Merge v0.31.1-rc0 branch into master

.coveragerc

@@ -25,6 +25,9 @@ exclude_lines =
     # Ignore things that would have trivial tests
     def version
 
+    # Ignore overload stubs
+    @overload
+
 
 ignore_errors = True
 

.github/workflows/docs.yml

@@ -26,5 +26,5 @@ jobs:
     - uses: PennyLaneAI/sphinx-action@master
       with:
         docs-folder: "doc/"
-        pre-build-command: "apt install -y graphviz && pip3 install -r doc/requirements.txt && pip3 install . pip3 install openfermionpyscf && pip3 install dill zstd"
+        pre-build-command: "apt install -y graphviz && pip3 install -r doc/requirements.txt && pip3 install . pip3 install openfermionpyscf && pip3 install aiohttp fsspec h5py"
         build-command: "sphinx-build -b html . _build -W --keep-going"

.github/workflows/interface-unit-tests.yml

@@ -278,7 +278,7 @@ jobs:
       install_pennylane_lightning_master: false
       pytest_coverage_flags: ${{ inputs.pytest_coverage_flags }}
       pytest_markers: data
-      additional_pip_packages: zstd dill
+      additional_pip_packages: h5py
 
 
   device-tests:

.gitignore

@@ -24,3 +24,4 @@ benchmark/revisions/
 venv
 config.toml
 .envrc
+datasets/*

codecov.yml

@@ -1,5 +1,6 @@
 ignore:
   - "pennylane/devices/tests/*"
+  - "pennylane/data/base/_lazy_modules.py"
 
 codecov:
   notify:

doc/code/qml_data.rst

@@ -3,6 +3,5 @@ qml.data
 
 .. currentmodule:: pennylane.data
 
-.. automodapi:: pennylane.data
-    :no-heading:
-    :no-inherited-members:
+.. automodule:: pennylane.data
+

doc/introduction/data.rst

@@ -11,16 +11,12 @@ where the quantum dataset is a collection of `quantum data` obtained from variou
 
 .. note::
 
-    The packages ``zstd`` and ``dill`` are required to use the :mod:`~pennylane.data` module. 
-    These can be installed with ``pip install zstd dill``.
-
-.. warning::
+    The packages ``aiohttp``, ``fsspec``, and ``h5py`` are required to use the :mod:`~pennylane.data` module. 
+    These can be installed with:
+    
+    .. code-block:: console
 
-        PennyLane datasets use the ``dill`` module to compress, store, and read data. Since ``dill``
-        is built on the ``pickle`` module, we reproduce an important warning from the ``pickle``
-        module: it is possible to construct malicious pickle data which will execute arbitrary code
-        during unpickling. Never unpickle data that could have come from an untrusted source, or
-        that could have been tampered with.
+        pip install aiohttp fsspec h5py
 
 Loading Datasets in PennyLane
 -----------------------------
@@ -35,20 +31,22 @@ The :func:`~pennylane.data.load` function returns a ``list`` with the desired da
 
 >>> H2datasets = qml.data.load("qchem", molname="H2", basis="STO-3G", bondlength=1.1)
 >>> print(H2datasets)
-[<Dataset = description: qchem/H2/STO-3G/1.1, attributes: ['molecule', 'hamiltonian', ...]>]
+[<Dataset = molname: H2, basis: STO-3G, bondlength: 1.1, attributes: ['basis', 'basis_rot_groupings', ...]>]
 >>> H2data = H2datasets[0]
 
 We can load datasets for multiple parameter values by providing a list of values instead of a single value.
-To load all possible values, use the special keyword "full".
+To load all possible values, use the special value :const:`~pennylane.data.FULL` or the string ``"full"``:
 
 >>> H2datasets = qml.data.load("qchem", molname="H2", basis="full", bondlength=[0.5, 1.1])
 >>> print(H2datasets)
-[<Dataset = description: qchem/H2/6-31G/0.5, attributes: ['molecule', 'hamiltonian', ...]>,
- <Dataset = description: qchem/H2/6-31G/1.1, attributes: ['molecule', 'hamiltonian', ...]>,
- <Dataset = description: qchem/H2/STO-3G/0.5, attributes: ['molecule', 'hamiltonian', ...]>,
- <Dataset = description: qchem/H2/STO-3G/1.1, attributes: ['molecule', 'hamiltonian', ...]>]
-
-When we only want to download portions of a large dataset, we can specify the desired properties  (referred to as `attributes`).
+[<Dataset = molname: H2, basis: STO-3G, bondlength: 0.5, attributes: ['basis', 'basis_rot_groupings', ...]>,
+<Dataset = molname: H2, basis: STO-3G, bondlength: 1.1, attributes: ['basis', 'basis_rot_groupings', ...]>,
+<Dataset = molname: H2, basis: CC-PVDZ, bondlength: 0.5, attributes: ['basis', 'basis_rot_groupings', ...]>,
+<Dataset = molname: H2, basis: CC-PVDZ, bondlength: 1.1, attributes: ['basis', 'basis_rot_groupings', ...]>,
+<Dataset = molname: H2, basis: 6-31G, bondlength: 0.5, attributes: ['basis', 'basis_rot_groupings', ...]>,
+<Dataset = molname: H2, basis: 6-31G, bondlength: 1.1, attributes: ['basis', 'basis_rot_groupings', ...]>]
+
+When we only want to download portions of a large dataset, we can specify the desired properties  (referred to as 'attributes').
 For example, we can download or load only the molecule and energy of a dataset as follows:
 
 >>> part = qml.data.load("qchem", molname="H2", basis="STO-3G", bondlength=1.1, 
@@ -61,16 +59,20 @@ For example, we can download or load only the molecule and energy of a dataset a
 To determine what attributes are available for a type of dataset, we can use the function :func:`~pennylane.data.list_attributes`:
 
 >>> qml.data.list_attributes(data_name="qchem")
-["molecule",
-"hamiltonian",
-"sparse_hamiltonian",
-...
-"tapered_hamiltonian",
-"full"]
+['molname',
+ 'basis',
+ 'bondlength',
+ ...
+ 'vqe_params',
+ 'vqe_energy']
 
 .. note::
 
-    "full" is the default value for ``attributes``, and it means that all available attributes for the Dataset will be downloaded.
+    The default values for attributes are as follows:
+
+    - Molecules: ``basis`` is the smallest available basis, usually ``"STO-3G"``, and ``bondlength`` is the optimal bondlength for the molecule or an alternative if the optimal is not known.
+
+    - Spin systems: ``periodicity`` is ``"open"``, ``lattice`` is ``"chain"``, and ``layout`` is ``1x4`` for ``chain`` systems and ``2x2`` for ``rectangular`` systems.
 
 Using Datasets in PennyLane
 ---------------------------
@@ -139,9 +141,9 @@ array([-1.5, -0.5,  0.5,  1.5])
 We can then write this :class:`~pennylane.data.Dataset` to storage and read it as follows:
 
 
->>> dataset.write("./path/to/dataset.dat")
+>>> dataset.write("./path/to/dataset.h5")
 >>> read_dataset = qml.data.Dataset()
->>> read_dataset.read("./path/to/dataset.dat")
+>>> read_dataset.read("./path/to/dataset.h5")
 >>> read_dataset.data_name
 "Example"
 >>> read_dataset.hamiltonian
@@ -155,19 +157,6 @@ array([-1.5, -0.5,  0.5,  1.5])
 Quantum Datasets Functions and Classes
 --------------------------------------
 
-Classes
-^^^^^^^
-
-.. autosummary::
-    :nosignatures:
-
-    ~pennylane.data.Dataset
-
-:html:`</div>`
-
-Functions
-^^^^^^^^^
-
 :html:`<div class="summary-table">`
 
 .. autosummary::
@@ -177,5 +166,6 @@ Functions
     ~pennylane.data.list_attributes
     ~pennylane.data.load
     ~pennylane.data.load_interactive
+    ~pennylane.data.Dataset
 
 :html:`</div>`

doc/releases/changelog-0.31.0.md

@@ -1,6 +1,6 @@
 :orphan:
 
-# Release 0.31.0 (current release)
+# Release 0.31.0
 
 <h3>New features since last release</h3>
 

doc/releases/changelog-0.31.1.md

@@ -0,0 +1,25 @@
+:orphan:
+
+# Release 0.31.1 (current release)
+
+<h3>Improvements 🛠</h3>
+
+* `data.Dataset` now uses HDF5 instead of dill for serialization.
+  [(#4097)](https://github.com/PennyLaneAI/pennylane/pull/4097)
+
+* The `qchem` functions `primitive_norm` and `contracted_norm` are modified to
+  be compatible with higher versions of scipy.
+  [(#4321)](https://github.com/PennyLaneAI/pennylane/pull/4321)
+
+<h3>Bug Fixes 🐛</h3>
+
+* Dataset URLs are now properly escaped when fetching from S3.
+  [(#4412)](https://github.com/PennyLaneAI/pennylane/pull/4412)
+
+<h3>Contributors ✍️</h3>
+
+This release contains contributions from (in alphabetical order):
+
+Utkarsh Azad,
+Jack Brown,
+Soran Jahangiri

docker/pennylane.dockerfile

@@ -46,7 +46,7 @@ RUN pip install pytest pytest-cov pytest-mock flaky
 RUN pip install -i https://test.pypi.org/simple/ pennylane-lightning --pre --upgrade
 # hotfix, remove when pyscf 2.1 is released (currently no wheel for python3.10)
 RUN pip install openfermionpyscf || true
-RUN pip install dill zstd || true
+RUN pip install hdf5 fsspec aiohttp || true
 RUN make test && make coverage
 
 # create Second small build.

pennylane/__init__.py

@@ -116,13 +116,14 @@
 from pennylane.vqe import ExpvalCost
 from pennylane.debugging import snapshots
 from pennylane.shadows import ClassicalShadow
-import pennylane.data
 import pennylane.pulse
 
 import pennylane.gradients  # pylint:disable=wrong-import-order
 import pennylane.qinfo  # pylint:disable=wrong-import-order
 from pennylane.interfaces import execute  # pylint:disable=wrong-import-order
 
+import pennylane.data
+
 # Look for an existing configuration file
 default_config = Configuration("config.toml")