diff --git a/.github/workflows/testing.yml b/.github/workflows/testing.yml index e56f87fbf..f71000bae 100644 --- a/.github/workflows/testing.yml +++ b/.github/workflows/testing.yml @@ -21,19 +21,19 @@ jobs: strategy: matrix: os: ["ubuntu-latest"] - python-version: ["3.10", "3.11"] + python-version: ["3.11", "3.12"] steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v6 with: fetch-depth: 0 - name: Set up Python - uses: actions/setup-python@v4 + uses: actions/setup-python@v6 with: python-version: ${{ matrix.python-version }} cache: "pip" - name: Install dependencies run: | - python${{ matrix.python-version }} -m pip install --upgrade "pip<25.3" build pip-tools + python${{ matrix.python-version }} -m pip install --upgrade "pip<25.3" build pip-tools pre-commit python${{ matrix.python-version }} -m piptools compile --extra dev -o requirements.txt mpcontribs-client/setup.py mpcontribs-api/setup.py python${{ matrix.python-version }} -m pip install -r requirements.txt cd mpcontribs-api && python${{ matrix.python-version }} -m pip install --no-deps . @@ -47,6 +47,13 @@ jobs: run: | $env:SSL_CERT_FILE=$(python${{ matrix.python-version }} -m certifi) echo "SSL_CERT_FILE=$env:SSL_CERT_FILE" >> $GITHUB_ENV + + - name: Run pre-commit + run: | + python${{ matrix.python-version }} -m pip install pre-commit + pre-commit install + pre-commit run --all-files + - name: Test Client and build env: MPCONTRIBS_API_KEY: ${{ secrets.MPCONTRIBS_API_KEY }} @@ -59,6 +66,16 @@ jobs: python${{ matrix.python-version }} -m pytest -v -s --cov=mpcontribs/client --cov-report=term-missing --cov-report=xml --ignore=bravado python${{ matrix.python-version }} -m build --outdir ../dist + - name: Install lux and test with pytest + run: | + git lfs install + git lfs pull + cd mpcontribs-lux + python${{ matrix.python-version }} -m pip install -r requirements/requirements-${{ matrix.os }}_py${{ matrix.python-version }}_extras.txt + python${{ matrix.python-version }} -m pip install -e . + python${{ matrix.python-version }} -m pytest -n auto -x --cov=mpcontribs/lux --cov-report=xml + + auto-gen-release: needs: - test diff --git a/.gitignore b/.gitignore index 577f054bf..af8e9312a 100644 --- a/.gitignore +++ b/.gitignore @@ -31,3 +31,4 @@ mpcontribs-portal/mpcontribs/portal/templates/notebooks coverage.xml mpcontribs-api/supervisord.conf mpcontribs-portal/supervisord.conf +**/.DS_Store diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 33dcde101..3f37230e8 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -2,8 +2,12 @@ exclude: | (?x)( ^mpcontribs-portal/mpcontribs/users/| ^binder/| + ^mpcontribs-api/| ^mpcontribs-ingester/| - ^mpcontribs-api/mpcontribs/api/redox_thermo_csp/ + ^mpcontribs-io/| + ^mpcontribs-kernel-gateway/| + ^mpcontribs-portal/| + ^mpcontribs-serverless/ ) repos: @@ -14,7 +18,6 @@ repos: - id: trailing-whitespace - id: check-added-large-files - id: check-merge-conflict - - id: fix-encoding-pragma - id: forbid-new-submodules - id: requirements-txt-fixer @@ -35,3 +38,12 @@ repos: rev: 25.9.0 hooks: - id: black + + - repo: https://github.com/kynan/nbstripout + rev: 0.8.1 + hooks: + - id: nbstripout + args: + - --drop-empty-cells + - --strip-init-cells + - --extra-keys=metadata.kernelspec diff --git a/mpcontribs-client/README.md b/mpcontribs-client/README.md index 302497c00..82f6e28f9 100644 --- a/mpcontribs-client/README.md +++ b/mpcontribs-client/README.md @@ -33,7 +33,7 @@ Set the environment variable `SSL_CERT_FILE` to `$(python -m certifi)`. OverflowError: timeout value is too large ``` -Install the bravado fork ([PR](https://github.com/Yelp/bravado/pull/472)) manually via +Install the bravado fork ([PR](https://github.com/Yelp/bravado/pull/472)) manually via ``` pip install "bravado[fido] @ git+https://github.com/tschaume/bravado@9ce06f2df7118e16af4a3d3fdc21ccfeedc5cd50#egg=bravado-11.0.3" ``` diff --git a/mpcontribs-client/requirements/deployment.txt b/mpcontribs-client/requirements/deployment.txt index 555398ee6..c0806d08c 100644 --- a/mpcontribs-client/requirements/deployment.txt +++ b/mpcontribs-client/requirements/deployment.txt @@ -71,12 +71,12 @@ json2html==1.3.0 jsonpointer==3.0.0 # via jsonschema jsonref==1.1.0 - # via bravado-core -jsonschema[format-nongpl]==4.25.1 # via # bravado-core # swagger-spec-validator jsonschema-specifications==2025.9.1 + # via bravado-core +jsonschema[format-nongpl]==4.25.1 # via jsonschema kiwisolver==1.4.9 # via matplotlib diff --git a/mpcontribs-client/requirements/ubuntu-latest_py3.11.txt b/mpcontribs-client/requirements/ubuntu-latest_py3.11.txt index 9794713e4..9d4ce22b3 100644 --- a/mpcontribs-client/requirements/ubuntu-latest_py3.11.txt +++ b/mpcontribs-client/requirements/ubuntu-latest_py3.11.txt @@ -71,12 +71,12 @@ json2html==1.3.0 jsonpointer==3.0.0 # via jsonschema jsonref==1.1.0 - # via bravado-core -jsonschema[format-nongpl]==4.25.1 # via # bravado-core # swagger-spec-validator jsonschema-specifications==2025.9.1 + # via bravado-core +jsonschema[format-nongpl]==4.25.1 # via jsonschema kiwisolver==1.4.9 # via matplotlib diff --git a/mpcontribs-client/requirements/ubuntu-latest_py3.11_extras.txt b/mpcontribs-client/requirements/ubuntu-latest_py3.11_extras.txt index d02c97a8d..4385bb84c 100644 --- a/mpcontribs-client/requirements/ubuntu-latest_py3.11_extras.txt +++ b/mpcontribs-client/requirements/ubuntu-latest_py3.11_extras.txt @@ -79,12 +79,12 @@ json2html==1.3.0 jsonpointer==3.0.0 # via jsonschema jsonref==1.1.0 - # via bravado-core -jsonschema[format-nongpl]==4.25.1 # via # bravado-core # swagger-spec-validator jsonschema-specifications==2025.9.1 + # via bravado-core +jsonschema[format-nongpl]==4.25.1 # via jsonschema kiwisolver==1.4.9 # via matplotlib diff --git a/mpcontribs-client/requirements/ubuntu-latest_py3.12.txt b/mpcontribs-client/requirements/ubuntu-latest_py3.12.txt index b007959ac..4f2310fd2 100644 --- a/mpcontribs-client/requirements/ubuntu-latest_py3.12.txt +++ b/mpcontribs-client/requirements/ubuntu-latest_py3.12.txt @@ -71,12 +71,12 @@ json2html==1.3.0 jsonpointer==3.0.0 # via jsonschema jsonref==1.1.0 - # via bravado-core -jsonschema[format-nongpl]==4.25.1 # via # bravado-core # swagger-spec-validator jsonschema-specifications==2025.9.1 + # via bravado-core +jsonschema[format-nongpl]==4.25.1 # via jsonschema kiwisolver==1.4.9 # via matplotlib diff --git a/mpcontribs-client/requirements/ubuntu-latest_py3.12_extras.txt b/mpcontribs-client/requirements/ubuntu-latest_py3.12_extras.txt index 71ec49437..6a3164248 100644 --- a/mpcontribs-client/requirements/ubuntu-latest_py3.12_extras.txt +++ b/mpcontribs-client/requirements/ubuntu-latest_py3.12_extras.txt @@ -79,12 +79,12 @@ json2html==1.3.0 jsonpointer==3.0.0 # via jsonschema jsonref==1.1.0 - # via bravado-core -jsonschema[format-nongpl]==4.25.1 # via # bravado-core # swagger-spec-validator jsonschema-specifications==2025.9.1 + # via bravado-core +jsonschema[format-nongpl]==4.25.1 # via jsonschema kiwisolver==1.4.9 # via matplotlib diff --git a/mpcontribs-client/tests/conftest.py b/mpcontribs-client/tests/conftest.py index 7c3fbd91d..f0a9272d0 100644 --- a/mpcontribs-client/tests/conftest.py +++ b/mpcontribs-client/tests/conftest.py @@ -6,7 +6,7 @@ except ImportError: create_app = None -os.environ['MPCONTRIBS_DB_NAME'] = 'mpcontribs-test' +os.environ["MPCONTRIBS_DB_NAME"] = "mpcontribs-test" @pytest.fixture() diff --git a/mpcontribs-lux/.python-version b/mpcontribs-lux/.python-version new file mode 100644 index 000000000..e4fba2183 --- /dev/null +++ b/mpcontribs-lux/.python-version @@ -0,0 +1 @@ +3.12 diff --git a/mpcontribs-lux/README.md b/mpcontribs-lux/README.md new file mode 100644 index 000000000..b64b47345 --- /dev/null +++ b/mpcontribs-lux/README.md @@ -0,0 +1,44 @@ +## MPContribs LUX + +Ego sum lux datorum. + +MPContribs-lux is a package which sheds light on data stored on the [Materials Project's AWS S3 MPContribs bucket](https://materialsproject-contribs.s3.amazonaws.com/index.html#) by providing annotated schemas and optionally analysis tools to better explore user-submitted data. + +Adding a schema to this database is a pre-requisite for obtaining permission/IAM credentials for uploading data to MP's MPContribs Bucket. +Once a staff member from MP reviews and approves your data schema, your receive IAM role will be granted/updated (as appropriate). + +What if I don't want my schemas / data made public yet? + +To expedite the process of review, follow [these instructions](https://docs.github.com/en/repositories/creating-and-managing-repositories/duplicating-a-repository) to make a private copy (not a fork, which cannot be private) of the `MPContribs` repo. +Suppose you name your new repository `PrivateMPContribs` and your username is ``, you would run these commands from a terminal: + +```console +git clone --bare https://github.com/materialsproject/MPContribs.git +cd MPContribs +git push --mirror https://github.com//PrivateMPContribs.git +cd .. +rm -rf MPContribs +``` + +Then add your schemas to the private repo `PrivateMPContribs` and invite the maintainers of `MPContribs` to view it (you don't need to give us edit access). +We will then review your schemas. +When you're ready to make your data public, you will also have to make a public PR with your new schemas. + +But my CSV/JSON/YAML/etc. file isn't complicated. Why do I need to upload a schema? + +Schemas are important for ensuring accessibility, interoperability, and reproducibility, and for ensuring that you are fully aware of possible errors in your dataset. + +If you are not comfortable mimicking the example `pydantic` schemas in `mpcontribs.lux.projects.examples`, you can either use the schema autogeneration features in `mpcontribs.lux.autogen`: + +```py +from mpcontribs.lux.autogen import SchemaGenerator + +schema_gen = SchemaGenerator(file_name = "/path/to/some/csv/or/json/file") +pydantic_model = schema_gen.pydantic_schema +print(pydantic_model.schema()) +``` + +...or reach out to the maintainers! + +The test suite for MPContribs-lux will automatically test your `pydantic` models for arrow/parquet compatibility using the [arrowize](https://github.com/materialsproject/emmet/blob/74194bbf8c7b32ce15141bb1c9ee0527a0fc6c45/emmet-core/emmet/core/arrow.py#L40) utility from `emmet-core` (MP's production data model and data pipeline repository). +Schemas submitted to MPContribs-lux do not necessarily need to be parquet/arrow compatlible, the `@arrow_incompatible` decorator from `emmet-core`'s [utils](https://github.com/materialsproject/emmet/blob/74194bbf8c7b32ce15141bb1c9ee0527a0fc6c45/emmet-core/emmet/core/utils.py#L104) module can be used to mark a `pydantic` model to be skipped during arrow compatibility testing. diff --git a/mpcontribs-lux/examples/1-mpcontribs_upload.ipynb b/mpcontribs-lux/examples/1-mpcontribs_upload.ipynb new file mode 100644 index 000000000..7d1d4b211 --- /dev/null +++ b/mpcontribs-lux/examples/1-mpcontribs_upload.ipynb @@ -0,0 +1,494 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Requirements:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "!pip install mp_api>=0.45.13 mpcontribs-client>=5.10.4 pandas>=2.3.0" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Programatically uploading data to MPContribs using the python client\n", + "\n", + "This guide will walk you through uploading a dataset of experimentally-determined properties of a handful of cubic solids from the following paper:\n", + "\n", + "> F. Tran, J. Stelzl, and P. Blaha, J. Chem. Phys., vol. 144, p. 204120, 2016, DOI: [10.1063/1.4948636](https://doi.org/10.1063/1.4948636)\n", + "\n", + "(This data has been parsed manually and is redistributed without claims of copyright.)\n", + "\n", + "To the MPContribs project [`test_solid_data`](https://next-gen.materialsproject.org/contribs/projects/test_solid_data).\n", + "\n", + "Let's start by inspecting the data. It is semi-structured JSON, with a `data` field and `metadata` field:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import gzip\n", + "import json\n", + "\n", + "with gzip.open(\"cubic_solid_expt_data.json.gz\", \"rt\") as f:\n", + " user_data = json.load(f)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `data` subset of `user_data` contains a list of entries, each with the following fields:\n", + "- `formula` (str) : The chemical formula of the entry\n", + "- `a0` (float) : The cubic lattice constant of the structure in the entry\n", + "- `b0` (float) : The bulk modulus of the solid\n", + "- `e0` (float) : The cohesive energy of the solid\n", + "- `cif` (str) : A crystallographic information file (CIF) representation of the structure in the entry\n", + "\n", + "Fortunately for us, the `data` field is structured to be readable with `pandas`. While you don't strictly need to use `pandas` to upload data to MPContribs, it is well-suited to its columnar format" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "\n", + "pd.DataFrame(user_data[\"data\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `metadata` subset contains `citation` information, the `units` of the fields in `data`, and their `long_names` / descriptions. These are the basic metadata/provenance information required by MPContribs. Note that a preprint is also an acceptable citation." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for k, v in user_data[\"metadata\"].items():\n", + " print(k, v)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Column names in MPContribs cannot contain special characters beyond alphanumeric ones. The `snake_to_camel` function is useful if you have snake-case (e.g., `some_data_to_upload`) column names (will be converted to `someDataToUpload`).\n", + "\n", + "Let's start by creating the project. If your `MP_API_KEY` is set as an environment variable, you don't need to call `MPRester` with any kwargs. Otherwise, pass an `api_key = ` kwarg to it" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from mp_api.client import MPRester\n", + "from mpcontribs.client import Client as ContribsClient\n", + "\n", + "\n", + "def snake_to_camel(in_str: str) -> str:\n", + " return \"\".join(\n", + " (s[0].upper() if i > 0 else s[0]) + s[1:]\n", + " for i, s in enumerate(in_str.lower().split(\"_\"))\n", + " )\n", + "\n", + "\n", + "PROJECT_NAME = \"test_solid_data\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "with (\n", + " MPRester(\n", + " # api_key= # use as needed, snake_case `api_key`\n", + " ) as mpr\n", + "):\n", + " mpr.contribs.create_project(\n", + " name=PROJECT_NAME,\n", + " title=\"Example MPContribs entry\", # can be anything with standard characters\n", + " authors=\", \".join(user_data[\"metadata\"][\"citation\"][\"authors\"]),\n", + " description=( # again can be anything, could be a paper/preprint abstract\n", + " \"Experimental data on cubic solid state geometries, elastic, and energetic properties with zero-point corrections.\"\n", + " ),\n", + " url=user_data[\"metadata\"][\"citation\"][\"url\"],\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "client = ContribsClient(\n", + " project=PROJECT_NAME,\n", + " apikey=MPRester().api_key, # Note that this is one word, not snake case as before\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Suppose now that you want to update the project metadata, for example, adding more relevant links to the data / code used to process it. Those simple updates are handled with `ContribsClient.update_project`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "client.update_project(\n", + " {\n", + " \"references\": [\n", + " {\"label\": \"doi\", \"url\": user_data[\"metadata\"][\"citation\"][\"url\"]},\n", + " {\n", + " \"label\": \"github\",\n", + " \"url\": \"https://github.com/esoteric-ephemera/mpcontribs-example/\",\n", + " },\n", + " ]\n", + " }\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we can actually start annotating and uploading data! The first step is specifying the columns and their long decriptions (`metadata`). Note that the MPContribs client can interpret units/dimensions from [`pint`](https://github.com/hgrecco/pint). Most common scientific units are handled there, including fundamental constants like the electron charge `e`, or angstrom.\n", + "\n", + "When specifying units, any values which are text only should be given units of `None` type. Any numeric or boolean data which is dimensionless, e.g., the number of sites in a structure (`num_sites` below), should be given a unit of `str()`. All other numeric data can use units as needed.\n", + "\n", + "Also note that fields can be nested using dot notation. The `lattice.a`, `lattice.b`, etc. examples below will nest an `a` and `b` field under a lattice super-heading, as will the `symmetry.number` and `symmetry.symbol` under a `symmetry` super-heading." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "_columns_with_units = {\n", + " **user_data[\"metadata\"][\"units\"],\n", + " **{f\"lattice.{k}\": \"angstrom\" for k in (\"a\", \"b\", \"c\")},\n", + " **{f\"lattice.{k}\": \"degree\" for k in (\"alpha\", \"beta\", \"gamma\")},\n", + " \"num_sites\": None,\n", + " \"symmetry.number\": None, # Numeric or boolean values which are dimensionless or unitless require `None` units\n", + " \"symmetry.symbol\": \"\", # String data requires emptry str() as units\n", + "}\n", + "\n", + "columns_with_units = {snake_to_camel(k): v for k, v in _columns_with_units.items()}\n", + "\n", + "column_descriptions = {\n", + " snake_to_camel(k): v\n", + " for k, v in {\n", + " **{\n", + " k: f\"{v}, in {user_data['metadata']['units'][k]}\"\n", + " for k, v in user_data[\"metadata\"][\"long_names\"].items()\n", + " },\n", + " **{\n", + " f\"lattice.{k}\": f\"The lattice {k} parameter in angstrom\"\n", + " for k in (\"a\", \"b\", \"c\")\n", + " },\n", + " **{\n", + " f\"lattice.{k}\": f\"The lattice {k} angle in angstrom\"\n", + " for k in (\"alpha\", \"beta\", \"gamma\")\n", + " },\n", + " \"num_sites\": \"The number of sites in the primitive cell\",\n", + " \"symmetry.number\": \"The international space group number\",\n", + " \"symmetry.symbol\": \"The international space group symbol\",\n", + " }.items()\n", + "}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "All contribs entries require an identifier field, which can be arbitrary (UUID, integer, etc.) and non-unique. In this example, we will use the Materials Project ID (MPID) of a corresponding matched structure. Using MPIDs will actually permit dynamic linking of data between MPContribs and the core MP data. The code below just sets up the columns.\n", + "\n", + "
\n", + "\n", + "The links to MPIDs were pre-built as follows:\n", + "\n", + "\n", + "```python\n", + "from mp_api.client import MPRester\n", + "from pymatgen.core import Structure\n", + "from emmet.core.mpid import AlphaID\n", + "from pymatgen.analysis.structure_matcher import StructureMatcher\n", + "import gzip\n", + "import json\n", + "\n", + "with gzip.open(\"cubic_solid_expt_data.json.gz\",\"rt\") as f:\n", + " user_data = json.load(f)\n", + " \n", + "matcher = StructureMatcher()\n", + "with MPRester() as mpr:\n", + " for i, entry in enumerate(user_data[\"data\"]):\n", + " s = Structure.from_str(entry[\"cif\"],fmt=\"cif\")\n", + " mp_summary = mpr.materials.summary.search(formula=s.composition.reduced_formula)\n", + " for doc in mp_summary:\n", + " if matcher.fit(doc.structure,s):\n", + " user_data[\"data\"][i][\"material_id\"] = AlphaID(doc.material_id).formatted\n", + " break\n", + "\n", + "with gzip.open(\"cubic_solid_expt_data.json.gz\",\"wt\") as f:\n", + " json.dump(user_data, f)\n", + "\n", + "```\n", + "\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "client.init_columns(columns_with_units)\n", + "client.update_project({\"other\": column_descriptions})" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's first simulate running some basic analysis on our data as a `pandas.DataFrame`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from pymatgen.core import Structure\n", + "import pandas as pd\n", + "\n", + "data_upload = pd.DataFrame(user_data[\"data\"])\n", + "data_upload[\"structure\"] = data_upload.cif.apply(\n", + " lambda x: Structure.from_str(x, fmt=\"cif\").to_primitive()\n", + ")\n", + "\n", + "for k in (\"a\", \"b\", \"c\", \"alpha\", \"beta\", \"gamma\"):\n", + " data_upload[f\"lattice.{k}\"] = data_upload.structure.apply(\n", + " lambda x: getattr(x.lattice, k)\n", + " )\n", + "\n", + "data_upload[\"num_sites\"] = data_upload.structure.apply(lambda x: len(x))\n", + "\n", + "for i, k in enumerate(\n", + " [\n", + " \"symbol\",\n", + " \"number\",\n", + " ]\n", + "):\n", + " data_upload[f\"symmetry.{k}\"] = data_upload.structure.apply(\n", + " lambda x: x.get_space_group_info()[i]\n", + " )" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we put the data in a format that the MPContribs client can parse. This should be a list of dicts of the form:\n", + "```python\n", + "contribs_format = [\n", + " {\n", + " \"data\": {\n", + " ... # data for a single entry, basically one row in the table\n", + " },\n", + " \"identifier\": ..., # required \n", + " \"project\": ... , # required\n", + " \"formula\": ..., # strongly recommended\n", + " \"structures\": [], # optional, list of `pymatgen.core.structure.Structure` objects, see below.\n", + " \"tables\": [], # optional, list of `pandas.DataFrame`-like objects\n", + " \"attachments\": [], # optional list of small, non-columnar data objects, see note below\n", + " }\n", + "]\n", + "```\n", + "\n", + "All data in `data` must include units which match those in `columns_with_units` for those units to be parsed correctly.\n", + "\n", + "Note that complex objects beyond standard JSON (str, bool, int, and float) should not be put in the `data` dict. There is a separate field for uploading `pymatgen.core.structure.Structure` data: `structures` above.\n", + "\n", + "
\n", + "\n", + "Simple array/matrix/tensorial data can be input as dot notation, e.g., a 2x2 array as:\n", + "\n", + "\n", + "```python\n", + "\n", + "a = [\n", + " [1., 2.],\n", + " [3., 4.]\n", + "] # original\n", + "\n", + "contribs_format = [\n", + " {\n", + " \"data\": {\n", + " f\"a.{i}{j}\": a[i][j] for j in range(2) for i in range(2)\n", + " },\n", + " ...\n", + " }\n", + "]\n", + "```\n", + "\n", + "
\n", + "\n", + "Smaller data objects can also optionally be included as [tables (columnar data) or attachments (non-columnar, like JPEGs)](https://docs.materialsproject.org/uploading-data/what-is-mpcontribs), however it may be more performant to upload these objects to AWS separately." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "contribs_format = [\n", + " {\n", + " \"data\": {\n", + " snake_to_camel(k): f\"{getattr(row, k)} {unit if unit else ''}\"\n", + " for k, unit in _columns_with_units.items()\n", + " },\n", + " \"identifier\": row.material_id,\n", + " \"project\": PROJECT_NAME,\n", + " \"formula\": row.structure.formula,\n", + " \"structures\": [row.structure],\n", + " }\n", + " for _, row in data_upload.iterrows()\n", + "]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we're ready to upload our data! You can upload up to 500 entries (rows) of a dataset before it requires approval from MP admins.\n", + "\n", + "For uploading, querying, or deleting very large datasets (>10,000 rows), you may want to explicitly pass the `timeout = " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "client.submit_contributions(contribs_format) # timeout = ... can be passed here" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Suppose you made a mistake and need to remove one or more entries. You can delete them as follows.\n", + "\n", + "To remove subsets of the data, you can use `pymongo`-syntax as a dict query in `delete_contributions`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "client.delete_contributions() # timeout = ... can be passed here" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "When you've received approval from MP admins, you can make your project public" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "client.init_columns()\n", + "client.make_public()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And if you change your mind, just make it private again" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "client.make_private()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "DANGER ZONE: to start from scratch, you can delete your project!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "client.delete_project()" + ] + } + ], + "metadata": { + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.0" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/mpcontribs-lux/examples/2-aws_opendata_upload.ipynb b/mpcontribs-lux/examples/2-aws_opendata_upload.ipynb new file mode 100644 index 000000000..a876fc5dd --- /dev/null +++ b/mpcontribs-lux/examples/2-aws_opendata_upload.ipynb @@ -0,0 +1,187 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "0", + "metadata": {}, + "source": [ + "## Requirements" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1", + "metadata": {}, + "outputs": [], + "source": [ + "!pip install pandas>=2.3.0 pyarrow>=21.0.0 boto3>=1.40.0 python-dotenv>=1.0.0" + ] + }, + { + "cell_type": "markdown", + "id": "2", + "metadata": {}, + "source": [ + "## Making a large-data download from OpenData\n", + "\n", + "To upload larger data objects, such as raw data, to MPContribs, you will need to obtain IAM credentials from MP staff. You should also think carefully about how you structure your data so that it is amenable to cloud storage.\n", + "Formats like `parquet` for columnar data and `zarr` for hierarchical data will aid in partial retrieval of data.\n", + "`parquet` also permits easily filtering data.\n", + "\n", + "In this example, we will simulate using a `.env` file to store AWS credentials:\n", + "```bash\n", + ">>> ~/.env\n", + "aws_access_key_id=abcdefg...\n", + "aws_secret_access_key=abcdefg...\n", + "```\n", + "\n", + "And convert the JSON data file to a single parquet file for download:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3", + "metadata": {}, + "outputs": [], + "source": [ + "import gzip\n", + "import json\n", + "import pandas as pd\n", + "import pyarrow as pa\n", + "\n", + "OPENDATA_BUCKET = \"materialsproject-contribs\"\n", + "PROJECT_NAME = \"test_solid_data\"\n", + "\n", + "with gzip.open(\"cubic_solid_expt_data.json.gz\", \"rt\") as f:\n", + " user_data = json.load(f)\n", + "\n", + "data = pd.DataFrame(user_data[\"data\"])\n", + "arrow_table = pa.Table.from_pandas(data)" + ] + }, + { + "cell_type": "markdown", + "id": "4", + "metadata": {}, + "source": [ + "As a reasonable best practice, we will embed the citation and column metadata in the `arrow` table schema. To do this, the metadata must be a dict of string keys mapped to strings (or bytes in both cases). This means we must flatten the `metadata` dict of the dataset, and serialize its values:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5", + "metadata": {}, + "outputs": [], + "source": [ + "import pyarrow.parquet as pq\n", + "\n", + "pq.write_table(\n", + " arrow_table.replace_schema_metadata(\n", + " metadata={\n", + " **arrow_table.schema.metadata,\n", + " **{\n", + " f\"{key}.{sub_key}\": json.dumps(v)\n", + " for key, vals in user_data[\"metadata\"].items()\n", + " for sub_key, v in vals.items()\n", + " },\n", + " }\n", + " ),\n", + " \"solid_data.parquet\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "6", + "metadata": {}, + "source": [ + "The following convenience functions are designed to make it easy to upload or delete data from AWS S3 OpenData." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7", + "metadata": {}, + "outputs": [], + "source": [ + "import boto3\n", + "from dotenv import load_dotenv\n", + "from pathlib import Path\n", + "import os\n", + "\n", + "\n", + "def get_s3_client():\n", + " \"\"\"Start an S3 client from credentials stored in a ~/.env file.\"\"\"\n", + " load_dotenv()\n", + " return boto3.client(\n", + " \"s3\",\n", + " **{k: os.environ[k] for k in (\"aws_access_key_id\", \"aws_secret_access_key\")},\n", + " )\n", + "\n", + "\n", + "def upload_single_file_to_aws(\n", + " in_path: str | Path,\n", + " out_path: str | Path | None = None,\n", + ") -> None:\n", + " \"\"\"Convenience function to upload a file to S3.\n", + "\n", + " Parameters\n", + " -----------\n", + " in_path : str | Path\n", + " The path to the file to be uploaded.\n", + " out_path : str, Path, or None\n", + " If a str or Path, the prefix and key of the file to upload.\n", + " If None (default), defaults to `s3://materialsproject-contribs/{PROJECT_NAME}/{file_name relative to cwd()}`.\n", + " \"\"\"\n", + " out_path = str(out_path or Path(PROJECT_NAME) / str(Path(in_path).name))\n", + " with open(str(in_path), \"rb\") as f:\n", + " get_s3_client().upload_fileobj(f, Bucket=OPENDATA_BUCKET, Key=out_path)\n", + "\n", + "\n", + "def delete_single_file_in_aws(in_path: str) -> None:\n", + " \"\"\"Remove a key from your OpenData bucket, specified by `in_path`.\"\"\"\n", + " get_s3_client().delete_object(\n", + " Bucket=OPENDATA_BUCKET, Key=str(Path(PROJECT_NAME) / str(Path(in_path).name))\n", + " )" + ] + }, + { + "cell_type": "markdown", + "id": "8", + "metadata": {}, + "source": [ + "Now we simply upload the parquet file we created earlier" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9", + "metadata": {}, + "outputs": [], + "source": [ + "upload_single_file_to_aws(\"solid_data.parquet\")" + ] + } + ], + "metadata": { + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.0" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/mpcontribs-lux/examples/README.md b/mpcontribs-lux/examples/README.md new file mode 100644 index 000000000..05a7b06ac --- /dev/null +++ b/mpcontribs-lux/examples/README.md @@ -0,0 +1,32 @@ +# Examples for programmatically uploading data to MPContribs + +[MPContribs](https://docs.materialsproject.org/services/mpcontribs) is a parallel API / frontend to the [Materials Project](https://next-gen.materialsproject.org/) that allows users to upload structured data from their research. +It exists as a separate storage solution to non-domain-specific data repositories, and is backed by MongoDB and a [python client](https://github.com/materialsproject/MPContribs/tree/master/mpcontribs-client). +This example walks the user through uploading a set of data to MPContribs programmatically. + +For the Materials Project documentation on MPContribs, see [here](https://docs.materialsproject.org/uploading-data/). + +These guides will walk you through uploading a real MPContribs project, [`test_solid_data`](https://next-gen.materialsproject.org/contribs/projects/test_solid_data), which you can also use for reference when uploading your data. + +## Is this guide right for you? + +If you like using python and have data that is not purely columnar/CSV/excel, e.g., data including structured python objects, then this guide could be useful for you. +If you are less comfortable with python, or have non-columnar data, then you should consider using the [contribs upload interface](https://next-gen.materialsproject.org/contribs/create) + +## Prerequisites + +You will need an account with the Materials Project. +Once you've signed in, copy your API key from your [dashboard](https://next-gen.materialsproject.org/api) and either +1. Run from a terminal: + ``` + echo 'export MP_API_KEY=' >> ~/.bashrc + echo 'export MPCONTRIBS_API_KEY=$MP_API_KEY' >> ~/.bashrc +``` +and replace ``, and ~/.bashrc with ~/.zshrc, etc. as appropriate. + +2. Use it explicitly in the API client code +3. Use an alternate environment variable solution like `.env` files. + +For a python environment, you will need the packages in `requirements.txt`. +If you need to upload large (>15 MB/document limit of MongoDB) or raw data, this guide will instruct you how to upload those data objects to the Materials Project's AWS OpenData bucket, pending permission/IAM credentials from Materials Project staff. +If you are uploading large data, we strongly recomment using the `pyarrow` package to write parquet files for data that is amenable to more columnar formats, and `zarr` for hierarchical/HDF5-like/netCDF-like or tensorial data. diff --git a/mpcontribs-lux/examples/cubic_solid_expt_data.json.gz b/mpcontribs-lux/examples/cubic_solid_expt_data.json.gz new file mode 100644 index 000000000..4b6e13305 --- /dev/null +++ b/mpcontribs-lux/examples/cubic_solid_expt_data.json.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:20e29c227b5e1926926ad653dd42e11166dd908c6410fb8ea902c36a0d5c72f9 +size 3460 diff --git a/mpcontribs-lux/mpcontribs/lux/_types.py b/mpcontribs-lux/mpcontribs/lux/_types.py new file mode 100644 index 000000000..5da8cdda9 --- /dev/null +++ b/mpcontribs-lux/mpcontribs/lux/_types.py @@ -0,0 +1,13 @@ +"""Define a few custom types for use in schemas.""" + +from typing import Annotated + +from pydantic import BeforeValidator + +_complex_type_validator = BeforeValidator( + lambda x: (x.real, x.imag) if isinstance(x, complex) else x +) + +ComplexType = Annotated[tuple[float, float], _complex_type_validator] + +NullableComplexType = Annotated[tuple[float, float] | None, _complex_type_validator] diff --git a/mpcontribs-lux/mpcontribs/lux/autogen.py b/mpcontribs-lux/mpcontribs/lux/autogen.py new file mode 100644 index 000000000..aeee406c2 --- /dev/null +++ b/mpcontribs-lux/mpcontribs/lux/autogen.py @@ -0,0 +1,163 @@ +"""Automatically generate schemas from existing data using pandas.""" + +from enum import StrEnum +from typing import Any, Type + +from emmet.core.types.typing import NullableDateTimeType, DateTimeType +import pandas as pd +from pathlib import Path +from pydantic import BaseModel, Field, model_validator, create_model + +from mpcontribs.lux._types import ComplexType, NullableComplexType + + +class FileFormat(StrEnum): + """Define known file formats for autogeneration of schemae.""" + + CSV = "csv" + JSON = "json" + JSONL = "jsonl" + + +class SchemaGenerator(BaseModel): + """Automatically infer a dataset schema and create a pydantic model from it.""" + + file_name: str | Path = Field(description="The path to the dataset.") + + fmt: FileFormat | None = Field( + None, + description="The dataset file format. If no format is provided, it will be inferred.", + ) + + @model_validator(mode="before") + def check_format(cls, config: dict[str, Any]) -> dict[str, Any]: + + if isinstance(fp := config["file_name"], str): + config["file_name"] = Path(fp).resolve() + + if config.get("fmt"): + if isinstance(config["fmt"], str): + if config["fmt"] in FileFormat.__members__: + config["fmt"] = FileFormat[config["fmt"]] + else: + try: + config["fmt"] = FileFormat(config["fmt"]) + except ValueError: + raise ValueError( + f"Could not interpret submitted file format {config['fmt']}" + ) + else: + try: + config["fmt"] = next( + file_fmt + for file_fmt in FileFormat + if file_fmt.value in config["file_name"].name + ) + except StopIteration: + raise ValueError( + f"Could not infer file format for {config['file_name']}" + ) + return config + + @staticmethod + def _cast_dtype(dtype, assume_nullable: bool = True): + """Cast input dtype to parquet-friendly dtypes. + + Accounts for difficulties de-serializing datetimes + and complex numbers. + + Assumes all fields are nullable by default. + """ + vname = getattr(dtype, "name", str(dtype)).lower() + + if any(spec_type in vname for spec_type in ("datetime", "complex")): + if "datetime" in vname: + return NullableDateTimeType if assume_nullable else DateTimeType + elif "complex" in vname: + return NullableComplexType if assume_nullable else ComplexType + + inferred_type = str + if "float" in vname: + inferred_type = float + elif "int" in vname: + inferred_type = int + + return inferred_type | None if assume_nullable else inferred_type + + @property + def pydantic_model(self) -> Type[BaseModel]: + """Create the pydantic model of the data structure.""" + + if self.fmt == "csv": + data = pd.read_csv(self.file_name) + + elif self.fmt in {"json", "jsonl"}: + # we exclude the "table" case for `orient` since the user + # presumably already knows what the schema is. + for orient in ("columns", "index", "records", "split", "values"): + try: + data = pd.read_json( + self.file_name, orient=orient, lines=self.fmt == "jsonl" + ) + break + except Exception as exc: + continue + else: + raise ValueError( + f"Could not load {self.fmt.value} data, please check manually." + ) + + model_fields = { + col_name: ( + self._cast_dtype(data.dtypes[col_name]), + Field( + default=None, + ), + ) + for col_name in data.columns + } + + return create_model( + f"{self.file_name.name.split('.',1)[0]}", + **model_fields, + ) + + def schema( + self, model_name: str | None = None, descriptions: dict[str, str] | None = None + ) -> str: + """Generate a python-like string which can be used to schematize data. + + Parameters + ----------- + model_name : str or None (default) + If a str, the name of the class to use. + If None, defaults to the name of the file from which the schema was read. + descriptions : dict of str to str, or None (default) + If a dict, the descriptions of the model fields included. + If None, no descriptions are used. + + Returns + ----------- + str which can be written to a file. + See `mpcontribs-lux.tests.test_autogen` for examples. + """ + field_desc = {k: f'"{v}"' if v else v for k, v in (descriptions or {}).items()} + + pydantic_model = self.pydantic_model + schema_str = f""" +from pydantic import BaseModel, Field + +from emmet.core.types.typing import NullableDateTimeType, DateTimeType +from mpcontribs.lux._types import ComplexType, NullableComplexType + +class {model_name or pydantic_model.__name__}(BaseModel): +""" + schema_str += "".join( + f""" + {field_name} : {field.annotation} = Field( + default={field.default}, + description = {field_desc.get(field_name)}) +""" + for field_name, field in pydantic_model.model_fields.items() + ) + return schema_str diff --git a/mpcontribs-lux/mpcontribs/lux/projects/__init__.py b/mpcontribs-lux/mpcontribs/lux/projects/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/mpcontribs-lux/mpcontribs/lux/projects/esoteric_ephemera/__init__.py b/mpcontribs-lux/mpcontribs/lux/projects/esoteric_ephemera/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/mpcontribs-lux/mpcontribs/lux/projects/esoteric_ephemera/schemas/MP_ALOE_2025.py b/mpcontribs-lux/mpcontribs/lux/projects/esoteric_ephemera/schemas/MP_ALOE_2025.py new file mode 100644 index 000000000..754df5e51 --- /dev/null +++ b/mpcontribs-lux/mpcontribs/lux/projects/esoteric_ephemera/schemas/MP_ALOE_2025.py @@ -0,0 +1,28 @@ +"""Define schemas for the MP-ALOE 2025 dataset.""" + +from pydantic import Field + +from mpcontribs.lux.projects.esoteric_ephemera.schemas.MatPES_2025_1 import ( + MatPESTrainDoc, +) + + +class MPAloeTrainDoc(MatPESTrainDoc): + """Schematize MP-ALOE data.""" + + mp_aloe_id: str | None = Field( + None, description="The identifier of this entry in MP-ALOE." + ) + ionic_step_number: int | None = Field( + None, description="The ionic step index of this frame." + ) + prototype_number: int | None = Field( + None, description="The index of the prototype structure used in generation." + ) + is_charge_balanced: bool | None = Field( + None, description="Whether the structure is likely charge balanced." + ) + has_overlapping_pseudo_cores: bool | None = Field( + None, + description="Whether the pseudopotential cores overlap for at least one set of nearest neighbors.", + ) diff --git a/mpcontribs-lux/mpcontribs/lux/projects/esoteric_ephemera/schemas/MPtrj_2022_9.py b/mpcontribs-lux/mpcontribs/lux/projects/esoteric_ephemera/schemas/MPtrj_2022_9.py new file mode 100644 index 000000000..113333f4e --- /dev/null +++ b/mpcontribs-lux/mpcontribs/lux/projects/esoteric_ephemera/schemas/MPtrj_2022_9.py @@ -0,0 +1,48 @@ +"""Define schemas for the MPtrj v2022.9 dataset.""" + +from pydantic import BaseModel, Field + +from emmet.core.types.typing import IdentifierType + +from mpcontribs.lux.projects.esoteric_ephemera.schemas.base import MLTrainDoc + + +class MPtrjProvenance(BaseModel): + """Metadata for MPtrj entries.""" + + material_id: IdentifierType | None = Field( + None, description="The Materials Project (summary) ID for this material." + ) + task_id: IdentifierType | None = Field( + None, description="The Materials Project (summary) ID for this material." + ) + calcs_reversed_index: int | None = Field( + None, description="The index of the reversed calculations, if applicable." + ) + ionic_step_index: int | None = Field( + None, description="The index of the ionic step, if applicable." + ) + + +class MPtrjTrainDoc(MLTrainDoc): + """Schematize MPtrj data.""" + + energy: float | None = Field( + None, description="The total uncorrected energy associated with this structure." + ) + + cohesive_energy_per_atom: float | None = Field( + None, description="The uncorrected cohesive energy per atom of this material." + ) + + corrected_cohesive_energy_per_atom: float | None = Field( + None, + description=( + "The corrected cohesive energy per atom of this material, " + "using the Materials Project GGA / GGA+U mixing scheme." + ), + ) + + provenance: MPtrjProvenance | None = Field( + None, description="Metadata for this frame." + ) diff --git a/mpcontribs-lux/mpcontribs/lux/projects/esoteric_ephemera/schemas/MatPES_2025_1.py b/mpcontribs-lux/mpcontribs/lux/projects/esoteric_ephemera/schemas/MatPES_2025_1.py new file mode 100644 index 000000000..e6c0925ce --- /dev/null +++ b/mpcontribs-lux/mpcontribs/lux/projects/esoteric_ephemera/schemas/MatPES_2025_1.py @@ -0,0 +1,69 @@ +"""Define schemas for the MatPES 2025.1 dataset.""" + +from pydantic import BaseModel, Field + +from emmet.core.types.typing import IdentifierType + +from mpcontribs.lux.projects.esoteric_ephemera.schemas.base import MLTrainDoc + + +class MatPESProvenanceDoc(BaseModel): + """Information regarding the origins of a MatPES structure.""" + + original_mp_id: IdentifierType | None = Field( + None, + description="MP identifier corresponding to the Materials Project structure from which this entry was sourced from.", + ) + materials_project_version: str | None = Field( + None, + description="The version of the Materials Project from which the struture was sourced.", + ) + md_ensemble: str | None = Field( + None, + description="The molecular dynamics ensemble used to generate this structure.", + ) + md_temperature: float | None = Field( + None, + description="If a float, the temperature in Kelvin at which MLMD was performed.", + ) + md_pressure: float | None = Field( + None, + description="If a float, the pressure in atmosphere at which MLMD was performed.", + ) + md_step: int | None = Field( + None, + description="The step in the MD simulation from which the structure was sampled.", + ) + mlip_name: str | None = Field( + None, description="The name of the ML potential used to perform MLMD." + ) + + +class MatPESTrainDoc(MLTrainDoc): + """ + Schema for VASP data in the Materials Potential Energy Surface (MatPES) effort. + + This schema is used in the data entries for MatPES v2025.1, + which can be downloaded either: + - On [MPContribs](https://materialsproject-contribs.s3.amazonaws.com/index.html#MatPES_2025_1/) + - or on [the site](https://matpes.ai) + """ + + matpes_id: str | None = Field(None, description="MatPES identifier.") + + formation_energy_per_atom: float | None = Field( + None, + description="The uncorrected formation enthalpy per atom at zero pressure and temperature.", + ) + cohesive_energy_per_atom: float | None = Field( + None, description="The uncorrected cohesive energy per atom." + ) + + provenance: MatPESProvenanceDoc | None = Field( + None, description="Information about the provenance of the structure." + ) + + @property + def pressure(self) -> float | None: + """Return the pressure from the DFT stress tensor.""" + return sum(self.stress[:3]) / 3.0 if self.stress else None diff --git a/mpcontribs-lux/mpcontribs/lux/projects/esoteric_ephemera/schemas/__init__.py b/mpcontribs-lux/mpcontribs/lux/projects/esoteric_ephemera/schemas/__init__.py new file mode 100644 index 000000000..785cafc05 --- /dev/null +++ b/mpcontribs-lux/mpcontribs/lux/projects/esoteric_ephemera/schemas/__init__.py @@ -0,0 +1,10 @@ +from mpcontribs.lux.projects.esoteric_ephemera.schemas.base import MLTrainDoc +from mpcontribs.lux.projects.esoteric_ephemera.schemas.MatPES_2025_1 import ( + MatPESTrainDoc, +) +from mpcontribs.lux.projects.esoteric_ephemera.schemas.MP_ALOE_2025 import ( + MPAloeTrainDoc, +) +from mpcontribs.lux.projects.esoteric_ephemera.schemas.MPtrj_2022_9 import MPtrjTrainDoc + +__all__ = ["MLTrainDoc", "MatPESTrainDoc", "MPAloeTrainDoc", "MPtrjTrainDoc"] diff --git a/mpcontribs-lux/mpcontribs/lux/projects/esoteric_ephemera/schemas/base.py b/mpcontribs-lux/mpcontribs/lux/projects/esoteric_ephemera/schemas/base.py new file mode 100644 index 000000000..6a9f6607c --- /dev/null +++ b/mpcontribs-lux/mpcontribs/lux/projects/esoteric_ephemera/schemas/base.py @@ -0,0 +1,236 @@ +"""Define base schemas for machine learning interatomic potential data.""" + +from __future__ import annotations + +from functools import cached_property +from typing import TYPE_CHECKING + +import numpy as np +from pydantic import Field + +from emmet.core.structure import StructureMetadata +from emmet.core.math import Matrix3D, Vector3D, Vector6D, matrix_3x3_to_voigt +from emmet.core.types.pymatgen_types.composition_adapter import CompositionType +from emmet.core.types.pymatgen_types.element_adapter import ElementType +from emmet.core.vasp.calc_types import RunType as VaspRunType + +from pymatgen.core import Element, Structure + +if TYPE_CHECKING: + from typing_extensions import Self + + from emmet.core.tasks import TaskDoc + + +class MLTrainDoc(StructureMetadata, extra="allow"): # type: ignore[call-arg] + """Generic schema for ML training data.""" + + cell: Matrix3D | None = Field( + None, + description="The 3x3 matrix of cell/lattice vectors, such that a is the first row, b the second, and c the third.", + ) + + atomic_numbers: list[int] | None = Field( + None, + description="The list of proton numbers at each site. Should be the same length as `cart_coords`", + ) + + cart_coords: list[Vector3D] | None = Field( + None, + description="The list of Cartesian coordinates of each atom. Should be the same length as `atomic_numbers`.", + ) + + magmoms: list[float] | None = Field( + None, description="The list of on-site magnetic moments." + ) + + energy: float | None = Field( + None, description="The total energy associated with this structure." + ) + + forces: list[Vector3D] | None = Field( + None, + description="The interatomic forces corresponding to each site in the structure.", + ) + + abs_forces: list[float] | None = Field( + None, description="The magnitude of the interatomic force on each site." + ) + + stress: Vector6D | None = Field( + None, + description="The components of the symmetric stress tensor in Voigt notation (xx, yy, zz, yz, xz, xy).", + ) + + stress_matrix: Matrix3D | None = Field( + None, + description="The 3x3 stress tensor. Use this if the tensor is unphysically non-symmetric.", + ) + + bandgap: float | None = Field(None, description="The final DFT bandgap.") + + elements: list[ElementType] | None = Field( + None, + description="List of unique elements in the material sorted alphabetically.", + ) + + composition: CompositionType | None = Field( + None, description="Full composition for the material." + ) + + composition_reduced: CompositionType | None = Field( + None, + title="Reduced Composition", + description="Simplified representation of the composition.", + ) + + functional: VaspRunType | None = Field( + None, description="The approximate functional used to generate this entry." + ) + + bader_charges: list[float] | None = Field( + None, description="Bader charges on each site of the structure." + ) + bader_magmoms: list[float] | None = Field( + None, + description="Bader on-site magnetic moments for each site of the structure.", + ) + + @cached_property + def structure(self) -> Structure: + """Get the structure associated with this entry.""" + site_props = {"magmom": self.magmoms} if self.magmoms else None + return Structure( + np.array(self.cell), + [Element.from_Z(z) for z in self.atomic_numbers], # type: ignore[union-attr] + self.cart_coords, # type: ignore[arg-type] + coords_are_cartesian=True, + site_properties=site_props, + ) + + @classmethod + def from_structure( + cls, + meta_structure: Structure, + fields: list[str] | None = None, + **kwargs, + ) -> Self: + """ + Create an ML training document from an ordered structure and fields. + + This method mostly exists to ensure that the structure field is + set because `meta_structure` does not populate it automatically. + + Parameters + ----------- + meta_structure : Structure + An ordered structure + fields : list of str or None + Additional fields in the document to populate + **kwargs + Any other fields / constructor kwargs + """ + if not meta_structure.is_ordered: + raise ValueError( + f"{cls.__name__} only supports ordered structures at this time." + ) + + if (forces := kwargs.get("forces")) is not None and kwargs.get( + "abs_forces" + ) is None: + kwargs["abs_forces"] = [np.linalg.norm(f) for f in forces] + + if magmoms := meta_structure.site_properties.get("magmom"): + kwargs["magmoms"] = magmoms + + return super().from_structure( + meta_structure=meta_structure, + fields=fields, + cell=meta_structure.lattice.matrix, + atomic_numbers=[site.specie.Z for site in meta_structure], + cart_coords=meta_structure.cart_coords, + **kwargs, + ) + + @classmethod + def from_task_doc( + cls, + task_doc: TaskDoc, + **kwargs, + ) -> list[Self]: + """Create a list of ML training documents from the ionic steps in a TaskDoc. + + Parameters + ----------- + task_doc : TaskDoc + **kwargs + Any kwargs to pass to `from_structure`. + """ + entries = [] + + for cr in task_doc.calcs_reversed[::-1]: + nion = len(cr.output.ionic_steps) + + for iion, ionic_step in enumerate(cr.output.ionic_steps): + structure = Structure.from_dict(ionic_step.structure.as_dict()) + # these are fields that should only be set on the final frame of a calculation + # also patch in magmoms because of how Calculation works + last_step_kwargs = {} + if iion == nion - 1: + if magmom := cr.output.structure.site_properties.get("magmom"): + structure.add_site_property("magmom", magmom) + last_step_kwargs["bandgap"] = cr.output.bandgap + if bader_analysis := cr.bader: + for bk in ( + "charge", + "magmom", + ): + last_step_kwargs[f"bader_{bk}s"] = bader_analysis[bk] + + if (_st := ionic_step.stress) is not None: + st = np.array(_st) + if np.allclose(st, st.T, rtol=1e-8): + # Stress tensor is symmetric + last_step_kwargs["stress"] = matrix_3x3_to_voigt(_st) + else: + # Stress tensor is non-symmetric + last_step_kwargs["stress_matrix"] = _st + + entries.append( + cls.from_structure( + meta_structure=structure, + energy=ionic_step.e_0_energy, + forces=ionic_step.forces, + functional=cr.run_type, + **last_step_kwargs, + **kwargs, + ) + ) + return entries + + @cached_property + def to_ase_atoms(self): + """Get the ASE Atoms associated with this entry.""" + + try: + from ase.calculators.singlepoint import SinglePointCalculator + from ase import Atoms + except ImportError: + raise ImportError( + "You must `pip install ase` to use the atoms functionality here!" + ) + + atoms = Atoms( + positions=self.cart_coords, + numbers=self.atomic_numbers, + cell=self.cell, + ) + calc = SinglePointCalculator( + atoms, + **{ + k: getattr(self, k, None) + for k in {"energy", "forces", "stress", "magmoms"} + }, + ) + atoms.calc = calc + return atoms diff --git a/mpcontribs-lux/mpcontribs/lux/projects/examples.py b/mpcontribs-lux/mpcontribs/lux/projects/examples.py new file mode 100644 index 000000000..c2ac2e52b --- /dev/null +++ b/mpcontribs-lux/mpcontribs/lux/projects/examples.py @@ -0,0 +1,65 @@ +"""Define example schemas for users. + +This schema is used for the public MPContribs project `test_solid_data`: + https://next-gen.materialsproject.org/contribs/projects/test_solid_data +You can find its download on AWS S3: + https://materialsproject-contribs.s3.amazonaws.com/index.html#test_solid_data/solid_data.parquet +""" + +from functools import cached_property + +from pydantic import BaseModel, Field + +from pymatgen.core import Structure + + +class ExampleSchema(BaseModel): + """Define example schema with appropriate levels of annotated metadata.""" + + formula: str | None = Field( + None, description="The chemical formula of the unit cell." + ) + + a0: float | None = Field( + None, + description="The experimental equilibrium cubic " + "lattice constant a, in Å, including zero-point corrections " + "for nuclear vibration.", + ) + + b0: float | None = Field( + None, + description="The experimental bulk modulus at " + "optimal lattice geometry, in GPa, including zero-point " + "corrections for nuclear vibration.", + ) + + e0: float | None = Field( + None, + description="The experimental cohesive energy, in eV/atom, " + "including zero-point corrections for nuclear vibration.", + ) + + cif: str | None = Field( + None, + description="The structure represented as a Crystallographic Information File.", + ) + + material_id: str | None = Field( + None, + description="The Materials Project ID of the structure which " + "corresponds to this entry. The ID will start with `mp-`", + ) + + @cached_property + def get_pymatgen_structure(self) -> Structure | None: + """Get the pymatgen structure for this entry, if it exists. + + Example of adding functionality to downstream users to interact + with your data. + + You can provide more advanced analysis tools, which we also show below. + """ + if self.cif: + return Structure.from_str(self.cif, fmt="cif") + return None diff --git a/mpcontribs-lux/pyproject.toml b/mpcontribs-lux/pyproject.toml new file mode 100644 index 000000000..c259b97ee --- /dev/null +++ b/mpcontribs-lux/pyproject.toml @@ -0,0 +1,49 @@ +[build-system] +requires = ["setuptools>=80.0.0","setuptools-scm>=8"] +build-backend = "setuptools.build_meta" + +[tool.setuptools_scm] +root = ".." +relative_to = "__file__" + +[tool.setuptools] +include-package-data = true + +[tool.setuptools.packages.find] +where = ["."] +exclude = ["tests","examples","test_data"] +include = ["mpcontribs.lux"] + + +[project] +name = "mpcontribs-lux" +dynamic = ["version"] +description = "LUX: shed light on data published on MPContribs" +readme = "README.md" +requires-python = ">=3.11" +dependencies = [ + "emmet-core>0.86.0", + "pyarrow", + "pandas", +] +license = {text = "Modified BSD"} +authors = [ + {name = "The Materials Project", email="feedback@materialsproject.org"}, +] + +[project.urls] +Homepage = "https://github.com/materialsproject/MPContribs" +Documentation = "https://docs.materialsproject.org/services/mpcontribs" + +[project.optional-dependencies] +test = [ + "pre-commit", + "pytest", + "pytest-cov", + "pytest-xdist", + "pycodestyle", + "pydocstyle", + "flake8", + "mypy", + "mypy-extensions", +] diff --git a/mpcontribs-lux/requirements/requirements-ubuntu-latest_py3.11.txt b/mpcontribs-lux/requirements/requirements-ubuntu-latest_py3.11.txt new file mode 100644 index 000000000..bb73ebe8a --- /dev/null +++ b/mpcontribs-lux/requirements/requirements-ubuntu-latest_py3.11.txt @@ -0,0 +1,144 @@ +# +# This file is autogenerated by pip-compile with Python 3.12 +# by the following command: +# +# pip-compile --output-file=requirements/requirements-ubuntu-latest_py3.12.txt +# +annotated-types==0.7.0 + # via pydantic +bibtexparser==1.4.3 + # via pymatgen +blake3==1.0.8 + # via emmet-core +certifi==2025.11.12 + # via requests +charset-normalizer==3.4.4 + # via requests +contourpy==1.3.3 + # via matplotlib +cycler==0.12.1 + # via matplotlib +emmet-core==0.86.2 + # via mpcontribs-lux (pyproject.toml) +fonttools==4.61.0 + # via matplotlib +idna==3.11 + # via requests +joblib==1.5.2 + # via pymatgen +kiwisolver==1.4.9 + # via matplotlib +latexcodec==3.0.1 + # via pybtex +matplotlib==3.10.7 + # via pymatgen +monty==2025.3.3 + # via + # emmet-core + # pymatgen +mpmath==1.3.0 + # via sympy +narwhals==2.13.0 + # via plotly +networkx==3.6.1 + # via pymatgen +numpy==2.3.5 + # via + # contourpy + # matplotlib + # monty + # pandas + # pymatgen + # pymatgen-io-validation + # scipy + # spglib +orjson==3.11.5 + # via pymatgen +packaging==25.0 + # via + # matplotlib + # plotly +palettable==3.3.3 + # via pymatgen +pandas==2.3.3 + # via + # mpcontribs-lux (pyproject.toml) + # pymatgen +pillow==12.0.0 + # via matplotlib +plotly==6.5.0 + # via pymatgen +pyarrow==22.0.0 + # via mpcontribs-lux (pyproject.toml) +pybtex==0.25.1 + # via emmet-core +pydantic==2.12.5 + # via + # emmet-core + # pydantic-settings + # pymatgen-io-validation +pydantic-core==2.41.5 + # via pydantic +pydantic-settings==2.12.0 + # via + # emmet-core + # pymatgen-io-validation +pymatgen==2025.10.7 + # via + # emmet-core + # pymatgen-io-validation +pymatgen-io-validation==0.1.2 + # via emmet-core +pyparsing==3.2.5 + # via + # bibtexparser + # matplotlib +python-dateutil==2.9.0.post0 + # via + # matplotlib + # pandas +python-dotenv==1.2.1 + # via pydantic-settings +pytz==2025.2 + # via pandas +pyyaml==6.0.3 + # via pybtex +requests==2.32.5 + # via + # pymatgen + # pymatgen-io-validation +ruamel-yaml==0.18.16 + # via + # monty + # pymatgen +ruamel-yaml-clib==0.2.15 + # via ruamel-yaml +scipy==1.16.3 + # via pymatgen +six==1.17.0 + # via python-dateutil +spglib==2.6.0 + # via pymatgen +sympy==1.14.0 + # via pymatgen +tabulate==0.9.0 + # via pymatgen +tqdm==4.67.1 + # via pymatgen +typing-extensions==4.15.0 + # via + # emmet-core + # pydantic + # pydantic-core + # spglib + # typing-inspection +typing-inspection==0.4.2 + # via + # pydantic + # pydantic-settings +tzdata==2025.2 + # via pandas +uncertainties==3.2.3 + # via pymatgen +urllib3==2.6.1 + # via requests diff --git a/mpcontribs-lux/requirements/requirements-ubuntu-latest_py3.11_extras.txt b/mpcontribs-lux/requirements/requirements-ubuntu-latest_py3.11_extras.txt new file mode 100644 index 000000000..cb109503c --- /dev/null +++ b/mpcontribs-lux/requirements/requirements-ubuntu-latest_py3.11_extras.txt @@ -0,0 +1,209 @@ +# +# This file is autogenerated by pip-compile with Python 3.12 +# by the following command: +# +# pip-compile --all-extras --output-file=requirements/requirements-ubuntu-latest_py3.12_extras.txt +# +annotated-types==0.7.0 + # via pydantic +bibtexparser==1.4.3 + # via pymatgen +blake3==1.0.8 + # via emmet-core +certifi==2025.11.12 + # via requests +cfgv==3.5.0 + # via pre-commit +charset-normalizer==3.4.4 + # via requests +contourpy==1.3.3 + # via matplotlib +coverage[toml]==7.13.0 + # via pytest-cov +cycler==0.12.1 + # via matplotlib +distlib==0.4.0 + # via virtualenv +emmet-core==0.86.2 + # via mpcontribs-lux (pyproject.toml) +execnet==2.1.2 + # via pytest-xdist +filelock==3.20.0 + # via virtualenv +flake8==7.3.0 + # via mpcontribs-lux (pyproject.toml) +fonttools==4.61.0 + # via matplotlib +identify==2.6.15 + # via pre-commit +idna==3.11 + # via requests +iniconfig==2.3.0 + # via pytest +joblib==1.5.2 + # via pymatgen +kiwisolver==1.4.9 + # via matplotlib +latexcodec==3.0.1 + # via pybtex +librt==0.7.3 + # via mypy +matplotlib==3.10.7 + # via pymatgen +mccabe==0.7.0 + # via flake8 +monty==2025.3.3 + # via + # emmet-core + # pymatgen +mpmath==1.3.0 + # via sympy +mypy==1.19.0 + # via mpcontribs-lux (pyproject.toml) +mypy-extensions==1.1.0 + # via + # mpcontribs-lux (pyproject.toml) + # mypy +narwhals==2.13.0 + # via plotly +networkx==3.6.1 + # via pymatgen +nodeenv==1.9.1 + # via pre-commit +numpy==2.3.5 + # via + # contourpy + # matplotlib + # monty + # pandas + # pymatgen + # pymatgen-io-validation + # scipy + # spglib +orjson==3.11.5 + # via pymatgen +packaging==25.0 + # via + # matplotlib + # plotly + # pytest +palettable==3.3.3 + # via pymatgen +pandas==2.3.3 + # via + # mpcontribs-lux (pyproject.toml) + # pymatgen +pathspec==0.12.1 + # via mypy +pillow==12.0.0 + # via matplotlib +platformdirs==4.5.1 + # via virtualenv +plotly==6.5.0 + # via pymatgen +pluggy==1.6.0 + # via + # pytest + # pytest-cov +pre-commit==4.5.0 + # via mpcontribs-lux (pyproject.toml) +pyarrow==22.0.0 + # via mpcontribs-lux (pyproject.toml) +pybtex==0.25.1 + # via emmet-core +pycodestyle==2.14.0 + # via + # flake8 + # mpcontribs-lux (pyproject.toml) +pydantic==2.12.5 + # via + # emmet-core + # pydantic-settings + # pymatgen-io-validation +pydantic-core==2.41.5 + # via pydantic +pydantic-settings==2.12.0 + # via + # emmet-core + # pymatgen-io-validation +pydocstyle==6.3.0 + # via mpcontribs-lux (pyproject.toml) +pyflakes==3.4.0 + # via flake8 +pygments==2.19.2 + # via pytest +pymatgen==2025.10.7 + # via + # emmet-core + # pymatgen-io-validation +pymatgen-io-validation==0.1.2 + # via emmet-core +pyparsing==3.2.5 + # via + # bibtexparser + # matplotlib +pytest==9.0.2 + # via + # mpcontribs-lux (pyproject.toml) + # pytest-cov + # pytest-xdist +pytest-cov==7.0.0 + # via mpcontribs-lux (pyproject.toml) +pytest-xdist==3.8.0 + # via mpcontribs-lux (pyproject.toml) +python-dateutil==2.9.0.post0 + # via + # matplotlib + # pandas +python-dotenv==1.2.1 + # via pydantic-settings +pytz==2025.2 + # via pandas +pyyaml==6.0.3 + # via + # pre-commit + # pybtex +requests==2.32.5 + # via + # pymatgen + # pymatgen-io-validation +ruamel-yaml==0.18.16 + # via + # monty + # pymatgen +ruamel-yaml-clib==0.2.15 + # via ruamel-yaml +scipy==1.16.3 + # via pymatgen +six==1.17.0 + # via python-dateutil +snowballstemmer==3.0.1 + # via pydocstyle +spglib==2.6.0 + # via pymatgen +sympy==1.14.0 + # via pymatgen +tabulate==0.9.0 + # via pymatgen +tqdm==4.67.1 + # via pymatgen +typing-extensions==4.15.0 + # via + # emmet-core + # mypy + # pydantic + # pydantic-core + # spglib + # typing-inspection +typing-inspection==0.4.2 + # via + # pydantic + # pydantic-settings +tzdata==2025.2 + # via pandas +uncertainties==3.2.3 + # via pymatgen +urllib3==2.6.1 + # via requests +virtualenv==20.35.4 + # via pre-commit diff --git a/mpcontribs-lux/requirements/requirements-ubuntu-latest_py3.12.txt b/mpcontribs-lux/requirements/requirements-ubuntu-latest_py3.12.txt new file mode 100644 index 000000000..bb73ebe8a --- /dev/null +++ b/mpcontribs-lux/requirements/requirements-ubuntu-latest_py3.12.txt @@ -0,0 +1,144 @@ +# +# This file is autogenerated by pip-compile with Python 3.12 +# by the following command: +# +# pip-compile --output-file=requirements/requirements-ubuntu-latest_py3.12.txt +# +annotated-types==0.7.0 + # via pydantic +bibtexparser==1.4.3 + # via pymatgen +blake3==1.0.8 + # via emmet-core +certifi==2025.11.12 + # via requests +charset-normalizer==3.4.4 + # via requests +contourpy==1.3.3 + # via matplotlib +cycler==0.12.1 + # via matplotlib +emmet-core==0.86.2 + # via mpcontribs-lux (pyproject.toml) +fonttools==4.61.0 + # via matplotlib +idna==3.11 + # via requests +joblib==1.5.2 + # via pymatgen +kiwisolver==1.4.9 + # via matplotlib +latexcodec==3.0.1 + # via pybtex +matplotlib==3.10.7 + # via pymatgen +monty==2025.3.3 + # via + # emmet-core + # pymatgen +mpmath==1.3.0 + # via sympy +narwhals==2.13.0 + # via plotly +networkx==3.6.1 + # via pymatgen +numpy==2.3.5 + # via + # contourpy + # matplotlib + # monty + # pandas + # pymatgen + # pymatgen-io-validation + # scipy + # spglib +orjson==3.11.5 + # via pymatgen +packaging==25.0 + # via + # matplotlib + # plotly +palettable==3.3.3 + # via pymatgen +pandas==2.3.3 + # via + # mpcontribs-lux (pyproject.toml) + # pymatgen +pillow==12.0.0 + # via matplotlib +plotly==6.5.0 + # via pymatgen +pyarrow==22.0.0 + # via mpcontribs-lux (pyproject.toml) +pybtex==0.25.1 + # via emmet-core +pydantic==2.12.5 + # via + # emmet-core + # pydantic-settings + # pymatgen-io-validation +pydantic-core==2.41.5 + # via pydantic +pydantic-settings==2.12.0 + # via + # emmet-core + # pymatgen-io-validation +pymatgen==2025.10.7 + # via + # emmet-core + # pymatgen-io-validation +pymatgen-io-validation==0.1.2 + # via emmet-core +pyparsing==3.2.5 + # via + # bibtexparser + # matplotlib +python-dateutil==2.9.0.post0 + # via + # matplotlib + # pandas +python-dotenv==1.2.1 + # via pydantic-settings +pytz==2025.2 + # via pandas +pyyaml==6.0.3 + # via pybtex +requests==2.32.5 + # via + # pymatgen + # pymatgen-io-validation +ruamel-yaml==0.18.16 + # via + # monty + # pymatgen +ruamel-yaml-clib==0.2.15 + # via ruamel-yaml +scipy==1.16.3 + # via pymatgen +six==1.17.0 + # via python-dateutil +spglib==2.6.0 + # via pymatgen +sympy==1.14.0 + # via pymatgen +tabulate==0.9.0 + # via pymatgen +tqdm==4.67.1 + # via pymatgen +typing-extensions==4.15.0 + # via + # emmet-core + # pydantic + # pydantic-core + # spglib + # typing-inspection +typing-inspection==0.4.2 + # via + # pydantic + # pydantic-settings +tzdata==2025.2 + # via pandas +uncertainties==3.2.3 + # via pymatgen +urllib3==2.6.1 + # via requests diff --git a/mpcontribs-lux/requirements/requirements-ubuntu-latest_py3.12_extras.txt b/mpcontribs-lux/requirements/requirements-ubuntu-latest_py3.12_extras.txt new file mode 100644 index 000000000..cb109503c --- /dev/null +++ b/mpcontribs-lux/requirements/requirements-ubuntu-latest_py3.12_extras.txt @@ -0,0 +1,209 @@ +# +# This file is autogenerated by pip-compile with Python 3.12 +# by the following command: +# +# pip-compile --all-extras --output-file=requirements/requirements-ubuntu-latest_py3.12_extras.txt +# +annotated-types==0.7.0 + # via pydantic +bibtexparser==1.4.3 + # via pymatgen +blake3==1.0.8 + # via emmet-core +certifi==2025.11.12 + # via requests +cfgv==3.5.0 + # via pre-commit +charset-normalizer==3.4.4 + # via requests +contourpy==1.3.3 + # via matplotlib +coverage[toml]==7.13.0 + # via pytest-cov +cycler==0.12.1 + # via matplotlib +distlib==0.4.0 + # via virtualenv +emmet-core==0.86.2 + # via mpcontribs-lux (pyproject.toml) +execnet==2.1.2 + # via pytest-xdist +filelock==3.20.0 + # via virtualenv +flake8==7.3.0 + # via mpcontribs-lux (pyproject.toml) +fonttools==4.61.0 + # via matplotlib +identify==2.6.15 + # via pre-commit +idna==3.11 + # via requests +iniconfig==2.3.0 + # via pytest +joblib==1.5.2 + # via pymatgen +kiwisolver==1.4.9 + # via matplotlib +latexcodec==3.0.1 + # via pybtex +librt==0.7.3 + # via mypy +matplotlib==3.10.7 + # via pymatgen +mccabe==0.7.0 + # via flake8 +monty==2025.3.3 + # via + # emmet-core + # pymatgen +mpmath==1.3.0 + # via sympy +mypy==1.19.0 + # via mpcontribs-lux (pyproject.toml) +mypy-extensions==1.1.0 + # via + # mpcontribs-lux (pyproject.toml) + # mypy +narwhals==2.13.0 + # via plotly +networkx==3.6.1 + # via pymatgen +nodeenv==1.9.1 + # via pre-commit +numpy==2.3.5 + # via + # contourpy + # matplotlib + # monty + # pandas + # pymatgen + # pymatgen-io-validation + # scipy + # spglib +orjson==3.11.5 + # via pymatgen +packaging==25.0 + # via + # matplotlib + # plotly + # pytest +palettable==3.3.3 + # via pymatgen +pandas==2.3.3 + # via + # mpcontribs-lux (pyproject.toml) + # pymatgen +pathspec==0.12.1 + # via mypy +pillow==12.0.0 + # via matplotlib +platformdirs==4.5.1 + # via virtualenv +plotly==6.5.0 + # via pymatgen +pluggy==1.6.0 + # via + # pytest + # pytest-cov +pre-commit==4.5.0 + # via mpcontribs-lux (pyproject.toml) +pyarrow==22.0.0 + # via mpcontribs-lux (pyproject.toml) +pybtex==0.25.1 + # via emmet-core +pycodestyle==2.14.0 + # via + # flake8 + # mpcontribs-lux (pyproject.toml) +pydantic==2.12.5 + # via + # emmet-core + # pydantic-settings + # pymatgen-io-validation +pydantic-core==2.41.5 + # via pydantic +pydantic-settings==2.12.0 + # via + # emmet-core + # pymatgen-io-validation +pydocstyle==6.3.0 + # via mpcontribs-lux (pyproject.toml) +pyflakes==3.4.0 + # via flake8 +pygments==2.19.2 + # via pytest +pymatgen==2025.10.7 + # via + # emmet-core + # pymatgen-io-validation +pymatgen-io-validation==0.1.2 + # via emmet-core +pyparsing==3.2.5 + # via + # bibtexparser + # matplotlib +pytest==9.0.2 + # via + # mpcontribs-lux (pyproject.toml) + # pytest-cov + # pytest-xdist +pytest-cov==7.0.0 + # via mpcontribs-lux (pyproject.toml) +pytest-xdist==3.8.0 + # via mpcontribs-lux (pyproject.toml) +python-dateutil==2.9.0.post0 + # via + # matplotlib + # pandas +python-dotenv==1.2.1 + # via pydantic-settings +pytz==2025.2 + # via pandas +pyyaml==6.0.3 + # via + # pre-commit + # pybtex +requests==2.32.5 + # via + # pymatgen + # pymatgen-io-validation +ruamel-yaml==0.18.16 + # via + # monty + # pymatgen +ruamel-yaml-clib==0.2.15 + # via ruamel-yaml +scipy==1.16.3 + # via pymatgen +six==1.17.0 + # via python-dateutil +snowballstemmer==3.0.1 + # via pydocstyle +spglib==2.6.0 + # via pymatgen +sympy==1.14.0 + # via pymatgen +tabulate==0.9.0 + # via pymatgen +tqdm==4.67.1 + # via pymatgen +typing-extensions==4.15.0 + # via + # emmet-core + # mypy + # pydantic + # pydantic-core + # spglib + # typing-inspection +typing-inspection==0.4.2 + # via + # pydantic + # pydantic-settings +tzdata==2025.2 + # via pandas +uncertainties==3.2.3 + # via pymatgen +urllib3==2.6.1 + # via requests +virtualenv==20.35.4 + # via pre-commit diff --git a/mpcontribs-lux/test_data/by_user/esoteric_ephemera/r2scan_task.json.gz b/mpcontribs-lux/test_data/by_user/esoteric_ephemera/r2scan_task.json.gz new file mode 100644 index 000000000..927059554 --- /dev/null +++ b/mpcontribs-lux/test_data/by_user/esoteric_ephemera/r2scan_task.json.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:71c9f1601122bc47149203a2058980039dc794bf58c140c624983d37849096a1 +size 12382 diff --git a/mpcontribs-lux/tests/conftest.py b/mpcontribs-lux/tests/conftest.py new file mode 100644 index 000000000..55449d03a --- /dev/null +++ b/mpcontribs-lux/tests/conftest.py @@ -0,0 +1,25 @@ +"""Define common testing fixtures.""" + +import os +from pathlib import Path +import shutil +import tempfile + +import pytest + + +@pytest.fixture(autouse=True) +def test_dir(): + """Run a test in a temporary directory.""" + + old_cwd = os.getcwd() + new_path = tempfile.mkdtemp() + os.chdir(new_path) + yield + os.chdir(old_cwd) + shutil.rmtree(new_path) + + +@pytest.fixture(scope="session") +def test_data_dir() -> Path: + return (Path(__file__) / ".." / ".." / "test_data").resolve() diff --git a/mpcontribs-lux/tests/projects/esoteric_ephemera/test_schemas.py b/mpcontribs-lux/tests/projects/esoteric_ephemera/test_schemas.py new file mode 100644 index 000000000..70b6ec801 --- /dev/null +++ b/mpcontribs-lux/tests/projects/esoteric_ephemera/test_schemas.py @@ -0,0 +1,58 @@ +"""Test schemas for user esoteric_ephemera.""" + +import gzip +import json +from pathlib import Path + +import numpy as np +import pytest + +from emmet.core.math import matrix_3x3_to_voigt +from emmet.core.tasks import TaskDoc + + +@pytest.fixture(scope="module") +def task_doc(test_data_dir) -> TaskDoc: + + with gzip.open( + test_data_dir / "by_user" / "esoteric_ephemera" / "r2scan_task.json.gz", "rb" + ) as f: + return TaskDoc(**json.load(f)) + + +def test_matpes_doc_from_task_doc(test_dir, task_doc): + + from mpcontribs.lux.projects.esoteric_ephemera.schemas import MatPESTrainDoc + + matpes_train_docs = MatPESTrainDoc.from_task_doc(task_doc) + + assert len(matpes_train_docs) == sum( + len(cr.output.ionic_steps) for cr in task_doc.calcs_reversed + ) + + ctr = 0 + for cr in task_doc.calcs_reversed[::-1]: + for iistep, istep in enumerate(cr.output.ionic_steps): + assert matpes_train_docs[ctr].energy == pytest.approx(istep.e_0_energy) + assert np.allclose(matpes_train_docs[ctr].forces, istep.forces) + + assert np.allclose( + matpes_train_docs[ctr].stress, matrix_3x3_to_voigt(istep.stress) + ) + + if iistep < len(cr.output.ionic_steps) - 1: + assert matpes_train_docs[ctr].bandgap is None + assert ( + matpes_train_docs[ctr].structure.site_properties.get("magmom") + is None + ) + else: + assert matpes_train_docs[ctr].bandgap == pytest.approx( + cr.output.bandgap + ) + assert np.allclose( + matpes_train_docs[ctr].structure.site_properties.get("magmom"), + cr.output.structure.site_properties.get("magmom"), + ) + + ctr += 1 diff --git a/mpcontribs-lux/tests/test_autogen.py b/mpcontribs-lux/tests/test_autogen.py new file mode 100644 index 000000000..17b877ddb --- /dev/null +++ b/mpcontribs-lux/tests/test_autogen.py @@ -0,0 +1,92 @@ +"""Test and demo automatic generation of schemas.""" + +import gzip +from importlib_resources import files as import_module_path +import importlib.util +import json +from pathlib import Path +import sys +from tempfile import NamedTemporaryFile + +from mpcontribs.lux.autogen import SchemaGenerator + + +def dynamically_load_module_from_path(path: Path, module_name: str): + # Dynamically load a module: + # https://docs.python.org/3/library/importlib.html#importing-a-source-file-directly + spec = importlib.util.spec_from_file_location(module_name, path) + module = importlib.util.module_from_spec(spec) + sys.modules[module_name] = module + spec.loader.exec_module(module) + return module + + +def test_schema_generation(test_dir): + + base_module_path = import_module_path("mpcontribs.lux") + + temp_file = NamedTemporaryFile(suffix=".json") + with gzip.open( + ( + import_module_path("mpcontribs.lux") + / ".." + / ".." + / "examples" + / "cubic_solid_expt_data.json.gz" + ).resolve(), + "rb", + ) as source_file: + temp_file.write(json.dumps(json.load(source_file)["data"]).encode()) + + temp_file.seek(0) + + schemer = SchemaGenerator( + file_name=temp_file.name, + ) + + expected_model_fields = {"a0", "b0", "cif", "e0", "formula", "material_id"} + + expected_field_types = { + "a0": float | None, + "b0": float | None, + "cif": str | None, + "e0": float | None, + "formula": str | None, + "material_id": str | None, + } + + assert set(schemer.pydantic_model.model_fields) == expected_model_fields + + schema = schemer.schema() + + # Avoiding `eval` here; `eval` also can't handle import statements + with open(test_py_file := Path("./test_no_kwargs.py").resolve(), "wt") as py_temp: + py_temp.write(schema) + test_no_kwargs = dynamically_load_module_from_path(test_py_file, "test_no_kwargs") + + model = getattr(test_no_kwargs, schemer.pydantic_model.__name__) + assert set(model.model_fields) == expected_model_fields + assert all(not field.description for field in model.model_fields.values()) + assert all( + model.model_fields[k].annotation == anno + for k, anno in expected_field_types.items() + ) + + new_desc = {"b0": "Bulk modulus", "cif": "CIF"} + with open( + test_py_file := Path("./test_w_name_and_anno.py").resolve(), "wt" + ) as py_temp: + py_temp.write(schemer.schema(model_name="TestClass", descriptions=new_desc)) + test_w_kwargs = dynamically_load_module_from_path(test_py_file, "test_w_kwargs") + model = test_w_kwargs.TestClass + assert model.__name__ == "TestClass" + assert set(model.model_fields) == expected_model_fields + assert all( + model.model_fields[k].description == desc for k, desc in new_desc.items() + ) + assert all( + model.model_fields[k].annotation == anno + for k, anno in expected_field_types.items() + ) + + temp_file.close() diff --git a/mpcontribs-lux/tests/test_models_for_arrow_compatibility.py b/mpcontribs-lux/tests/test_models_for_arrow_compatibility.py new file mode 100644 index 000000000..00f6709ab --- /dev/null +++ b/mpcontribs-lux/tests/test_models_for_arrow_compatibility.py @@ -0,0 +1,53 @@ +import importlib +import inspect +import itertools +import os +from pathlib import Path + +import pyarrow as pa +import pytest +from emmet.core.arrow import arrowize +from pydantic._internal._model_construction import ModelMetaclass + + +def import_models(): + lux_path = Path(__file__).parent.parent.joinpath("mpcontribs/lux") + lux_models = [] + for root, dirs, files in os.walk(lux_path): + if "__pycache__" in dirs: + dirs.remove("__pycache__") + + parent_module = ".".join( + [ + "mpcontribs", + "lux", + *list( + itertools.takewhile(lambda x: x != "lux", reversed(root.split("/"))) + )[::-1], + ] + ) + + for file in files: + if file not in ["__init__.py", "__pycache__"]: + if file[-3:] != ".py": + continue + + file_name = file[:-3] + module_name = f"{parent_module}.{file_name}" + + for name, obj in inspect.getmembers( + importlib.import_module(module_name), inspect.isclass + ): + if ( + obj.__module__ == module_name + and isinstance(obj, ModelMetaclass) + and not hasattr(obj, "arrow_incompatible") + ): + lux_models.append(obj) + + return lux_models + + +@pytest.mark.parametrize("model", import_models()) +def test_document_models_for_arrow_compatibility(model): + assert isinstance(arrowize(model), pa.DataType) diff --git a/mpcontribs-lux/uv.lock b/mpcontribs-lux/uv.lock new file mode 100644 index 000000000..0fdf7d441 --- /dev/null +++ b/mpcontribs-lux/uv.lock @@ -0,0 +1,2035 @@ +version = 1 +revision = 3 +requires-python = ">=3.11" +resolution-markers = [ + "python_full_version >= '3.12' and sys_platform == 'win32'", + "python_full_version >= '3.12' and sys_platform != 'win32'", + "python_full_version < '3.12' and sys_platform == 'win32'", + "python_full_version < '3.12' and sys_platform != 'win32'", +] + +[[package]] +name = "annotated-types" +version = "0.7.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = 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