Merge pull request #964 from PowerGridModel/feature/minor-format-docs2

Solve some markdownlint issues

Author: mgovers

.markdownlint.yaml

@@ -26,24 +26,3 @@ MD013: false
 
 # MD024/no-duplicate-heading : Multiple headings with the same content : https://github.com/DavidAnson/markdownlint/blob/v0.37.4/doc/md024.md
 MD024: false
-
-# MD033/no-inline-html : Inline HTML : https://github.com/DavidAnson/markdownlint/blob/v0.32.1/doc/md033.md
-MD033: false
-
-# MD040/fenced-code-language : Fenced code blocks should have a language specified : https://github.com/DavidAnson/markdownlint/blob/v0.37.4/doc/md040.md
-MD040: false
-
-# MD041/first-line-heading/first-line-h1 : First line in a file should be a top-level heading : https://github.com/DavidAnson/markdownlint/blob/v0.37.4/doc/md041.md
-MD041: false
-
-# MD042/no-empty-links : No empty links : https://github.com/DavidAnson/markdownlint/blob/v0.32.1/doc/md042.md
-MD042: false
-
-# MD045/no-alt-text : Images should have alternate text (alt text) : https://github.com/DavidAnson/markdownlint/blob/v0.32.1/doc/md045.md
-MD045: false
-
-# MD051/link-fragments : Link fragments should be valid : https://github.com/DavidAnson/markdownlint/blob/v0.37.4/doc/md051.md
-MD051: false
-
-# MD056/table-column-count : Table column counts should match : https://github.com/DavidAnson/markdownlint/blob/v0.37.4/doc/md056.md
-MD056: false

.vscode/extensions.json

@@ -24,6 +24,7 @@
 		"matepek.vscode-catch2-test-adapter",
 		"cschlosser.doxdocgen",
 		"fredericbonnet.cmake-test-adapter",
-		"sonarsource.sonarlint-vscode"
+		"sonarsource.sonarlint-vscode",
+		"davidanson.vscode-markdownlint"
 	]
 }

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.svg?no-cache)](https://badge.fury.io/py/power-grid-model)
+[![PyPI version](https://badge.fury.io/py/power-grid-model.svg?no-cache)](https://badge.fury.io/py/power-grid-model) <!-- markdownlint-disable-line first-line-h1 -->
 [![Anaconda-Server Badge](https://anaconda.org/conda-forge/power-grid-model/badges/version.svg?no-cache)](https://anaconda.org/conda-forge/power-grid-model)
 [![License: MPL2.0](https://img.shields.io/badge/License-MPL2.0-informational.svg)](https://github.com/PowerGridModel/power-grid-model/blob/main/LICENSE)
 [![Downloads](https://static.pepy.tech/badge/power-grid-model)](https://pepy.tech/project/power-grid-model)
@@ -24,7 +24,7 @@ SPDX-License-Identifier: MPL-2.0
 
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.8054429.svg)](https://zenodo.org/record/8054429)
 
-[![](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 -->
 
 # Power Grid Model
 
@@ -50,15 +50,15 @@ Want to be updated on the latest news and releases? Subscribe to the Power Grid
 
 You can directly install the package from PyPI.
 
-```
+```sh
 pip install power-grid-model
 ```
 
 ### 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
 ```
 

docs/advanced_documentation/native-data-interface.md

@@ -115,12 +115,12 @@ The pointers are passed into C++ code so that the C++ program can write results
 
 The basic data types used in the interface between C++ and Python are shown in the table below.
 
-| C++ type     | `numpy.dtype` | null value                                          |  usage   |
-| ---          | ---           | ---                                                 | ---      |
-| `int32_t`    | `'i4'`        | - 2^31                                              | ids of physical components |
-| `int8_t`     | `'i1'`        | - 2^7                                               | enumeration types, boolean types, and small integers (e.g. tap position of transformer) |
-| `double`     | `'f8'`        | NaN ([IEEE 754](https://en.wikipedia.org/wiki/NaN)) | physical quantities (e.g. voltage) |
-| `double[3]`  | `'(3, )f8'`   | NaN ([IEEE 754](https://en.wikipedia.org/wiki/NaN)) | three-phase asymmetric physical quantities (e.g. voltage) |
+| C++ type    | `numpy.dtype` | null value                                          | usage                                                                                   |
+| ----------- | ------------- | --------------------------------------------------- | --------------------------------------------------------------------------------------- |
+| `int32_t`   | `'i4'`        | - 2^31                                              | ids of physical components                                                              |
+| `int8_t`    | `'i1'`        | - 2^7                                               | enumeration types, boolean types, and small integers (e.g. tap position of transformer) |
+| `double`    | `'f8'`        | NaN ([IEEE 754](https://en.wikipedia.org/wiki/NaN)) | physical quantities (e.g. voltage)                                                      |
+| `double[3]` | `'(3, )f8'`   | NaN ([IEEE 754](https://en.wikipedia.org/wiki/NaN)) | three-phase asymmetric physical quantities (e.g. voltage)                               |
 
 *The [endianness](https://en.wikipedia.org/wiki/Endianness)
 of C++ and Python side is also matched. For `x86-64` platform the little endian is used, so that

docs/quickstart.md

@@ -10,7 +10,7 @@ In this quick start a simple 10kV network as below is calculated.
 A line connects two nodes. One node has a source. The other node has a symmetric load.
 The full code for this section is provided in {{ "[quick_example.py]({}/scripts/quick_example.py)".format(gh_link_head_blob) }}.
 
-```
+```txt
 node_1 ---line_3--- node_2
  |                    |
 source_5            sym_load_4
@@ -134,7 +134,7 @@ print(pd.DataFrame(result['node']))
 
 The result data can then be viewed in tabular forms.
 
-```
+```txt
 Node Input
    id  u_rated
 0   1  10500.0