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copied!<h2>Units</h2> <p>A solution would be to gather all units from the SymPy <code>units</code> module and use them to substitute the symbols created by <code>sympify</code></p> <pre><code>>>> import sympy.physics.units as u ... subs = {} ... for k, v in u.__dict__.items(): ... if isinstance(v, Expr) and v.has(u.Unit): ... subs[Symbol(k)] = v # Map the `Symbol` for a unit to the unit >>> # sympify returns `Symbol`s, `subs` maps them to `Unit`s >>> print sympify('yard*millimeter/ly').subs(subs) 127*m/1313990343414000000000 </code></pre> <p>If the symbol is not in <code>units</code> it will just be printed as unknown symbol (for instance <code>barn</code>)</p> <pre><code>>>> print sympify('barn/meter**2').subs(subs) barn/m**2 </code></pre> <p>But you can always add stuff to the <code>subs</code> dictionary.</p> <pre><code>>>> subs[Symbol('almost_meter')] = 0.9*u.meter ... sympify('almost_meter').subs(subs) 0.9*m </code></pre> <p>SI prefixes don't work exactly like you want them. You will need to add a multiplication sign (or hope that it is a common unit like <code>km</code> which is explicitly implemented). Moreover, as they are not <code>Unit</code> instances but rather <code>Integer</code> instance you will have to add them to <code>subs</code>:</p> <pre><code>>>> import sympy.physics.units as u ... subs = {} ... for k, v in u.__dict__.items(): ... if (isinstance(v, Expr) and v.has(u.Unit)) or isinstance(v, Integer): ... subs[Symbol(k)] = v >>> print sympify('mega*m').subs(subs) 1000000*m </code></pre> <p>For unicode you might need some preprocessing. I do not think SymPy makes any promises about unicode support.</p> <p>If you implement new <code>Unit</code>s, please consider making a pull request with them on github. The file to edit should be <code>sympy/physics/units.py</code>.</p> <h2>Whitespaces and implicit multiplication</h2> <p>In the dev version of SymPy you can find code for assuming implicit multiplications where appropriate whitespaces are written:</p> <pre><code>>>> from sympy.parsing.sympy_parser import (parse_expr, ... standard_transformations, implicit_multiplication_application) >>> parse_expr("10sin**2 x**2 + 3xyz + tan theta", ... transformations=(standard_transformations + ... (implicit_multiplication_application,))) 3*x*y*z + 10*sin(x**2)**2 + tan(theta) </code></pre> <h2>Security</h2> <p><code>sympify</code> uses <code>eval</code> which is exploitable if you are going to use it for a web facing app!</p>

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