chore: removed blacken-docs

.pre-commit-config.yaml

@@ -3,12 +3,6 @@ ci:
   autofix_commit_msg: "style: pre-commit fixes"
 
 repos:
-  - repo: https://github.com/adamchainz/blacken-docs
-    rev: "1.16.0"
-    hooks:
-      - id: blacken-docs
-        additional_dependencies: [black==23.*]
-
   - repo: https://github.com/pre-commit/pre-commit-hooks
     rev: "v4.5.0"
     hooks:

README.md

@@ -1,9 +1,10 @@
-# ragged
+# Ragged
 
 [![Actions Status][actions-badge]][actions-link]
 [![PyPI version][pypi-version]][pypi-link]
 [![PyPI platforms][pypi-platforms]][pypi-link]
 [![GitHub Discussion][github-discussions-badge]][github-discussions-link]
+
 <!-- [![Documentation Status][rtd-badge]][rtd-link] -->
 <!-- [![Conda-Forge][conda-badge]][conda-link] -->
 
@@ -25,9 +26,12 @@
 
 ## Introduction
 
-**Ragged** is a library for manipulating ragged arrays as though they were **NumPy** or **CuPy** arrays, following the [Array API specification](https://data-apis.org/array-api/latest/API_specification).
+**Ragged** is a library for manipulating ragged arrays as though they were
+**NumPy** or **CuPy** arrays, following the
+[Array API specification](https://data-apis.org/array-api/latest/API_specification).
 
-For example, this is a [ragged/jagged array](https://en.wikipedia.org/wiki/Jagged_array):
+For example, this is a
+[ragged/jagged array](https://en.wikipedia.org/wiki/Jagged_array):
 
 ```python
 >>> import ragged
@@ -48,20 +52,28 @@ The values are all floating-point numbers, so `a.dtype` is `float64`,
 dtype('float64')
 ```
 
-but `a.shape` has non-integer dimensions to account for the fact that some of its list lengths are non-uniform:
+but `a.shape` has non-integer dimensions to account for the fact that some of
+its list lengths are non-uniform:
 
 ```python
 >>> a.shape
 (4, None, None)
 ```
 
-In general, a `ragged.array` can have any mixture of regular and irregular dimensions, though `shape[0]` (the length) is always an integer. This convention follows the **Array API**'s specification for [array.shape](https://data-apis.org/array-api/latest/API_specification/generated/array_api.array.shape.html#array_api.array.shape), which must be a tuple of `int` or `None`:
+In general, a `ragged.array` can have any mixture of regular and irregular
+dimensions, though `shape[0]` (the length) is always an integer. This convention
+follows the **Array API**'s specification for
+[array.shape](https://data-apis.org/array-api/latest/API_specification/generated/array_api.array.shape.html#array_api.array.shape),
+which must be a tuple of `int` or `None`:
 
 ```python
 array.shape: Tuple[Optional[int], ...]
 ```
 
-(Our use of `None` to indicate a dimension without a single-valued size differs from the **Array API**'s intention of specifying dimensions of _unknown_ size, but it follows the technical specification. **Array API**-consuming libraries can try using **Ragged** to find out if they are ragged-ready.)
+(Our use of `None` to indicate a dimension without a single-valued size differs
+from the **Array API**'s intention of specifying dimensions of _unknown_ size,
+but it follows the technical specification. **Array API**-consuming libraries
+can try using **Ragged** to find out if they are ragged-ready.)
 
 All of the normal elementwise and reducing functions apply, as well as slices:
 
@@ -100,22 +112,42 @@ ragged.array([
 ])
 ```
 
-All of the methods, attributes, and functions in the **Array API** will be implemented for **Ragged**, as well as conveniences that are not required by the **Array API**. See [open issues marked "todo"](https://github.com/jpivarski/ragged/issues?q=is%3Aissue+is%3Aopen+label%3Atodo) for **Array API** functions that still need to be written (out of 120 in total).
+All of the methods, attributes, and functions in the **Array API** will be
+implemented for **Ragged**, as well as conveniences that are not required by the
+**Array API**. See
+[open issues marked "todo"](https://github.com/jpivarski/ragged/issues?q=is%3Aissue+is%3Aopen+label%3Atodo)
+for **Array API** functions that still need to be written (out of 120 in total).
 
-**Ragged** has two `device` values, `"cpu"` (backed by **NumPy**) and `"cuda"` (backed by **CuPy**). Eventually, all operations will be identical for CPU and GPU.
+**Ragged** has two `device` values, `"cpu"` (backed by **NumPy**) and `"cuda"`
+(backed by **CuPy**). Eventually, all operations will be identical for CPU and
+GPU.
 
 ## Implementation
 
-**Ragged** is implemented using **Awkward Array** ([code](https://github.com/scikit-hep/awkward), [docs](https://awkward-array.org/)), which is an array library for arbitrary tree-like (JSON-like) data. Because of its generality, **Awkward Array** cannot follow the **Array API**—in fact, its array objects can't have separate `dtype` and `shape` attributes (the array `type` can't be factorized). **Ragged** is therefore
+**Ragged** is implemented using **Awkward Array**
+([code](https://github.com/scikit-hep/awkward),
+[docs](https://awkward-array.org/)), which is an array library for arbitrary
+tree-like (JSON-like) data. Because of its generality, **Awkward Array** cannot
+follow the **Array API**—in fact, its array objects can't have separate `dtype`
+and `shape` attributes (the array `type` can't be factorized). **Ragged** is
+therefore
 
-- a _specialization_ of **Awkward Array** for numeric data in fixed-length and variable-length lists, and
-- a _formalization_ to adhere to the **Array API** and its fully typed protocols.
+- a _specialization_ of **Awkward Array** for numeric data in fixed-length and
+  variable-length lists, and
+- a _formalization_ to adhere to the **Array API** and its fully typed
+  protocols.
 
-See [Why does this library exist?](https://github.com/jpivarski/ragged/discussions/6) under the [Discussions](https://github.com/jpivarski/ragged/discussions) tab for more details.
+See
+[Why does this library exist?](https://github.com/jpivarski/ragged/discussions/6)
+under the [Discussions](https://github.com/jpivarski/ragged/discussions) tab for
+more details.
 
-**Ragged** is a thin wrapper around **Awkward Array**, restricting it to ragged arrays and transforming its function arguments and return values to fit the specification.
+**Ragged** is a thin wrapper around **Awkward Array**, restricting it to ragged
+arrays and transforming its function arguments and return values to fit the
+specification.
 
-**Awkward Array**, in turn, is time- and memory-efficient, ready for big datasets. Consider the following:
+**Awkward Array**, in turn, is time- and memory-efficient, ready for big
+datasets. Consider the following:
 
 ```python
 import gc      # control for garbage collection
@@ -184,7 +216,11 @@ time: 4.180 sec
 time: 0.082 sec
 ```
 
-**Awkward Array** and **Ragged** are generally smaller and faster than their Python equivalents for the same reasons that **NumPy** is smaller and faster than Python lists. See **Awkward Array** [papers and presentations](https://awkward-array.org/doc/main/getting-started/papers-and-talks.html) for more.
+**Awkward Array** and **Ragged** are generally smaller and faster than their
+Python equivalents for the same reasons that **NumPy** is smaller and faster
+than Python lists. See **Awkward Array**
+[papers and presentations](https://awkward-array.org/doc/main/getting-started/papers-and-talks.html)
+for more.
 
 ## Installation
 
@@ -196,8 +232,13 @@ pip install ragged
 
 and will someday be on conda-forge.
 
-`ragged` is a pure-Python library that only depends on `awkward` (which, in turn, only depends on `numpy` and a compiled extension). In principle (i.e. eventually), `ragged` can be loaded into Pyodide and JupyterLite.
+`ragged` is a pure-Python library that only depends on `awkward` (which, in
+turn, only depends on `numpy` and a compiled extension). In principle (i.e.
+eventually), `ragged` can be loaded into Pyodide and JupyterLite.
 
 # Acknowledgements
 
-Support for this work was provided by NSF grant [OAC-2103945](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2103945) and the gracious help of [Awkward Array contributors](https://github.com/scikit-hep/awkward?tab=readme-ov-file#acknowledgements).
+Support for this work was provided by NSF grant
+[OAC-2103945](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2103945) and the
+gracious help of
+[Awkward Array contributors](https://github.com/scikit-hep/awkward?tab=readme-ov-file#acknowledgements).