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meta.yaml
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{% set name = "scqubits" %}
{% set version = "4.1.0" %}
package:
name: {{ name|lower }}
version: {{ version }}
source:
# url: https://pypi.io/packages/source/{{ name[0] }}/{{ name }}/{{ name }}-{{ version }}.tar.gz
# sha256: b721600b0d782c9ffea03ff7cd69f7b01ed7f72f3022ff37e943881d7b17af41
path: .
build:
number: 0
skip: true # [py<37]
script: "{{ PYTHON }} -m pip install . -vv"
channels:
- conda-forge
requirements:
host:
- python
- pip
- cython >=0.29.20
- numpy >=1.14.2
build:
- python
- cython >=0.29.20
- numpy >=1.14.2
- scipy
- {{ compiler('cxx') }}
run:
- python
- cycler
- matplotlib >=3.5.1
- numpy >=1.14.2
- qutip >=4.3.1
- scipy >=1.5
- dill
- sympy
- tqdm
- typing_extensions
- h5py >=2.10
- pathos >=0.3.0
- traitlets
# Optional dependencies
- ipywidgets
- ipyvuetify
test:
requires:
- pytest
- pytest-cov
- pathos
source_files:
- scqubits/
imports:
- scqubits
commands:
- pytest -v --pyargs scqubits
- pytest -v --pyargs scqubits --num_cpus=4
about:
home: https://github.com/scqubits/scqubits
license: BSD-3-Clause
license_family: BSD
license_file: LICENSE
summary: Superconducting qubits in Python
description: |
scqubits is an open-source Python library for simulating superconducting qubits. It is meant to give the user a
convenient way to obtain energy spectra of common superconducting qubits, plot energy levels as a function of
external parameters, calculate matrix elements etc. The library further provides an interface to QuTiP, making it
easy to work with composite Hilbert spaces consisting of coupled superconducting qubits and harmonic modes.
Internally, numerics within scqubits is carried out with the help of Numpy and Scipy; plotting capabilities rely
on Matplotlib.
doc_url: https://scqubits.readthedocs.io/
dev_url: https://github.com/scqubits/scqubits
extra:
recipe-maintainers:
- jkochNU
- petergthatsme