mathspec
Write the specification (spec) of an optimisation model as a YAML file. Check it and print it as math, with no data and no solver.
A spec declares four things: the dimensions it runs over, such as snapshot
and generator; the data it expects, such as load and cost; the decisions
the solver makes, such as dispatch; and the rules those decisions obey, such
as sum(dispatch, over=generator) == load. The file below is a
complete spec.
- Check specs in CI, with no data. A wrong name or dimension fails when the file loads, and the error names the fix. Errors →
- Publish the math you solve. The equations in the paper print from the file the solver reads. Typeset →
- One spec, many tools. Engines, renderers and analysers read the spec through one public API, so no two of them can read the file differently. Program API →
- Write full-size specs. The spec of PyPSA's
n.optimize()model is one file, with stochastic, multi-period and quadratic variants. PyPSA in one file →
Example
description: Least-cost dispatch of a generator fleet against an hourly load.
dimensions:
snapshot: { dtype: int, description: dispatch periods }
generator: { description: generating units }
parameters:
capacity: { dims: [generator], description: installed capacity }
load: { dims: [snapshot], description: demand to be met }
cost: { dims: [generator], description: marginal cost }
variables:
dispatch:
description: output of a generator in a snapshot
dims: [snapshot, generator]
where: "capacity > 0"
bounds: { lower: 0, upper: capacity }
constraints:
power_balance:
dims: [snapshot]
expression: sum(dispatch, over=generator) == load
objective:
sense: minimize
expression: sum(dispatch * cost)
The math it prints
The typesetter prints the file above as math, with no data and no solver. Markdown is one of three formats, and GitHub renders it here.
Least-cost dispatch of a generator fleet against an hourly load.
Variable domains
dispatch
0 \le \mathit{dispatch}_{t,g} \le \mathrm{capacity}_{g} \qquad \forall\, t \in \mathcal{T},\ g \in \mathcal{G} \,:\, \mathrm{capacity}_{g} > 0
Objective
\min \sum_{t \in \mathcal{T},\ g \in \mathcal{G}} \mathit{dispatch}_{t,g} \cdot \mathrm{cost}_{g}
Subject to
power_balance
\sum_{g \in \mathcal{G}} \mathit{dispatch}_{t,g} = \mathrm{load}_{t} \qquad \forall\, t \in \mathcal{T}
The whole document: a symbol table, and the legend it prints
Least-cost dispatch of a generator fleet against an hourly load.
Sets
| Symbol | Meaning |
|---|---|
$\mathcal{S}$ |
index $s$ — snapshot — dispatch periods |
$\mathcal{G}$ |
index $g$ — generator — generating units |
Parameters
| Symbol | Meaning |
|---|---|
$\bar p$ |
capacity over $\mathcal{G}$ — installed capacity |
$\ell$ |
load over $\mathcal{S}$ — demand to be met |
$c$ |
cost over $\mathcal{G}$ — marginal cost |
Variables
| Symbol | Meaning |
|---|---|
$\mathit{dispatch}$ |
dispatch over $\mathcal{S} \times \mathcal{G}$ — output of a generator in a snapshot |
Variable domains
dispatch
$0 \le \mathit{dispatch}_{s,g} \le \bar p_{g} \qquad \forall\, s \in \mathcal{S},\ g \in \mathcal{G} \,:\, \bar p_{g} > 0$
Objective
$\min \sum_{s \in \mathcal{S},\ g \in \mathcal{G}} \mathit{dispatch}_{s,g} \cdot c_{g}$
Subject to
power_balance
$\sum_{g \in \mathcal{G}} \mathit{dispatch}_{s,g} = \ell_{s} \qquad \forall\, s \in \mathcal{S}$
Each format is one call:
import mathspec as ms
spec = ms.to_spec('dispatch.yaml')
ms.to_markdown(spec)
ms.to_latex(spec)
ms.to_typst(spec)
A symbol table gives the names their conventional spelling, as in the folded block. Print a spec as math does the same from a shell.
Engines and other tools
mathspec builds nothing and solves nothing itself. Instead, specsolve and linopy build a model from a spec and its data, and solve it. Support in both is work in progress. Any other tool can read the same spec through the Program API. The solid boxes are mathspec; the dashed boxes are outside it.
flowchart LR
accTitle: What mathspec does, and what other tools do with a spec
accDescr: A YAML file loads into a Spec and the Program it lowers to. mathspec checks the spec and prints it as math, with no data. Outside mathspec, drawn dashed, an engine such as specsolve or linopy reads the same spec, takes your data and returns your answers, and any other tool, such as a renderer or an analyser, reads the same spec through the Program API.
Y(["your spec<br/>one YAML file"]) --> SPEC["<b>Spec</b> and the <b>Program</b> it lowers to<br/><i>checked before any data exists</i>"]
SPEC --> CHECK["<b>check it</b><br/>python -m mathspec check"]
SPEC --> SHOW["<b>print it as math</b><br/>LaTeX · Typst · Markdown"]
SPEC -.-> OTHER["<b>your own tool</b><br/>a renderer · an analyser · …<br/>reads the Program API"]
SPEC -.-> ENGINE["<b>an engine</b><br/>specsolve · linopy<br/>builds and solves the model"]
DATA[("your data")] -.-> ENGINE
ENGINE -.-> ANS(["your answers"])
classDef outside stroke-dasharray:5 4
class ENGINE,DATA,ANS,OTHER outside
Documentation
The documentation is at https://mathspec.readthedocs.io.
Installation
See installation. To work on mathspec, see contributing.
Prior art
Every file under src/ was written in specsolve
and extracted here. The keys come from
Calliope: math in YAML, one
block per component, dims: and a where: string. sum(over=) and the
dimension rules take their names from linopy.
Status
Alpha, pre-1.0.
Breaking changes land without a deprecation cycle. Pin an exact version if you depend on this, and read the changelog before upgrading. The test suite passes every construct through the schema, the parsers and all three typeset formats, and compiles the LaTeX. The YAML that mathspec accepts can still change.
Licence
Metadata
Release files for mathspec 0.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| mathspec-0.3.0.tar.gz | 177.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mathspec-0.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 363.0 kB
Release files / mathspec-0.3.0.tar.gz
| Download URL | mathspec-0.3.0.tar.gz |
|---|---|
| Size | 177.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
16b875b6b70af859e8fffae34fbf8d3a252f7b5009c61558696411e274e8e845
|
|
BLAKE2b-256 checksum How to use checksums |
22ec0dee85ffed9e7e9af0c16e32a92d877f6767a337ec83c833bc48ea036039
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|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
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Transparency logRelease files / mathspec-0.3.0-py3-none-any.whl
| Download URL | mathspec-0.3.0-py3-none-any.whl |
|---|---|
| Size | 185.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
613f3fa1bb36bcffe490290fed42d7966529593054a4fe560392d7442b83f4f0
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BLAKE2b-256 checksum How to use checksums |
3f7e5c6f0e3c89881a247f159987d8ee12d3c985fa5b10bd572fe12eeac3766e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 15, 2026.
Transparency log