/check-code-quality.yml
+++ b/.github/workflows/check-code-quality.yml
@@ -21,24 +21,27 @@ jobs:
       - name: Checkout
         uses: actions/checkout@v6
 
-      - name: Set up Python
-        uses: actions/setup-python@v6
-        with:
-          python-version: 3.11
+      - name: Install uv
+        uses: astral-sh/setup-uv@v7
 
-      - name: Upgrade pip
-        run: pip install --upgrade pip
+      - name: Install most linters from uv
+        run: |
+          uv sync --group lint
+
+      - name: Run mypy
+        run: |
+          uv run mypy .
 
-      - name: Install and run mypy
+      - name: Run ruff
         run: |
-          pip install mypy
-          mypy src
+          uv run ruff check .
+          uv run ruff format .
 
-      - name: Install and run ruff
+      - name: Install and run markdownlint
         run: |
-          pip install ruff .
-          ruff check .
-          ruff format .
+          npm install -g markdownlint-cli@0.47.0
+          echo "Running markdownlint"
+          markdownlint --fix .
 
       - name: If needed raise error
         run: |
diff --git a/.github/workflows/check-pr-labels.yml b/.github/workflows/check-pr-labels.yml
index 40c16775..3a2902ca 100644
--- a/.github/workflows/check-pr-labels.yml
+++ b/.github/workflows/check-pr-labels.yml
@@ -2,7 +2,6 @@
 #
 # SPDX-License-Identifier: MPL-2.0
 
-
 name: Check PR Labels
 
 on:
diff --git a/.github/workflows/refresh-lock-and-linter-dependencies.yml b/.github/workflows/refresh-lock-and-linter-dependencies.yml
new file mode 100644
index 00000000..f8db36cd
--- /dev/null
+++ b/.github/workflows/refresh-lock-and-linter-dependencies.yml
@@ -0,0 +1,110 @@
+# SPDX-FileCopyrightText: Contributors to the Power Grid Model project <powergridmodel@lfenergy.org>
+#
+# SPDX-License-Identifier: MPL-2.0
+
+name: Refresh lock and linter Dependencies
+
+on:
+  workflow_call:
+    inputs:
+      create-pr:
+        type: boolean
+        description: "Whether to create a pull request with the changes"
+        required: false
+        default: false
+  workflow_dispatch:
+    inputs:
+      create-pr:
+        type: boolean
+        description: "Whether to create a pull request with the changes"
+        required: false
+        default: false
+  schedule:
+    - cron: "0 2 * * 0" # Every Sunday at 2:00 UTC
+
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}-linter-dependencies
+  cancel-in-progress: true
+
+
+jobs:
+  refresh-lock-and-linter-dependencies:
+    name: Refresh lock and linter Dependencies
+    runs-on: ubuntu-latest
+    permissions:
+      contents: write
+      pull-requests: write
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v6
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v7
+
+      - name: upgrade uv lock
+        run: uv lock --upgrade  
+
+      - name: Install linters from uv
+        run: |
+          uv sync --only-group lint
+      
+      - name: retrieve versions
+        id: versions
+        run: |
+          grab_installed_version() {
+            local pkg="$1"
+            local version
+            version=$(uv pip freeze | grep -i "^$pkg==" | head -n1 | cut -d= -f3)
+            echo "${pkg}=$version" >> "$GITHUB_OUTPUT"
+          }
+          grab_installed_version "ruff"
+          grab_installed_version "clang-format"
+          grab_installed_version "mypy"
+          grab_installed_version "gersemi"
+
+      - name: Update .pre-commit-config.yaml
+        uses: cuchi/jinja2-action@v1.3.0
+        with:
+          template: .pre-commit-config.yaml.jinja
+          output_file: .pre-commit-config.yaml
+          variables: |
+            ruff=${{ steps.versions.outputs.ruff }}
+            clang_format=${{ steps.versions.outputs.clang-format }}
+            mypy=${{ steps.versions.outputs.mypy }}
+            gersemi=${{ steps.versions.outputs.gersemi }}
+
+      - name: show changed files
+        run: |
+          git status
+          git diff .pre-commit-config.yaml
+
+      - name: try to install pre-commit
+        run: |
+          source .venv/bin/activate
+          pre-commit install
+          pre-commit install-hooks
+          pre-commit uninstall
+
+      - name: generate GitHub App token
+        uses: actions/create-github-app-token@v2
+        id: generate-token
+        with:
+          app-id: ${{ secrets.CI_BOT_APP_ID }}
+          private-key: ${{ secrets.CI_BOT_PRIVATE_KEY }}
+
+      - name: create pull request
+        if: ${{ inputs.create-pr || github.event_name == 'schedule' }}
+        uses: peter-evans/create-pull-request@v8
+        with:
+          commit-message: "Refresh lock and linter dependencies"
+          branch: "dependencies/refresh-lock-and-linter"
+          title: "Refresh lock and linter dependencies"
+          body: "This PR refreshes the lock file and updates linter dependencies to their latest versions."
+          labels: "dependencies"
+          signoff: true
+          sign-commits: true
+          delete-branch: true
+          base: ${{ github.head_ref }}
+          token: ${{ steps.generate-token.outputs.token }}
diff --git a/.github/workflows/sonar.yml b/.github/workflows/sonar.yml
index de475077..0ccb0e22 100644
--- a/.github/workflows/sonar.yml
+++ b/.github/workflows/sonar.yml
@@ -30,18 +30,13 @@ jobs:
         with:
           fetch-depth: 0  # Shallow clones should be disabled for a better relevancy of analysis
 
-      - name: Set up Python
-        uses: actions/setup-python@v6
-        with:
-          python-version: "3.13"
-
-      - name: Install in develop mode
-        run: |
-          pip install -e .[dev]
+      - name: Install uv
+        uses: astral-sh/setup-uv@v7
 
       - name: Test and Coverage
         run: |
-          pytest
+          uv sync --no-default-groups --group test
+          uv run pytest
 
           # Fix relative paths in coverage file
           # Known bug: https://community.sonarsource.com/t/sonar-on-github-actions-with-python-coverage-source-issue/36057
@@ -52,4 +47,4 @@ jobs:
         uses: SonarSource/sonarqube-scan-action@v7
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-          SONAR_TOKEN: ${{ secrets.SONAR_TOKEN }}
\ No newline at end of file
+          SONAR_TOKEN: ${{ secrets.SONAR_TOKEN }}
diff --git a/.markdownlint.yaml b/.markdownlint.yaml
new file mode 100644
index 00000000..97271f46
--- /dev/null
+++ b/.markdownlint.yaml
@@ -0,0 +1,16 @@
+# SPDX-FileCopyrightText: Contributors to the Power Grid Model project <powergridmodel@lfenergy.org>
+#
+# SPDX-License-Identifier: MPL-2.0
+
+# MD001/heading-increment : Heading levels should only increment by one level at a time : https://github.com/DavidAnson/markdownlint/blob/v0.37.4/doc/md001.md
+MD001: false
+
+# MD013/line-length : Line length : https://github.com/DavidAnson/markdownlint/blob/v0.38.0/doc/md013.md
+line-length:
+  line_length: 120
+  code_blocks: false
+  tables: false
+  stern: true
+
+# MD024/no-duplicate-heading : Multiple headings with the same content : https://github.com/DavidAnson/markdownlint/blob/v0.37.4/doc/md024.md
+MD024: false
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index eb699d29..de240880 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -3,13 +3,13 @@
 # SPDX-License-Identifier: MPL-2.0
 
 repos:
-  - repo: https://github.com/fsfe/reuse-tool
-    rev: v5.0.2
+  - repo: https://github.com/fsfe/reuse-tool  # outside pypi
+    rev: v6.2.0
     hooks:
       - id: reuse
   - repo: https://github.com/astral-sh/ruff-pre-commit
     # Ruff version.
-    rev: v0.11.12
+    rev: v0.14.9
     hooks:
       # Run the linter.
       - id: ruff-check
@@ -19,16 +19,23 @@ repos:
       - id: ruff-format
         name: ruff-format
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.16.0
+    rev: v1.19.0
     hooks:
       - id: mypy
-        additional_dependencies: [numpy, pandas]
+        additional_dependencies:
+          - numpy
+          - types-pyyaml
+          - types-requests
   - repo: local
     hooks:
       - id: pytest
         name: pytest
-        entry: pytest
+        entry: uv run pytest
         language: system
         pass_filenames: false
         always_run: true
-        args: [ "--cov-fail-under=98" ]
+  - repo: https://github.com/igorshubovych/markdownlint-cli  # outside pypi 
+    rev: v0.47.0
+    hooks:
+    - id: markdownlint
+      args: ["--fix"]
diff --git a/.pre-commit-config.yaml.jinja b/.pre-commit-config.yaml.jinja
new file mode 100644
index 00000000..df40387a
--- /dev/null
+++ b/.pre-commit-config.yaml.jinja
@@ -0,0 +1,41 @@
+# SPDX-FileCopyrightText: Contributors to the Power Grid Model project <powergridmodel@lfenergy.org>
+#
+# SPDX-License-Identifier: MPL-2.0
+
+repos:
+  - repo: https://github.com/fsfe/reuse-tool  # outside pypi
+    rev: v6.2.0
+    hooks:
+      - id: reuse
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    # Ruff version.
+    rev: v{{ ruff }}
+    hooks:
+      # Run the linter.
+      - id: ruff-check
+        name: ruff-check
+        args: [ --fix ]
+      # Run the formatter.
+      - id: ruff-format
+        name: ruff-format
+  - repo: https://github.com/pre-commit/mirrors-mypy
+    rev: v{{ mypy }}
+    hooks:
+      - id: mypy
+        additional_dependencies:
+          - numpy
+          - types-pyyaml
+          - types-requests
+  - repo: local
+    hooks:
+      - id: pytest
+        name: pytest
+        entry: uv run pytest
+        language: system
+        pass_filenames: false
+        always_run: true
+  - repo: https://github.com/igorshubovych/markdownlint-cli  # outside pypi 
+    rev: v0.47.0
+    hooks:
+    - id: markdownlint
+      args: ["--fix"]
diff --git a/.python-version b/.python-version
new file mode 100644
index 00000000..6de712a8
--- /dev/null
+++ b/.python-version
@@ -0,0 +1,5 @@
+# SPDX-FileCopyrightText: Contributors to the Power Grid Model project <powergridmodel@lfenergy.org>
+#
+# SPDX-License-Identifier: MPL-2.0
+
+3.14
diff --git a/.readthedocs.yaml b/.readthedocs.yaml
index 71adb3d9..b35eea4e 100644
--- a/.readthedocs.yaml
+++ b/.readthedocs.yaml
@@ -11,11 +11,17 @@ sphinx:
 build:
   os: "ubuntu-24.04"
   tools:
-    python: "3.12"
+    python: "3.14"
   jobs:
+    pre_create_environment:
+      - asdf plugin add uv
+      - asdf install uv latest
+      - asdf global uv latest
+    create_environment:
+      - uv venv "${READTHEDOCS_VIRTUALENV_PATH}"
+    install:
+      - UV_PROJECT_ENVIRONMENT="${READTHEDOCS_VIRTUALENV_PATH}" uv sync --frozen --group doc
     post_install:
-      # Build package with doc requirements from pyproject.optional-dependencies
-      - pip install --verbose --editable .[doc]
       # download support
       - wget -P docs/release_and_support https://github.com/PowerGridModel/.github/raw/main/RELEASE.md
       - wget -P docs/release_and_support https://github.com/PowerGridModel/.github/raw/main/SUPPORT.md
diff --git a/README.md b/README.md
index 61182a3f..cf4015b8 100644
--- a/README.md
+++ b/README.md
@@ -4,7 +4,7 @@ SPDX-FileCopyrightText: Contributors to the Power Grid Model project <powergridm
 SPDX-License-Identifier: MPL-2.0
 -->
 
-[![PyPI version](https://badge.fury.io/py/power-grid-model-io.svg?no-cache)](https://badge.fury.io/py/power-grid-model-io)
+[![PyPI version](https://badge.fury.io/py/power-grid-model-io.svg?no-cache)](https://badge.fury.io/py/power-grid-model-io) <!-- markdownlint-disable-line first-line-h1 line-length -->
 [![Anaconda-Server Badge](https://anaconda.org/conda-forge/power-grid-model-io/badges/version.svg?no-cache)](https://anaconda.org/conda-forge/power-grid-model-io)
 [![License: MIT](https://img.shields.io/badge/License-MPL2.0-informational.svg)](https://github.com/PowerGridModel/power-grid-model-io/blob/main/LICENSE)
 [![Downloads](https://static.pepy.tech/badge/power-grid-model-io)](https://pepy.tech/project/power-grid-model-io)
@@ -24,11 +24,12 @@ SPDX-License-Identifier: MPL-2.0
 
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.8059257.svg)](https://zenodo.org/record/8059257)
 
-[![Power Grid Model logo](https://github.com/PowerGridModel/.github/blob/main/artwork/svg/color.svg)](#)
+[![Power Grid Model logo](https://github.com/PowerGridModel/.github/blob/main/artwork/svg/color.svg)](#) <!-- markdownlint-disable-line no-empty-links line-length -->
 
 # Power Grid Model Input/Output
 
-`power-grid-model-io` can be used for various conversions to the [power-grid-model](https://github.com/PowerGridModel/power-grid-model).
+`power-grid-model-io` can be used for various conversions to the
+[power-grid-model](https://github.com/PowerGridModel/power-grid-model).
 For detailed documentation, see [Read the Docs](https://power-grid-model-io.readthedocs.io/en/stable/index.html).
 
 ## Installation
@@ -36,16 +37,18 @@ For detailed documentation, see [Read the Docs](https://power-grid-model-io.read
 ### Install from PyPI
 
 You can directly install the package from PyPI.
+Although it is opt-in, it is recommended to use [`uv`](https://github.com/astral-sh/uv) as
+your development environment manager.
 
-```
-pip install power-grid-model-io
+```sh
+uv pip install power-grid-model-io
 ```
 
 ### Install from Conda
 
 If you are using `conda`, you can directly install the package from `conda-forge` channel.
 
-```
+```sh
 conda install -c conda-forge power-grid-model-io
 ```
 
@@ -55,18 +58,22 @@ conda install -c conda-forge power-grid-model-io
 
 ## License
 
-This project is licensed under the Mozilla Public License, version 2.0 - see [LICENSE](https://github.com/PowerGridModel/power-grid-model-io/blob/main/LICENSE) for details.
+This project is licensed under the Mozilla Public License, version 2.0 - see
+[LICENSE](https://github.com/PowerGridModel/power-grid-model-io/blob/main/LICENSE) for details.
 
 ## Contributing
 
-Please read [CODE_OF_CONDUCT](https://github.com/PowerGridModel/.github/blob/main/CODE_OF_CONDUCT.md) and [CONTRIBUTING](https://github.com/PowerGridModel/.github/blob/main/CONTRIBUTING.md) for details on the process 
+Please read [CODE_OF_CONDUCT](https://github.com/PowerGridModel/.github/blob/main/CODE_OF_CONDUCT.md) and
+[CONTRIBUTING](https://github.com/PowerGridModel/.github/blob/main/CONTRIBUTING.md) for details on the process
 for submitting pull requests to us.
 
-Visit [Contribute](https://github.com/PowerGridModel/power-grid-model-io/contribute) for a list of good first issues in this repo.
+Visit [Contribute](https://github.com/PowerGridModel/power-grid-model-io/contribute) for a list of good first issues in
+this repo.
 
 ## Citations
 
-If you are using Power Grid Model IO in your research work, please consider citing our library using the following references.
+If you are using Power Grid Model IO in your research work, please consider citing our library using the following
+references.
 
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.8059257.svg)](https://zenodo.org/record/8059257)
 
@@ -100,4 +107,5 @@ If you are using Power Grid Model IO in your research work, please consider citi
 
 ## Contact
 
-Please read [SUPPORT](https://github.com/PowerGridModel/.github/blob/main/SUPPORT.md) for how to connect and get into contact with the Power Grid Model IO project.
+Please read [SUPPORT](https://github.com/PowerGridModel/.github/blob/main/SUPPORT.md) for how to connect and get into
+contact with the Power Grid Model IO project.
diff --git a/docs/converters/converter.md b/docs/converters/converter.md
index af827285..e4d88964 100644
--- a/docs/converters/converter.md
+++ b/docs/converters/converter.md
@@ -6,22 +6,24 @@ SPDX-License-Identifier: MPL-2.0
 
 # Converters
 
-We currently provide 4 types of converters. 
+We currently provide 4 types of converters.
 Here, we discuss their basic structure and guidelines for building a custom converter.
 
-Use the examples notebooks to understand how to convert data from the respective formats. 
+Use the examples notebooks to understand how to convert data from the respective formats.
 
 - **PGM JSON Converter:** Refer to the [PGM JSON Example](../examples/pgm_json_example.ipynb)
 - **VisonExcelConverter** Refer to the [Vision Example](../examples/vision_example.ipynb)
-- **Pandapower Converter:** Converts [pandapower network](https://pandapower.readthedocs.io/en/stable/elements.html) (a dictionary of dataframes) to power-grid-model data.
+- **Pandapower Converter:** Converts [pandapower network](https://pandapower.readthedocs.io/en/stable/elements.html)
+  (a dictionary of dataframes) to power-grid-model data.
 
 Refer to [converters](../power_grid_model_io.md#converters) in API documentation for more details
 
 ## Structure
 
-All converters are derived from the base {py:class}`power_grid_model_io.converters.base_converter`. 
-The usable functions for loading, saving and converting the data are located in the base class. 
-The private functions (`_load_data`, `_parse_data` and `_serialize_data`) are overloaded based on the specific type of converter (i.e., excel, json or pandapower). 
+All converters are derived from the base {py:class}`power_grid_model_io.converters.base_converter`.
+The usable functions for loading, saving and converting the data are located in the base class.
+The private functions (`_load_data`, `_parse_data` and `_serialize_data`) are overloaded based on the specific type of
+converter (i.e., excel, json or pandapower).
 The `VisonExcelConverter` extends the [tabular converters](tabular_converter.md) for Excel exports of Vision.
 It is recommended that custom converters be created in a similar way.
 
@@ -42,10 +44,13 @@ Converter specific methods are presented in corresponding sections.
 
 ### Loading data
 
-Methods load_input_data(), load_update_data(), load_sym_output_data() and load_asym_output_data() are for loading the relevant data to the converter.
-Input data can be configured at converter initialisation by passing the path to source data to parameter `source_file`. Alternatively, the data can also be provided as an argument to the load function after initialisation.
+Methods load_input_data(), load_update_data(), load_sym_output_data() and load_asym_output_data() are for loading the
+relevant data to the converter.
+Input data can be configured at converter initialisation by passing the path to source data to parameter `source_file`.
+Alternatively, the data can also be provided as an argument to the load function after initialisation.
 
-In addition to the input data that will be used in calculations by power-grid-model, other miscellaneous information in the source file is stored in `extra_info`:
+In addition to the input data that will be used in calculations by power-grid-model, other miscellaneous information in
+the source file is stored in `extra_info`:
 
 ```python
 input_data, extra_info = converter.load_input_data(data=example_data)
@@ -54,21 +59,23 @@ input_data, extra_info = converter.load_input_data(data=example_data)
 ### Saving data
 
 It is possible to save the data in the format of the converter.
-The Converter can be instantiated with a path given to `destination_file`. 
+The Converter can be instantiated with a path given to `destination_file`.
 Alternatively, the destination path can be provided in the save function.
-You can also add additional information about each component in the form of `extra_info` generated by [Load data](converter.md#load-data) to be saved along with it.
+You can also add additional information about each component in the form of `extra_info` generated by
+[Load data](converter.md#load-data) to be saved along with it.
 
 ```python
 converter.save(example_data, extra_info=example_extra_info, destination=destination_path)
 ```
 
 ### Configuring the log output
- 
+
 An interface is provided to configure the log level of converters.
 This configuration can be done at converter initialisation or after.
 Notice that this log level only belongs to the logger within the converter.
-Users need to set their basic configuration of the `logging` module to a level that is below what is configuired for the converters.
- 
+Users need to set their basic configuration of the `logging` module to a level that is below what is configuired for the
+converters.
+
 ```python
 # Examplary usage in your script
 import logging
@@ -84,4 +91,4 @@ assert converter_info.get_log_level() == logging.INFO # Previously created conve
 
 converter_ = VisionExcelConverter(input_file, log_level=logging.DEBUG) # Any logs on DEBUG and INFO level will not be logged
 converter_.set_log_level(logging.WARNING) # Now the converter's log level is set to WARNING
-```
\ No newline at end of file
+```
diff --git a/docs/converters/pandapower_converter.md b/docs/converters/pandapower_converter.md
index 5bd2ddd5..7108fd7a 100644
--- a/docs/converters/pandapower_converter.md
+++ b/docs/converters/pandapower_converter.md
@@ -6,25 +6,29 @@ SPDX-License-Identifier: MPL-2.0
 
 # Pandapower converter
 
-The pandapower converter can convert the pandapower `net` to power-grid-model input data. 
+The pandapower converter can convert the pandapower `net` to power-grid-model input data.
 It also converts the power flow output of power-grid-model into the `res_*` Dataframes in the pandapower `net`.
 The converter can be used in a similar way as described in [Converters](converter.md).
 
 ## Cross referencing
 
-Due to differences between the power-grid-model and pandapower, some components in one model are modeled as multiple components in the other or vise versa.
-An example on how to cross-reference can be found in the [pandapower conversion example](../examples/pandapower_example.ipynb#cross-referencing-objects).
+Due to differences between the power-grid-model and pandapower, some components in one model are modeled as multiple
+components in the other or vise versa.
+An example on how to cross-reference can be found in the
+[pandapower conversion example](../examples/pandapower_example.ipynb#cross-referencing-objects).
 
 ## Defaults
 
-If any of the essential tap attributes: `tap_pos`, `tap_nom`, `tap_side` are not available then the tap feature for transformers are disabled by setting `tap_nom=tap_pos=0` via conversion.
-If a `vector_group` is not available for transformer then a default is set in conversion as `YNyn` for even clocks and `DYn` for odd clocks.
+If any of the essential tap attributes: `tap_pos`, `tap_nom`, `tap_side` are not available then the tap feature for
+transformers are disabled by setting `tap_nom=tap_pos=0` via conversion.
+If a `vector_group` is not available for transformer then a default is set in conversion as `YNyn` for even clocks and
+`DYn` for odd clocks.
 Similarly for three winding transformer, `YNynyn` is set for even clocks of `shift_mv_degree` and `shift_lv_degree`.
 If the clocks are odd, then the vector group is converted as `YNynd`, `YNdyn` or `YNdd`.
 
 ## Modeling differences
 
-The user must be aware of following unsupported features or differences in conversion. 
+The user must be aware of following unsupported features or differences in conversion.
 
 * Currently, the conversions only support powerflow calculations and their relevant attributes.
 * Any feature involving a PV bus, i.e., generator, DC line are unsupported as of now.
@@ -43,7 +47,8 @@ The features regarding `in_ka` and `z_ohm` attributes are currently unsupported.
 
 The external grid is modeled with a source impedance all sequence components in power-grid-model.
 Whereas it is only present in negative and zero sequence networks in pandapower.
-Hence, this impedance value has to be mentioned in the power-flow calculation when using the power-grid-model power flow calculation.
+Hence, this impedance value has to be mentioned in the power-flow calculation when using the power-grid-model power flow
+calculation.
 
 ### Transformer
 
@@ -51,10 +56,12 @@ Custom zero sequence parameters in transformers are not supported.
 The same ones as positive sequence admittance is used in power-grid-model.
 The changing of impedance by the means of characteristics in `net.characteristic` is not directly supported.
 The phase shift in angle by transforermers by the `shift_degree` attribute only supports clock values in PGM.
-The `tap_phase_shifter` transformer and shifting of angles with tap via `tap_step_degree` are features not added in power-grid-model yet.
-The default for transformer model to be used in pandapower is `t` model but power-grid-model supports only `pi` model of transformer hence this may create a minor difference calculation.
+The `tap_phase_shifter` transformer and shifting of angles with tap via `tap_step_degree` are features not added in
+power-grid-model yet.
+The default for transformer model to be used in pandapower is `t` model but power-grid-model supports only `pi` model of
+transformer hence this may create a minor difference calculation.
 
 ### Three  winding transformer
 
 The differences defined in [Transformer](#transformer) are applicable here as well.
-Additionally, tap connection at star point, i.e., `tap_at_star_point` is not supported.
\ No newline at end of file
+Additionally, tap connection at star point, i.e., `tap_at_star_point` is not supported.
diff --git a/docs/converters/tabular_converter.md b/docs/converters/tabular_converter.md
index 391ae084..58c5c780 100644
--- a/docs/converters/tabular_converter.md
+++ b/docs/converters/tabular_converter.md
@@ -4,13 +4,18 @@ SPDX-FileCopyrightText: Contributors to the Power Grid Model project <powergridm
 SPDX-License-Identifier: MPL-2.0
 -->
 # Tabular converter
-Tabular data is commonly stored in spreadsheet files: Excel files, CSV files, GNF files, databases, pandas DataFrames, etc.
-The similarity between all tabular data is that it contains multiple `tables`, each with multiple `columns`, possibly with a specific `unit` row.
+
+Tabular data is commonly stored in spreadsheet files:
+Excel files, CSV files, GNF files, databases, pandas DataFrames, etc.
+The similarity between all tabular data is that it contains multiple `tables`, each with multiple `columns`, possibly
+with a specific `unit` row.
 Others may have categorical values that need to be further mapped (i.e., open: 0, closed: 1).
 These attributes are referred to as `substitutions`.
 
 ## Mapping file
+
 A mapping file is a yaml file with three main sections `grid`, `units` and `substitutions`:
+
 ```yaml
 grid:
 
@@ -52,31 +57,40 @@ substitutions:
 ```
 
 ## Grid
+
 For each `table`, the target PGM `component` is listed (e.g., Nodes: node, Cables: line).
 The for each PGM `column` the source column is supplied (e.g., u_rated: Unom, from_status: From.SwitchStatus).
 
 ## Field Definitions
-If the `column` definition is a one-on-one mapping, the value is simply the name of the source column (e.g., u_rated: Unom).
+
+If the `column` definition is a one-on-one mapping, the value is simply the name of the source column
+(e.g., u_rated: Unom).
 In many other cases, however, mappings can be a bit more complex.
 You can use the following `column` definitions:
 
-  * Column name `str`
+* Column name `str`
+
     ```yaml
     from_node: From.Number
     ```
-  * First matching column name that exists in the data `str`
+
+* First matching column name that exists in the data `str`
+
     ```yaml
     p_specified: Inverter.Pnom | Inverter.Snom
     ```
-  * Automatic IDs `Dict[str, Dict[str, Any]]` with single key `reference`, required attribute `key` and optional
-    attributes `table` and `name`. More extensive examples are shown in the section [AutoID Mapping](##autois-mapping).
+
+* Automatic IDs `Dict[str, Dict[str, Any]]` with single key `reference`, required attribute `key` and optional
+    attributes `table` and `name`. More extensive examples are shown in the section [AutoID Mapping](#autoid-mapping).
+
     ```yaml
     id:
       auto_id:
         key: Number
     ```
 
-  * Reference to a column on another sheet `Dict[str, Dict[str, Any]]` with single key `reference` and the
+* Reference to a column on another sheet `Dict[str, Dict[str, Any]]` with single key `reference` and the
+
     ```yaml
     r1:
       reference:
@@ -85,27 +99,35 @@ You can use the following `column` definitions:
         key_column: Type short
         value_column: R
     ```
-  * Constant value `int` or `float`
+
+* Constant value `int` or `float`
+
     ```yaml
     from_status: 1
     tan1: 0.0
     ```
-  * Pandas DataFrame functions `Dict[str, List[Any]]`
+
+* Pandas DataFrame functions `Dict[str, List[Any]]`
     (`prod`, `sum`, `min`, `max`, etc. and the alias `multiply` which translates to `prod`)
+
     ```yaml
     p_specified:
       min:
         - Pnom
         - Inverter.Pnom
     ```
-  * Custom functions `Dict[str, Dict[str, Any]]`
+
+* Custom functions `Dict[str, Dict[str, Any]]`
+
     ```yaml
       g0:
         power_grid_model_io.functions.complex_inverse_real_part:
           real: R0
           imag: X0
     ```
-  * Nested definitions:
+
+* Nested definitions:
+
     ```yaml
     q_specified:
       power_grid_model_io.functions.phase_to_phase.reactive_power:
@@ -115,7 +137,9 @@ You can use the following `column` definitions:
             - Inverter.Pnom | Inverter.Snom
         cos_phi: Inverter.cos phi
     ```
+
     Is similar to something like:
+
     ```python
     from power_grid_model_io.functions.phase_to_phase import reactive_power
 
@@ -129,9 +153,14 @@ You can use the following `column` definitions:
     ```
 
 ## Units
-Power Grid Model uses SI units (e.g., "W" for Watts), but source data may be supplied in different units (e.g., "MW" for Mega Watts).
-If units are supplied in the tabular data, the data stored using pandas DataFrame is expected to have `MultiIndexes` for columns.
-For our application, a `MultiIndex` can be interpreted as a tuple; the first element is the column name, the second element is the column unit. For example: `("C0", "µF")`.
+
+Power Grid Model uses SI units (e.g., "W" for Watts), but source data may be supplied in different units
+(e.g., "MW" for Mega Watts).
+If units are supplied in the tabular data, the data stored using pandas DataFrame is expected to have `MultiIndexes` for
+columns.
+For our application, a `MultiIndex` can be interpreted as a tuple;
+the first element is the column name, the second element is the column unit.
+For example: `("C0", "µF")`.
 
 If an optional unit is supplied, it should be defined in the unit section of the mapping.
 Undefined units that do not exist in mapping are not allowed.
@@ -144,16 +173,20 @@ units:
   ohm/m:
     ohm/km: 0.001
 ```
+
 The definitions above can be interpreted as:
-  * **A** is a valid SI unit
-  * **F** is a valid SI unit
-    * 1 **µF** = 0.000001 **F**
-  * **ohm/m** is a valid SI unit
-    * 1 **ohm/km** = 0.001 **ohm/m**
+
+* **A** is a valid SI unit
+* **F** is a valid SI unit
+  * 1 **µF** = 0.000001 **F**
+* **ohm/m** is a valid SI unit
+  * 1 **ohm/km** = 0.001 **ohm/m**
 
 ## Substitutions
+
 Some columns may contain categorical values (enums) that should be mapped. The column names can be defined as
 regular expressions.
+
 ```yaml
 substitutions:
   ".*Switch state":
@@ -164,14 +197,17 @@ substitutions:
     none: false
     own: true
 ```
+
 The definitions above can be interpreted as:
-  * In all columns that end with `SwitchState` (e.g., `From.Switch State`, `To.Switch State` or just `Switch State`),
+
+* In all columns that end with `SwitchState` (e.g., `From.Switch State`, `To.Switch State` or just `Switch State`),
     the word "off" should be replaced with integer value 0, and the word "in" integer value 1.
-  * In all columns called "N1",
+* In all columns called "N1",
     the word "none" should be replaced with the boolean value `false`,
     and the word "own" boolean value `true`.
 
 ## AutoID
+
 The `id` field is special in the sense that each object should have a unique numerical id in power grid model.
 Therefore, each id definition is mapped to a numerical (integer) ID.
 Field names that end with `node` are also mapped to corresponding numerical IDs.
@@ -189,8 +225,10 @@ item = auto_id[1]      # item = "Bravo"
 See also {py:class}`power_grid_model_io.utils.AutoID`
 
 ## AutoID Mapping
+
 Let's consider a very common example of the usage of `auto_id` in a mapping file
 (note that we're focussing on the ids and references, other attributes are therefore omitted).
+
 ```yaml
   Nodes:
     node:
@@ -213,7 +251,9 @@ Let's consider a very common example of the usage of `auto_id` in a mapping file
             key:
               Number: To_Number
 ```
+
 This basically reads:
+
 * For each row in the Nodes table, a PGM node instance is created.
   * For each node instance, a numerical id is generated, which is unique for each value in the Number column. This
     assumes that the Number column is unique in the source table. Let's say tha values of the Number column in that
@@ -240,11 +280,12 @@ This basically reads:
     * `{"table": "Nodes", "key" {"Number": 102} -> 1`
     * `{"table": "Nodes", "key" {"Number": 103} -> 2`
 
-
 ## Advanced AutoID Mapping
+
 In some cases, multiple components have to be created for each row in a source table.
 In such cases, the `name` attribute may be necessary to create multiple PGM IDs for a single row. Consider
 this example:
+
 ```yaml
   Transformer loads:
     transformer:
@@ -289,6 +330,7 @@ this example:
 
 Suppose we have one Transformer Load connected to the Node Number 103 and its Subnumber is 1.
 Then the following IDs will be generated / retrieved:
+
 * `transformer.id`:
   `{"table": "Transformer loads", "name": "transformer", "key" {"Node_Number": 103, "Subnumber": 1} -> 5`
 * `transformer.from_node`:
@@ -315,7 +357,11 @@ Transformer Load:
   sym_gen: ...
 ```
 
-Then for each row in `Transformer Load` table, all 5 corresponding PGM components are created. But if it is the intention is to make some of these components optional, then it is possible to do so with the help of `filters` functions. These functions apply a mask based on the rules provided by the funciton. All components are selected from the start and the `filters` are then applied in a recursive `and` way.
+Then for each row in `Transformer Load` table, all 5 corresponding PGM components are created.
+But if it is the intention is to make some of these components optional, then it is possible to do so with the help of
+`filters` functions.
+These functions apply a mask based on the rules provided by the funciton.
+All components are selected from the start and the `filters` are then applied in a recursive `and` way.
 
 For example, `exclude_value` excludes all rows which match at the `value` for the `col` specified.
 
@@ -329,14 +375,20 @@ Transformers:
           value: 0
 ```
 
-
 ## Security Considerations
-Mapping files enable the specification of custom mappings or filter functions. These functions can come from the `power-grid-model-io` library, be user-provided, or even supplied by third parties. To ensure security, we have implemented several measures. Best practices are recommended to prevent malicious code execution.
+
+Mapping files enable the specification of custom mappings or filter functions.
+These functions can come from the `power-grid-model-io` library, be user-provided, or even supplied by third parties.
+To ensure security, we have implemented several measures.
+Best practices are recommended to prevent malicious code execution.
 
 ### Safe Loading of Configuration Files
-We use the `yaml.safe_load` functionality from the PyYAML library to load configuration files securely. This method prevents the execution of potentially malicious code during the loading process.
+
+We use the `yaml.safe_load` functionality from the PyYAML library to load configuration files securely.
+This method prevents the execution of potentially malicious code during the loading process.
 
 ### Secure Function Handling
+
 * No `eval`-like Functionality:
 
   We do not use `eval` or similar functions that can execute arbitrary code.
@@ -350,18 +402,24 @@ We use the `yaml.safe_load` functionality from the PyYAML library to load config
 
   * Prefixed by Import Path:
 
-    Functions must include their relative or absolute import path, ensuring they are importable using `import_module`. For example, `numpy.max` is allowed, but `np.max` is not.
+    Functions must include their relative or absolute import path, ensuring they are importable using `import_module`.
+    For example, `numpy.max` is allowed, but `np.max` is not.
 
 ### Prevention of Malicious Code Injection
+
 The rules mentioned above prevent the inclusion of malicious code like:
+
 ```python
 lambda x: return (malicious_code(), normal_code(x))[1]
 ```
+
 which, in normal operation without any malicious intentions, would be provided as plainly `normal_code`.
 
-We enforce above mentioned rules, completely rejecting the malicious snippet, and therefore prevent any potential harm from `malicious_code`.
+We enforce above mentioned rules, completely rejecting the malicious snippet, and therefore prevent any potential harm
+from `malicious_code`.
 
 ### Best Practices for Production Environments
+
 * File Permissions
 
   Configuration files should be treated similarly to Python source files, with appropriate file permissions.
diff --git a/docs/converters/vision_converter.md b/docs/converters/vision_converter.md
index 2fee20e6..26af3499 100644
--- a/docs/converters/vision_converter.md
+++ b/docs/converters/vision_converter.md
@@ -5,22 +5,29 @@ SPDX-License-Identifier: MPL-2.0
 
 # Vision converter
 
-The Vision Excel converter converts the Excel exports from Vision to PGM data format. As mentioned in [Converters](converters/converter.md), Vision Excel converter is an implementation of the tabular converter.
-The default mapping of all attributes is stored in the `vision_en.yaml` and `vision_nl.yaml` files in [config](https://github.com/PowerGridModel/power-grid-model-io/tree/main/src/power_grid_model_io/config) directory.
+The Vision Excel converter converts the Excel exports from Vision to PGM data format.
+As mentioned in [Converters](converters/converter.md), Vision Excel converter is an implementation of the tabular
+converter.
+The default mapping of all attributes is stored in the `vision_en.yaml` and `vision_nl.yaml` files in
+[config](https://github.com/PowerGridModel/power-grid-model-io/tree/main/src/power_grid_model_io/config) directory.
 Custom mapping files are supported via passing the file directory to the constructor of the converter.
 
 ## Load rate of elements
 
-Certain `elements` in Vision, i.e., appliances like transformer loads and induction motor have a result parameter of load rate.
+Certain `elements` in Vision, i.e., appliances like transformer loads and induction motor have a result parameter of
+load rate.
 In Vision, load rates are calculated without considering the simultaneity factors of connected nodes.
-So we may observe a variation in power inflow/outflow result (i.e., P, Q and S) due to different simultaneity factors. But the load rate always corresponds to `simultaneity of loads=1`.
+So we may observe a variation in power inflow/outflow result (i.e., P, Q and S) due to different simultaneity factors.
+But the load rate always corresponds to `simultaneity of loads=1`.
 
-When we make conversion to PGM, the input data attributes of PGM for loads like `p_specified` and `q_specified` are modified as per simultaneity. The resulting loading then takes simultaneity into account.
+When we make conversion to PGM, the input data attributes of PGM for loads like `p_specified` and `q_specified` are
+modified as per simultaneity. The resulting loading then takes simultaneity into account.
 **Hence, the loading of such elements may not correspond to the load rate obtained in Vision**
 
 ## Transformer load modeling
 
-power-grid-model-io converts the transformer load into a individual transformer and a load for usage in power-grid-model.
+power-grid-model-io converts the transformer load into a individual transformer and a load for usage in
+power-grid-model.
 To the best of our knowledge, Vision modeles a transformer load differently than an individual transformer plus load.
 There is a minor difference in both the reactive power consumed and generated.
 This might correspond to a minor voltage deviation in the results.
@@ -32,36 +39,81 @@ This can be done by first selecting the transformer loads: [Start | Select | Obj
 
 ## Voltage angle of buses in symmetric power-flow
 
-Note that in symmetrical calculations, Vision does not include clock angles of transformers in the result of voltage angles. power-grid-model, however, does consider them. Therefore when doing a direct comparison of angle results, this needs to be taken into consideration.
+Note that in symmetrical calculations, Vision does not include clock angles of transformers in the result of voltage
+angles.
+power-grid-model, however, does consider them.
+Therefore when doing a direct comparison of angle results, this needs to be taken into consideration.
 
 ## Modeling differences or unsupported attributes
 
-Some components are yet to be modeled for conversions because they might not have a straightforward mapping in power-grid-model. Those are listed here.
+Some components are yet to be modeled for conversions because they might not have a straightforward mapping in
+power-grid-model.
+Those are listed here.
 
 - power-grid-model currently does not support PV(Active Power-Voltage) bus and related corresponding features.
-- Currently, the efficiency type of PVs(Photovoltaics) element is also unsupported for all types except the `100%` type. For the efficiency type: `0, 1 pu: 93 %; 1 pu: 97 %`, the generation power is multiplied by 97% as a closest approximation.
-- The conversions for load behaviors of `industry`, `residential` and `business` are not yet modeled. The load behaviors usually do not create a significant difference in power-flow results for most grids when the voltage at bus is close to `1 pu`. Hence, the conversion of the mentioned load behaviors is approximated to be of `Constant Power` type for the time being.
-- The source bus in power-grid-model is mapped with a source impedance. `Sk"nom`, `R/X` and `Z0/Z1` are the attributes used in modeling source impedance. In Vision, these attributes are used only for short circuit calculations
-- The load rate for transformer is calculated in Vision by current i.e., `load_rate = max(u1 * I1, u2 * I2) * sqrt(3) / Snom * 100`. Whereas in power-grid-model, loading is calculated by power, i.e., `loading = max(s1,s2)/sn`. (Note: The attribute names are as per relevant notation in Vision and PGM respectively). This gives a slight difference in load rate of transformer.
-- A minor difference in results is expected since Vision uses a power mismatch in p.u. as convergence criteria whereas power-grid-model uses voltage mismatch.
-- The Voltage Control option in vision is modelled by `transformer_tap_regulator` in PGM. Currently, PGM only supports line drop compensation on both loading and generating direction.
-So the unchecking of `Also in backw. direction`. Neither `Load Dependent` compensation or a master-slave configuration for control under the `State` section is supported.
+- Currently, the efficiency type of PVs(Photovoltaics) element is also unsupported for all types except the `100%` type.
+  For the efficiency type: `0, 1 pu: 93 %; 1 pu: 97 %`, the generation power is multiplied by 97% as a closest
+  approximation.
+- The conversions for load behaviors of `industry`, `residential` and `business` are not yet modeled.
+  The load behaviors usually do not create a significant difference in power-flow results for most grids when the
+  voltage at bus is close to `1 pu`.
+  Hence, the conversion of the mentioned load behaviors is approximated to be of `Constant Power` type for the time
+  being.
+- The source bus in power-grid-model is mapped with a source impedance. `Sk"nom`, `R/X` and `Z0/Z1` are the attributes
+  used in modeling source impedance.
+  In Vision, these attributes are used only for short circuit calculations
+- The load rate for transformer is calculated in Vision by current i.e.,
+  `load_rate = max(u1 * I1, u2 * I2) * sqrt(3) / Snom * 100`.
+  Whereas in power-grid-model, loading is calculated by power, i.e., `loading = max(s1,s2)/sn`.
+  (Note: The attribute names are as per relevant notation in Vision and PGM respectively).
+  This gives a slight difference in load rate of transformer.
+- A minor difference in results is expected since Vision uses a power mismatch in p.u. as convergence criteria whereas
+  power-grid-model uses voltage mismatch.
+- The Voltage Control option in vision is modelled by `transformer_tap_regulator` in PGM.
+  Currently, PGM only supports line drop compensation on both loading and generating direction.
+  So this is equivalent to unchecking of `Also in backw. direction`.
+  Neither `Load Dependent` compensation or a master-slave configuration for control under the `State` section is
+  supported.
 
 ## Accomdation of UUID-based id system since Vision 9.7
-Vision introduced UUID based identifier system since version 9.7. It is implemented following the Microsoft naming scheme by replacing all the original identifier fields (i.e., '*Number', '*Subnumber', '*Nummber' and '*Subnummer') to GUID. This change brings the many benefits of UUIDs in general while on the other hand adds certain work on the conversion side. Since computations in PGM alone do not benefit from a string based identifier, we hence made the descision to perform UUID to integer conversion while maintaining the 'GUID' information in the `extra_info` field. Note that existing mapping files can still be used without significant changes, apart from adding `GUID` to the `extra` fields of interest.
+
+Vision introduced UUID based identifier system since version 9.7.
+It is implemented following the Microsoft naming scheme by replacing all the original identifier fields
+(i.e., '*Number', '*Subnumber', '*Nummber' and '*Subnummer') to GUID.
+This change brings the many benefits of UUIDs in general while on the other hand adds certain work on the conversion
+side.
+Since computations in PGM alone do not benefit from a string based identifier, we hence made the descision to perform
+UUID to integer conversion while maintaining the 'GUID' information in the `extra_info` field.
+Note that existing mapping files can still be used without significant changes, apart from adding `GUID` to the `extra`
+fields of interest.
 
 An examplery usage can be found in the example notebook as well as in the test cases.
 
 ## Common/Known issues related to Vision
-So far we have the following issue known to us related to Vision exported spread sheets. We provide a solution from user perspective to the best of our knowledge.
+
+So far we have the following issue known to us related to Vision exported spread sheets.
+We provide a solution from user perspective to the best of our knowledge.
 
 ### Duplicated `P` columns
-Vision can export sheets with duplicated `P` columns, one of which being unitless additional information. This field is of no actual purpose within PGM calculation. In case of duplicate column names, PGM-IO renames them to eg. `P`, `P_2` and so on. However the change in mapping to the duplicate name should be done manually by the user in a custom mapping file.
+
+Vision can export sheets with duplicated `P` columns, one of which being unitless additional information.
+This field is of no actual purpose within PGM calculation.
+In case of duplicate column names, PGM-IO renames them to, e.g., `P`, `P_2` and so on.
+However the change in mapping to the duplicate name should be done manually by the user in a custom mapping file.
 
 **Tip:** We advice users to uncheck the `specifics` when exporting from Vision and an extra `P` column would not appear.
 
 ### Different names for columns
-In different versions of exports, user can sometimes find different names for columns. For example, the column name `N1` might be represented as `Grounding1` in some exports. To address this, the `VisionExcelConverter`'s `terms_changed` argument can be used.
+
+In different versions of exports, user can sometimes find different names for columns.
+For example, the column name `N1` might be represented as `Grounding1` in some exports.
+To address this, the `VisionExcelConverter`'s `terms_changed` argument can be used.
 
 ### Sheets being ignored
-In different versions of exports, user can find different names for the spreadsheets. All sheets not specified in the mapping file are ignored for conversion. Hence if the mapping has an incorrect sheet name, they would not be considered in conversion and no error shall be given out. The user should use the adequate mapping file for different vision versions. And if the default mapping is modified, it is advised to verify if all required sheets are being converted.
+
+In different versions of exports, user can find different names for the spreadsheets.
+All sheets not specified in the mapping file are ignored for conversion.
+Hence if the mapping has an incorrect sheet name, they would not be considered in conversion and no error shall be given
+out.
+The user should use the adequate mapping file for different vision versions.
+And if the default mapping is modified, it is advised to verify if all required sheets are being converted.
diff --git a/docs/data_store.md b/docs/data_store.md
index 769f57c2..70d0d00b 100644
--- a/docs/data_store.md
+++ b/docs/data_store.md
@@ -6,7 +6,8 @@ SPDX-License-Identifier: MPL-2.0
 
 # Data Stores
 
-Data stores are part of converters which perform the actions of loading and saving the data in the particular format of the data store.
+Data stores are part of converters which perform the actions of loading and saving the data in the particular format of
+the data store.
 There are two data stores in each converter for source and destination data.
 
 The inheritance structure of data stores is as follows:
@@ -17,11 +18,14 @@ The inheritance structure of data stores is as follows:
     - Vision-excel file store
 
 Of these, JSON file store, Vision-excel file stores are used in their respective converters.
-A custom data store can be based on any of these existing stores. It has to convert the data to the specific data type. eg. tabular data.
+A custom data store can be based on any of these existing stores.
+It has to convert the data to the specific data type.
+E.g., tabular data.
 
 ## JSON file store
 
-This is the JSON format used in power-grid-model. It is used by PGM JSON converter. See `power_grid_model.utils` for more info.
+This is the JSON format used in power-grid-model. It is used by PGM JSON converter.
+See `power_grid_model.utils` for more info.
 
 ## Excel file store
 
@@ -35,4 +39,3 @@ Also refer {py:class}`power_grid_model_io.data_stores.ExcelFileStore` for specif
 
 The vision excel export specific operations in conversion  are carried out.
 Eg. Vision exports has the units on the 2nd row.
-
diff --git a/docs/index.md b/docs/index.md
index 14396d05..8f1b48a4 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -12,31 +12,36 @@ SPDX-License-Identifier: MPL-2.0
 :align: right
 ```
 
-Power Grid Model IO is a tool to convert grid data to and from the native data format of [power-grid-model](https://github.com/PowerGridModel/power-grid-model).
+Power Grid Model IO is a tool to convert grid data to and from the native data format of
+[power-grid-model](https://github.com/PowerGridModel/power-grid-model).
 Currently, conversions from Vision excel exports and Pandapower are possible.
 
-Some formats may be similar to the format used by [power-grid-model](https://github.com/PowerGridModel/power-grid-model), but use a different underlying data structure.
+Some formats may be similar to the format used by
+[power-grid-model](https://github.com/PowerGridModel/power-grid-model), but use a different underlying data structure.
 While we do not formally support those formats, you may find examples in this documentation for some of them.
 
 ## Install from PyPI
 
 You can directly install the package from PyPI.
+Although it is opt-in, it is recommended to use [`uv`](https://github.com/astral-sh/uv) as
+your development environment manager.
 
-```
-pip install power-grid-model-io
+```sh
+uv add power-grid-model-io
 ```
 
 ## Install from Conda
 
 If you are using `conda`, you can directly install the package from `conda-forge` channel.
 
-```
+```sh
 conda install -c conda-forge power-grid-model-io
 ```
 
 ## Citations
 
-If you are using Power Grid Model IO in your research work, please consider citing our library using the references in [Citation](release_and_support/CITATION.md).
+If you are using Power Grid Model IO in your research work, please consider citing our library using the references in
+[Citation](release_and_support/CITATION.md).
 
 ## Contents
 
diff --git a/docs/power_grid_model_io.md b/docs/power_grid_model_io.md
index a516c441..73c2e6e1 100644
--- a/docs/power_grid_model_io.md
+++ b/docs/power_grid_model_io.md
@@ -39,6 +39,7 @@ SPDX-License-Identifier: MPL-2.0
 .. automodule:: power_grid_model_io.functions._functions
 .. automodule:: power_grid_model_io.functions.phase_to_phase
 ```
+
 ## mappings
 
 ```{eval-rst}
diff --git a/pyproject.toml b/pyproject.toml
index 312ffdf6..b96c35d1 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -39,22 +39,33 @@ dependencies = [
 ]
 dynamic = ["version"]
 
-[project.optional-dependencies]
-dev = [
-    "pre-commit",
-    "pylint",
+[dependency-groups]
+
+test = [
     "pytest",
     "pytest-cov",
-    "ruff",
     "pydantic>2", # Used in unit tests
     "pandapower>2.11.1",
     "lxml", # missing pandapower dependency
 ]
+
+lint = [
+    "pre-commit",
+    "ruff",
+    "mypy",
+    "numpy", # needed for mypy
+    "types-pyyaml", # needed for mypy
+    "types-requests", # needed for mypy
+]
+
+dev = [{ include-group = "test" }, { include-group = "lint" }]
+
 examples = [
     "power-grid-model>1.9.80",
     "pandapower>2.11.1",
     "pyarrow", # Pyarrow support for Python 3.12 scheduled for 14.0.0: https://github.com/apache/arrow/issues/37880
 ]
+
 doc = [
     "sphinx",
     "myst-nb",
diff --git a/src/power_grid_model_io/converters/pgm_json_converter.py b/src/power_grid_model_io/converters/pgm_json_converter.py
index bd0ef6b7..04c646e2 100644
--- a/src/power_grid_model_io/converters/pgm_json_converter.py
+++ b/src/power_grid_model_io/converters/pgm_json_converter.py
@@ -143,6 +143,8 @@ def _parse_component(
         """
         # We'll initialize an 1d-array with NaN values for all the objects of this component type
         array = initialize_array(data_type, component, len(objects))
+        if array.dtype.names is None:
+            raise ValueError(f"Invalid component type: {component.value}")
 
         for i, obj in enumerate(objects):
             # As each object is a separate dictionary, and the attributes may differ per object, we need to check
diff --git a/src/power_grid_model_io/converters/tabular_converter.py b/src/power_grid_model_io/converters/tabular_converter.py
index d6cee260..d28c66dd 100644
--- a/src/power_grid_model_io/converters/tabular_converter.py
+++ b/src/power_grid_model_io/converters/tabular_converter.py
@@ -14,7 +14,7 @@
 import numpy as np
 import pandas as pd
 import yaml
-from power_grid_model import DatasetType, initialize_array
+from power_grid_model import ComponentType, DatasetType, initialize_array
 from power_grid_model.data_types import Dataset
 
 from power_grid_model_io.converters.base_converter import BaseConverter
@@ -115,7 +115,7 @@ def _parse_data(self, data: TabularData, data_type: DatasetType, extra_info: Opt
             data.set_substitutions(self._substitutions)
 
         # Initialize some empty data structures
-        pgm: Dict[str, List[np.ndarray]] = {}
+        pgm: Dict[ComponentType, List[np.ndarray]] = {}
 
         # For each table in the mapping
         for table in self._mapping.tables():
@@ -132,8 +132,8 @@ def _parse_data(self, data: TabularData, data_type: DatasetType, extra_info: Opt
                 )
                 if component_data is not None:
                     if component not in pgm:
-                        pgm[component] = []
-                    pgm[component].append(component_data)
+                        pgm[ComponentType(component)] = []
+                    pgm[ComponentType(component)].append(component_data)
 
         input_data = TabularConverter._merge_pgm_data(data=pgm)
         self._log.debug(
@@ -357,14 +357,12 @@ def _handle_extra_info(  # pylint: disable = too-many-arguments,too-many-positio
                     extra_info[i] = xtr
 
     @staticmethod
-    def _merge_pgm_data(data: Dict[str, List[np.ndarray]]) -> Dict[str, np.ndarray]:
+    def _merge_pgm_data(data: Dict[ComponentType, List[np.ndarray]]) -> Dict[ComponentType, np.ndarray]:
         """During the conversion, multiple numpy arrays can be produced for the same type of component. These arrays
         should be concatenated to form one large table.
 
         Args:
-          data: For each component, one or more numpy structured arrays
-          data: Dict[str:
-          List[np.ndarray]]:
+          data: Dict[ComponentType, List[np.ndarray]]: For each component, one or more numpy structured arrays
 
         Returns:
 
diff --git a/tests/unit/converters/test_tabular_converter.py b/tests/unit/converters/test_tabular_converter.py
index 157bc807..ae9465b1 100644
--- a/tests/unit/converters/test_tabular_converter.py
+++ b/tests/unit/converters/test_tabular_converter.py
@@ -60,7 +60,7 @@ def tabular_data():
 
 
 @pytest.fixture
-def tabular_data_no_units_no_substitutions():
+def tabular_data_no_units_no_substitutions() -> TabularData:
     nodes = pd.DataFrame(data=[[1, 10.5e3], [2, 400.0]], columns=["id_number", "u_nom"])
     lines = pd.DataFrame(data=[[1, 2], [3, 1]], columns=["id_number", "from_node_side"])
     sources = pd.DataFrame(columns=["id_number", "node_side"])
@@ -80,7 +80,7 @@ def test_set_mapping_file(converter: TabularConverter):
 
 def test_parse_data(converter: TabularConverter, tabular_data: TabularData):
     data = MagicMock()
-    converter._parse_data(data=data, data_type="dummy", extra_info=None)
+    converter._parse_data(data=data, data_type=MagicMock(), extra_info=None)
     data.set_unit_multipliers.assert_called_once()
     data.set_substitutions.assert_called_once()
 
@@ -590,7 +590,7 @@ def test_parse_reference(converter: TabularConverter, tabular_data_no_units_no_s
     assert_frame_equal(df_lines_from_node_long, pd.DataFrame([400.0, 10.5e3], columns=["u_nom"]))
 
 
-def test_parse_col_def_filter(converter: TabularConverter):
+def test_parse_col_def_filter(converter: TabularConverter, tabular_data_no_units_no_substitutions: TabularData):
     # Act/Assert:
     with pytest.raises(AssertionError):
         converter._parse_col_def_filter(
diff --git a/tests/validation/converters/test_pandapower_converter_input.py b/tests/validation/converters/test_pandapower_converter_input.py
index 1badfa3c..d0def717 100644
--- a/tests/validation/converters/test_pandapower_converter_input.py
+++ b/tests/validation/converters/test_pandapower_converter_input.py
@@ -43,7 +43,7 @@ def load_validation_data() -> Tuple[SingleDataset, ExtraInfo]:
     with warnings.catch_warnings():
         warnings.simplefilter("ignore")
 
-        data, extra_info = load_json_single_dataset(VALIDATION_FILE, data_type="input")
+        data, extra_info = load_json_single_dataset(VALIDATION_FILE, data_type=DatasetType.input)
 
     return data, extra_info
 
@@ -83,7 +83,7 @@ def test_input_data(input_data: Tuple[SingleDataset, SingleDataset]):
 
 
 @pytest.mark.parametrize(("component", "attribute"), component_attributes(VALIDATION_FILE, data_type=DatasetType.input))
-def test_attributes(input_data: Tuple[SingleDataset, SingleDataset], component: str, attribute: str):
+def test_attributes(input_data: Tuple[SingleDataset, SingleDataset], component: ComponentType, attribute: str):
     """
     For each attribute, check if the actual values are consistent with the expected values
     """
@@ -107,7 +107,7 @@ def test_attributes(input_data: Tuple[SingleDataset, SingleDataset], component:
     ("component", "obj_ids"),
     (pytest.param(component, objects, id=component) for component, objects in component_objects(VALIDATION_FILE)),
 )
-def test_extra_info(extra_info: Tuple[ExtraInfo, ExtraInfo], component: str, obj_ids: List[int]):
+def test_extra_info(extra_info: Tuple[ExtraInfo, ExtraInfo], component: ComponentType, obj_ids: List[int]):
     """
     For each object, check if the actual extra info is consistent with the expected extra info
     """
diff --git a/tests/validation/converters/test_vision_excel_converter.py b/tests/validation/converters/test_vision_excel_converter.py
index dc552e14..5f6610bf 100644
--- a/tests/validation/converters/test_vision_excel_converter.py
+++ b/tests/validation/converters/test_vision_excel_converter.py
@@ -11,7 +11,7 @@
 import numpy as np
 import pandas as pd
 import pytest
-from power_grid_model import DatasetType
+from power_grid_model import ComponentType, DatasetType
 from power_grid_model.data_types import SingleDataset
 
 from power_grid_model_io.converters import VisionExcelConverter
@@ -59,7 +59,7 @@ def load_validation_data(language: str) -> Tuple[SingleDataset, ExtraInfo]:
     Load the validation data from the json file
     """
     validation_file = Path(str(VALIDATION_FILE).format(language=language))
-    data, extra_info = load_json_single_dataset(validation_file, data_type="input")
+    data, extra_info = load_json_single_dataset(validation_file, data_type=DatasetType.input)
     return data, extra_info
 
 
@@ -113,7 +113,7 @@ def test_input_data_custom_yaml():
 
 @pytest.mark.parametrize(("component", "attribute"), component_attributes(VALIDATION_EN, data_type=DatasetType.input))
 @pytest.mark.parametrize("input_data", LANGUAGES, indirect=True)
-def test_attributes(input_data: Tuple[SingleDataset, SingleDataset], component: str, attribute: str):
+def test_attributes(input_data: Tuple[SingleDataset, SingleDataset], component: ComponentType, attribute: str):
     """
     For each attribute, check if the actual values are consistent with the expected values
     """
@@ -132,7 +132,7 @@ def test_attributes(input_data: Tuple[SingleDataset, SingleDataset], component:
     (pytest.param(component, objects, id=component) for component, objects in component_objects(VALIDATION_EN)),
 )
 @pytest.mark.parametrize("extra_info", LANGUAGES, indirect=True)
-def test_extra_info(extra_info: Tuple[ExtraInfo, ExtraInfo], component: str, obj_ids: List[int]):
+def test_extra_info(extra_info: Tuple[ExtraInfo, ExtraInfo], component: ComponentType, obj_ids: List[int]):
     """
     For each object, check if the actual extra info is consistent with the expected extra info
     """
diff --git a/tests/validation/utils.py b/tests/validation/utils.py
index d25e248d..ca88053d 100644
--- a/tests/validation/utils.py
+++ b/tests/validation/utils.py
@@ -18,7 +18,7 @@
 from power_grid_model_io.data_types import ExtraInfo
 
 
-def component_objects(json_path: Path) -> Generator[Tuple[str, List[int]], None, None]:
+def component_objects(json_path: Path) -> Generator[Tuple[ComponentType, List[int]], None, None]:
     """
     Read the json file (only the components and their ids are are used, i.e. the component names and attribute name)
 
@@ -41,7 +41,7 @@ def component_objects(json_path: Path) -> Generator[Tuple[str, List[int]], None,
             yield component, obj_ids
 
 
-def component_attributes(json_path: Path, data_type: DatasetType) -> Generator[Tuple[str, str], None, None]:
+def component_attributes(json_path: Path, data_type: DatasetType) -> Generator[Tuple[ComponentType, str], None, None]:
     """
     Read the json file (only the structure is used, i.e. the component names and attribute name)
 
@@ -58,7 +58,9 @@ def component_attributes(json_path: Path, data_type: DatasetType) -> Generator[T
     # Loop over all components in the validation file (in alphabetical order)
     for component, objects in sorted(data.items(), key=lambda x: x[0]):
         # Create a set of attribute names for each object, then take the union of all those sets
-        pgm_attr = set(power_grid_meta_data[data_type][component].dtype.names)
+        component_meta = power_grid_meta_data[data_type][component]
+        assert component_meta.dtype.names is not None
+        pgm_attr = set(component_meta.dtype.names)
         obj_keys = set(objects.keys()) & pgm_attr
         unique_attributes = set(obj_keys)
 
@@ -85,7 +87,7 @@ def component_attributes_df(
             yield component, attribute
 
 
-def select_values(actual: SingleDataset, expected: SingleDataset, component: str, attribute: str):
+def select_values(actual: SingleDataset, expected: SingleDataset, component: ComponentType, attribute: str):
     """
 
     Creates two aligned series, for a single component attribute, containing the actual values and the (non-NaN
@@ -134,7 +136,7 @@ def select_values(actual: SingleDataset, expected: SingleDataset, component: str
     return actual_values, expected_values
 
 
-def extract_extra_info(data: SinglePythonDataset, data_type: str) -> ExtraInfo:
+def extract_extra_info(data: SinglePythonDataset, data_type: DatasetType) -> ExtraInfo:
     """
     Reads the dataset and collect all arguments that aren't pgm attributes
 
@@ -146,15 +148,18 @@ def extract_extra_info(data: SinglePythonDataset, data_type: str) -> ExtraInfo:
     """
     extra_info: ExtraInfo = {}
     for component, objects in data.items():
-        pgm_attr = set(power_grid_meta_data[data_type][component].dtype.names)
+        component_meta = power_grid_meta_data[data_type][component]
+        assert component_meta.dtype.names is not None
+        pgm_attr = set(component_meta.dtype.names)
         for obj in objects:
             obj_extra_info = {attr: val for attr, val in obj.items() if attr not in pgm_attr}
             if obj_extra_info:
+                assert isinstance(obj["id"], int)
                 extra_info[obj["id"]] = obj_extra_info
     return extra_info
 
 
-def load_json_single_dataset(file_path: Path, data_type: str) -> Tuple[SingleDataset, ExtraInfo]:
+def load_json_single_dataset(file_path: Path, data_type: DatasetType) -> Tuple[SingleDataset, ExtraInfo]:
     """
     Loads and parses a json file in the most basic way, without using power_grid_model_io functions.
 
@@ -193,7 +198,7 @@ def load_json_single_dataset(file_path: Path, data_type: str) -> Tuple[SingleDat
     return dataset, extra_info
 
 
-def compare_extra_info(actual: ExtraInfo, expected: ExtraInfo, component: str, obj_ids: List[int]):
+def compare_extra_info(actual: ExtraInfo, expected: ExtraInfo, component: ComponentType, obj_ids: List[int]):
     # We'll collect all errors, instead of terminating at the first error
     errors = []
 
diff --git a/uv.lock b/uv.lock
new file mode 100644
index 00000000..798c56e2
--- /dev/null
+++ b/uv.lock
@@ -0,0 +1,2569 @@
+version = 1
+revision = 3
+requires-python = ">=3.11"
+resolution-markers = [
+    "python_full_version >= '3.12'",
+    "python_full_version < '3.12'",
+]
+
+[[package]]
+name = "alabaster"
+version = "1.0.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/a6/f8/d9c74d0daf3f742840fd818d69cfae176fa332022fd44e3469487d5a9420/alabaster-1.0.0.tar.gz", hash = "sha256:c00dca57bca26fa62a6d7d0a9fcce65f3e026e9bfe33e9c538fd3fbb2144fd9e", size = 24210, upload-time = "2024-07-26T18:15:03.762Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/7e/b3/6b4067be973ae96ba0d615946e314c5ae35f9f993eca561b356540bb0c2b/alabaster-1.0.0-py3-none-any.whl", hash = "sha256:fc6786402dc3fcb2de3cabd5fe455a2db534b371124f1f21de8731783dec828b", size = 13929, upload-time = "2024-07-26T18:15:02.05Z" },
+]
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+name = "annotated-types"
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+]
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diff --git a/uv.lock.license b/uv.lock.license
new file mode 100644
index 00000000..76010591
--- /dev/null
+++ b/uv.lock.license
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