sym provides a unified wrapper to some symbolic manipulation libraries in Python. It makes it easy for library authors to test their packages against several symbolic manipulation libraries.
Currently the following Python pacakges are available as “backends”:
The capabilities exposed here are those needed by
and include:
Differentiation
Numerical evaluation (including “lambdify” support)
see tests for examples. Note that pyodesys and pyneqsys also act as test suits for this package.
Documentation
Auto-generated API documentation for the latest stable release is found here: https://bjodah.github.io/sym/latest (and the development version for the current master branch is found here: http://hera.physchem.kth.se/~sym/branches/master/html).
Installation
Simplest way to install sym and its (optional) dependencies is to use pip:
$ pip install --user sym pytest $ python -m pytest --pyargs sym
or the conda package manager:
$ conda install -c bjodah sym pytest $ python -m pytest --pyargs sym
Source distribution is available here: https://pypi.python.org/pypi/sym
Example
Differentiation
>>> from sym import Backend
>>> be = Backend('pysym') # just an example, use SymPy rather than pysym
>>> x, y = map(be.Symbol, 'x y'.split())
>>> expr = x*y**2 - be.tan(2*x)
>>> print(expr.diff(x))
((y**2) - ((1 + (tan((2*x))**2))*2))for more examples, see examples/, and rendered jupyter notebooks here: http://hera.physchem.kth.se/~sym/master/examples
License
The source code is Open Source and is released under the simplified 2-clause BSD license. See LICENSE for further details. Contributors are welcome to suggest improvements at https://github.com/bjodah/sym
1 maintainer
Release files for sym 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 | |
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| sym-0.3.0.tar.gz | 16.1 kB | Details |
Release files / sym-0.3.0.tar.gz
| Download URL | sym-0.3.0.tar.gz |
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| Size | 16.1 kB |
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