pymatgen

name	pymatgen
description	Analyze, validate, convert, and transform materials structures and computed materials data with current pymatgen APIs, including local phase diagrams, symmetry sensitivity, electronic-structure I/O, and explicitly bounded Materials Project queries.
license	MIT
compatibility	Python 3.11+ with uv. The verified snapshot uses pymatgen 2026.5.4, pymatgen-core 2026.7.16, and mp-api 0.46.4. Bundled help and planning CLIs use only the standard library; local scientific execution lazily requires the pinned pymatgen packages. Materials Project access additionally requires explicit network approval and the single named secret MP_API_KEY.
allowed-tools	["Read","Write","Bash","Glob","Python"]
metadata	{"version":"1.2","skill-author":"K-Dense Inc.","last-reviewed":"2026-07-23"}

pymatgen

Use pymatgen for explicit, provenance-preserving work with compositions, molecules, periodic structures, computed entries, symmetry, phase diagrams, electronic structures, and electronic-structure-code files. Treat every parse, conversion, symmetry assignment, transformation, and database result as method- and parameter-dependent.

The MIT frontmatter license covers this skill. pymatgen and pymatgen-core are MIT; mp-api declares BSD-3-Clause-LBNL. Materials Project data is generally CC BY 4.0, while contributed data remains owned by its contributors. Check the exact artifact and data terms before redistribution.

Verified snapshot (2026-07-23)

• pymatgen==2026.5.4 is the latest stable wrapper release (2026-05-04). Package metadata requires Python 3.11+ and directly requires pymatgen-core>=2026.4.16.
• pymatgen-core==2026.7.16 is the latest stable core release (2026-07-16). It now contains core objects, symmetry/lattice operations, and the I/O layer, all under the existing pymatgen.* namespace.
• mp-api==0.46.4 is the latest stable Materials Project client (2026-06-15), requires Python 3.11+, and depends on pymatgen>2024.2.20.
• The current API site is built from 2026.7.16 core documentation. Pinning both distributions prevents pymatgen==2026.5.4 from silently resolving to a different future core.
• Pymatgen uses date-based versions. PyPI renders the date with dots; do not infer semantic-version compatibility from the numbers.

Create a project lock for reproducibility:

uv init --python 3.11
uv add "pymatgen==2026.5.4" "pymatgen-core==2026.7.16" "mp-api==0.46.4"
uv lock
uv sync --frozen

For a disposable reviewed environment:

uv venv --python 3.11 .venv-pymatgen
uv pip install --python .venv-pymatgen/bin/python \
  "pymatgen==2026.5.4" "pymatgen-core==2026.7.16" "mp-api==0.46.4"

Direct pins do not freeze all transitive wheels. Preserve uv.lock, platform, Python version, package versions, and artifact hashes.

Required workflow

1. State whether the object is a non-periodic Molecule or periodic Structure; record lattice and periodic boundary conditions.
2. State units. Pymatgen commonly uses Å, degrees, eV, eV/atom, amu, and g/cm³, but each API's documented contract is authoritative.
3. State coordinate mode. Structure coordinates are fractional unless coords_are_cartesian=True; Molecule coordinates are Cartesian.
4. Inspect every parser warning. For CIF, preserve occupancy, site-merging, stoichiometry, and correction warnings; do not silently accept fixes.
5. Report disorder/partial occupancies and oxidation-state decoration. Never guess oxidation states implicitly.
6. Run validation before symmetry, neighbor, transformation, conversion, or thermodynamic analysis.
7. Sweep symmetry tolerances and report symprec in Å and angle_tolerance in degrees with every assignment.
8. Treat transformations as new artifacts. Preserve the input, parameters, software versions, warnings, and parent/child checksums.
9. Before conversion, identify representation loss. Write only to a new path and round-trip-check scientifically relevant properties.
10. Build phase diagrams only from compatible total energies and correction schemes. A computed hull is conditional on the supplied entry set.
11. Keep all database access off by default. Disclose endpoint, filters, fields, result limit, cache behavior, output, license, and citation before an explicit execution step.
12. Preserve an artifact manifest. Never use pickle or load an untrusted general object graph; use schema-validated JSON and explicit constructors.

Core objects

Use the public convenience imports:

from pymatgen.core import Composition, Element, Lattice, Molecule, Structure

composition = Composition("LiFePO4", strict=True)
iron = Element("Fe")

lattice = Lattice.cubic(5.64)  # Å
structure = Structure(
    lattice,
    ["Na", "Cl"],
    [[0, 0, 0], [0.5, 0.5, 0.5]],
    coords_are_cartesian=False,
    validate_proximity=True,
)

molecule = Molecule(
    ["O", "H", "H"],
    [[0.0, 0.0, 0.0], [0.758, 0.0, 0.504], [-0.758, 0.0, 0.504]],
    charge=0,
    spin_multiplicity=1,
)

Structure and Molecule are mutable; use IStructure/IMolecule or an explicit copy when mutation would compromise provenance. See core classes.

Safe local structure intake

Prefer the bundled validator, which captures CIF and Python warnings and reports units, occupancy, disorder, oxidation states, periodicity, coordinate mode, and minimum distances:

python scripts/composition_structure_validator.py composition "Fe2O3"
python scripts/composition_structure_validator.py structure structure.cif
python scripts/structure_analyzer.py structure.cif --symmetry

For direct CIF work, use the current parser method and inspect both warning channels:

import warnings
from pymatgen.io.cif import CifParser

with warnings.catch_warnings(record=True) as caught:
    warnings.simplefilter("always")
    parser = CifParser("input.cif", check_cif=True)
    structures = parser.parse_structures(
        primitive=False,
        check_occu=True,
        on_error="raise",
    )

parser_messages = list(parser.warnings)
python_messages = [str(item.message) for item in caught]

Do not parse untrusted files in a privileged process. A critical malicious-CIF code-execution flaw affected pymatgen through 2024.2.8 and was fixed in 2024.2.20; the pinned release is newer, but parsers still process attacker controlled input. Use isolation and CPU/RAM/disk/time limits.

Symmetry

Space-group assignment depends on tolerances and structure quality:

from pymatgen.symmetry.analyzer import SpacegroupAnalyzer

analyzer = SpacegroupAnalyzer(
    structure,
    symprec=0.01,          # Å
    angle_tolerance=5.0,   # degrees
)
symbol = analyzer.get_space_group_symbol()
number = analyzer.get_space_group_number()

The Materials Project pipeline commonly uses symprec=0.1 Å, while pymatgen's documented default is 0.01 Å; these can produce different assignments. Generate a sensitivity report instead of changing tolerance until a preferred answer appears:

python scripts/symmetry_sensitivity_report.py structure.cif \
  --symprec 0.001,0.01,0.1 --angle-tolerance 1,5

See analysis modules.

Conversion and parser/writer I/O

Plan first; the planner does not open files or import pymatgen:

python scripts/io_conversion_plan.py \
  --input input.cif --input-format cif \
  --output POSCAR.new --output-format poscar \
  --periodic --coordinate-mode direct

Then convert to a new path with explicit loss acknowledgement:

python scripts/structure_converter.py input.cif POSCAR.new \
  --output-format poscar --coordinate-mode direct --allow-lossy \
  --acknowledge-parser-warnings

CIF, POSCAR, XYZ, and JSON do not preserve the same semantics. Check lattice, periodicity, coordinate mode, species ordering, selective dynamics, site properties, oxidation states, labels, and disorder after every conversion. See I/O formats.

Transformations and provenance

Transform a copy and preserve history:

from pymatgen.alchemy.materials import TransformedStructure
from pymatgen.transformations.standard_transformations import (
    SubstitutionTransformation,
    SupercellTransformation,
)

tracked = TransformedStructure(structure.copy(), [])
tracked.append_transformation(SupercellTransformation([2, 2, 2]))
tracked.append_transformation(SubstitutionTransformation({"Na": "K"}))
derived = tracked.final_structure
history = tracked.history

One-to-many ordering, doping, slab, and magnetic transformations can expand combinatorially or invoke optional executables. Bound candidates, sites, supercell size, runtime, and output count. See transformations and workflows.

Local phase diagrams

The bundled generator is offline and accepts only a strict JSON schema with total eV per entry and provenance:

{
  "schema_version": "1.0",
  "energy_unit": "eV",
  "energy_basis": "total_per_entry",
  "provenance": {
    "source": "reviewed local calculations",
    "method": "one compatible energy/correction scheme"
  },
  "entries": [
    {
      "entry_id": "local-Li",
      "composition": "Li",
      "energy_eV": -1.0,
      "provenance": {"source": "calculation manifest sha256:..."}
    }
  ]
}

python scripts/phase_diagram_generator.py entries.json --analyze Li2O

Elemental endpoints and all competing phases must be present. Do not mix raw energies from different functionals, pseudopotentials, magnetic states, or correction conventions. Computed on-hull status is not experimental stability.

Band structures, DOS, VASP, and Q-Chem

Parse only the data needed:

from pymatgen.io.vasp import Vasprun

run = Vasprun(
    "vasprun.xml",
    parse_dos=True,
    parse_eigen=True,
    parse_projected_eigen=False,
    parse_potcar_file=False,
)
band_structure = run.get_band_structure(line_mode=True)
band_gap = band_structure.get_band_gap()
complete_dos = run.complete_dos

Projected eigenvalues can require extreme memory. Verify convergence, k-path, spin/SOC settings, Fermi-level conventions, smearing, and projection basis before interpreting gaps or DOS. A parser success is not a converged calculation.

Current Q-Chem interfaces are pymatgen.io.qchem.inputs.QCInput and pymatgen.io.qchem.outputs.QCOutput:

from pymatgen.io.qchem.inputs import QCInput

job = QCInput(
    molecule,
    rem={"job_type": "sp", "method": "wb97x-v", "basis": "def2-svpd"},
)
text = str(job)

Pymatgen writes inputs and parses outputs; it does not grant a VASP or Q-Chem license or establish method validity. POTCAR files are VASP-licensed and are not distributed by pymatgen. Never redistribute them or scan unrelated directories for them. Optional tools such as enumlib, Bader, packmol, ffmpeg, and Zeo++ are native/external executables: review provenance, licenses, argv, working directory, and resource limits before a separate explicit invocation.

Materials Project: plan before network

Use only:

from mp_api.client import MPRester

The client reads MP_API_KEY when constructed. Supply only that named environment variable through the user's shell or secret manager. Do not accept the key as a CLI argument, traverse .env files, dump environment variables, or print exception data without redaction.

Dry-run planning is the default:

python scripts/mp_query.py \
  --chemsys Li-Fe-O \
  --energy-above-hull 0 0.05 \
  --fields formula_pretty,energy_above_hull,band_gap,origins \
  --limit 25

Only --execute permits one bounded summary query and requires a new output:

python scripts/mp_query.py \
  --material-id mp-149 \
  --fields formula_pretty,structure,origins,last_updated \
  --limit 1 --output mp-149.json --execute

The CLI sets num_chunks=1, requires explicit fields and filters, caps results, does not implement an implicit result cache, and never overwrites output. MPRester initialization also performs compatibility/heartbeat metadata requests; the plan discloses these, disables the platform-detail user agent and local database-version notification log, and records the returned database version. The summary workflow does not request full-dataset cache downloads. mp-api 0.46.4 retries HTTP 429/502/504 according to its own configured policy and respects Retry-After; do not invent a numeric service quota or add an unbounded retry loop.

Materials Project core values are computed, method-dependent data—not experimental truth. PBE commonly overestimates lattice parameters and systematically underestimates band gaps; aggregated values can change across database releases. Preserve retrieval time, query, fields, material/task origins, database release when available, client versions, CC BY attribution, and the canonical plus property-specific citations. See Materials Project API.

Bundled CLIs

All CLIs have dependency-free --help, lazy scientific imports, bounded JSON, and no implicit network:

• scripts/composition_structure_validator.py — strict composition/structure checks; optional oxidation-state guessing is explicit and bounded.
• scripts/structure_analyzer.py — bounded lattice, sites, symmetry, distance, and optional CrystalNN report.
• scripts/symmetry_sensitivity_report.py — tolerance-grid space groups.
• scripts/io_conversion_plan.py — dependency-free representation-loss plan.
• scripts/structure_converter.py — one-file conversion to a new path.
• scripts/phase_diagram_generator.py — strict local computed-entry hull.
• scripts/mp_query.py — dry-run MP query plan and opt-in bounded client.
• scripts/artifact_manifest.py — checksums, versions, sources, and provenance.

Use:

python scripts/artifact_manifest.py \
  --artifact input.cif --artifact analysis.json \
  --workflow "local symmetry sensitivity" --output manifest.json

References

• Core classes
• I/O formats, VASP, and Q-Chem
• Analysis, symmetry, phase diagrams, bands, and DOS
• Transformations and workflows
• Materials Project API, provenance, license, and limits

Sources (verified 2026-07-23)

• pymatgen 2026.5.4 on PyPI
• pymatgen-core 2026.7.16 on PyPI
• pymatgen API documentation
• pymatgen changelog
• mp-api 0.46.4 on PyPI
• Materials Project API getting started
• Materials Project query guide
• Materials Project FAQ and computed-data caveats
• Materials Project citation page
• Official tutorial series endorsed by pymatgen