Skip to main content

A Python toolkit for producing publication-quality microeconomics diagrams.

Project description

Econ-Viz

PyPI Python License Tests Coverage

A Python toolkit for producing publication-quality microeconomics diagrams. Define utility functions declaratively, solve for consumer equilibria, and export figures as PNG, PDF, or SVG — all in a few lines of code.

Installation

pip install econ-viz

Requires Python 3.12 or later.

Quick Start

from econ_viz import Canvas, levels, solve
from econ_viz.models import CobbDouglas

model = CobbDouglas(alpha=0.5, beta=0.5)
eq    = solve(model, px=2.0, py=3.0, income=30.0)
lvls  = levels.around(eq.utility, n=5)

cvs = Canvas(x_max=20, y_max=15, x_label="x", y_label="y",
             title="Cobb-Douglas  $x^{0.5} y^{0.5}$")
cvs.add_utility(model, levels=lvls)
cvs.add_budget(2.0, 3.0, 30.0, fill=True)
cvs.add_equilibrium(eq, show_ray=True)
cvs.save("cobb_douglas.png")

Cobb-Douglas indifference map with budget line and equilibrium point

Notebook

The project ships with an interactive playground notebook:

notebook/econ-viz Playground.ipynb

Download it and open it in Jupyter, VS Code, or Colab. The first code cell upgrades econ-viz from PyPI for fresh runtimes.

Highlights

  • Built-in models: Cobb-Douglas, Leontief, Perfect Substitutes, CES, Satiation, Quasi-Linear, Stone-Geary, and Translog
  • Solver support for interior, kink, boundary, and corner solutions
  • Closed-form demand helpers with solution_tex(...)
  • Comparative tools including comparative_statics(...) and slutsky_matrix(...)
  • Multi-panel Figure layouts, PricePath / IncomePath, and linked DemandDiagram
  • CLI support for plotting and closed-form demand output

Additional Tools

Closed-form Marshallian demand in TeX:

from econ_viz import solution_tex
from econ_viz.models import CobbDouglas

tex = solution_tex(CobbDouglas(alpha=0.4, beta=0.6))

Slutsky matrix:

from econ_viz import slutsky_matrix
from econ_viz.models import CobbDouglas

S = slutsky_matrix(CobbDouglas(alpha=0.4, beta=0.6), px=2.0, py=3.0, income=60.0)
# S.s_xx, S.s_xy, S.s_yx, S.s_yy

CLI

econ-viz help
econ-viz models
econ-viz solve-tex --model cobb-douglas --symbolic-params

Plotting example:

econ-viz plot --model cobb-douglas --alpha 0.5 --beta 0.5 \
              --px 2 --py 3 --income 30 \
              --fill --show-ray \
              --output cobb_douglas.png

Documentation

Full documentation lives at econ-viz.org.

License

MIT © Anthony Sung

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

econ_viz-1.3.1.tar.gz (53.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

econ_viz-1.3.1-py3-none-any.whl (74.3 kB view details)

Uploaded Python 3

File details

Details for the file econ_viz-1.3.1.tar.gz.

File metadata

  • Download URL: econ_viz-1.3.1.tar.gz
  • Upload date:
  • Size: 53.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for econ_viz-1.3.1.tar.gz
Algorithm Hash digest
SHA256 83817e45832559cceaff9168428de1547f67a5b1f73faecd84452b8d2115c37f
MD5 a1315e80416c80ef469839320d3601b9
BLAKE2b-256 69329ffea8cb88f87df47a6abede7dca3f0f4ab78c7da26dcdb34645caa31ab5

See more details on using hashes here.

Provenance

The following attestation bundles were made for econ_viz-1.3.1.tar.gz:

Publisher: publish.yml on EconViz/econ-viz

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file econ_viz-1.3.1-py3-none-any.whl.

File metadata

  • Download URL: econ_viz-1.3.1-py3-none-any.whl
  • Upload date:
  • Size: 74.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for econ_viz-1.3.1-py3-none-any.whl
Algorithm Hash digest
SHA256 1bc19e44bb42055fedb12af72947e7b22bdaac0d4112014ab337cd875649c4a9
MD5 6dd3f7b243826373c39a3a809229eaee
BLAKE2b-256 b2f95d470bf2d7310bbd8252492b69b565d3637f8be14aa1069bcddeff7f94e9

See more details on using hashes here.

Provenance

The following attestation bundles were made for econ_viz-1.3.1-py3-none-any.whl:

Publisher: publish.yml on EconViz/econ-viz

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page