tempvars 1.0b1

Context Manager for Handling Temporary Variables

tempvars

A context manager for handling temporary variables in Jupyter Notebook, IPython, etc.

One of the most frustrating aspects of working with Jupyter notebooks (for me, anyways) is debugging a worksheet for half an hour and discovering a carried-over variable name was hanging around in the notebook namespace and causing the misbehavior. The TempVars context manager clears selected identifiers from the namespace for the duration of the with suite, then restores them afterwards (or not, if desired). Further, any variables created within the managed context that match the criteria passed to TempVars are removed from the namespace upon exiting. For convenience, all variables that were removed from the namespace at both entry and exit are stored for later reference (see example code below).

NOTE: Due to the way Python handles non-global variable scopes, TempVars can only be used at the global scope. Any attempt to use TempVars in non-global contexts will result in a RuntimeError. Viable use-cases include Jupyter notebooks, the IPython and basic Python REPLs, and the outermost scope of executed and imported modules. Preliminary testing indicates it also works with cauldron-notebook, though it may be less helpful there due to the step-local scoping paradigm used (shared values must be passed around via cauldron.shared).

NOTE ALSO that tempvars is Python 3 only.

After installing with pip install tempvars, import as:

from tempvars import TempVars

Example Jupyter notebook input:

t_var1 = 5
t_var2 = 7
x = 15
y = 20
with TempVars(names=['x']) as tv1:
    with TempVars(starts=['t_'], restore=False) as tv2:
        print('      x present inside:  ' + str('x' in dir()))
        print(' t_var1 present inside:  ' + str('t_var1' in dir()))
        print(' t_var2 present inside:  ' + str('t_var2' in dir()))
        print('        y value inside:  ' + str(y))
        print('     tv1.stored_nsvars:  ' + str(tv1.stored_nsvars))
        print('     tv2.stored_nsvars:  ' + str(tv2.stored_nsvars))
        x = -3
        t_var3 = -7
        print(' (x, t_var3, y) inside:  ' + str((x, t_var3, y)))
print('   -------------------------------')
print('        (x, y) outside:  ' + str((x, y)))
print('t_var1 present outside:  ' + str('t_var1' in dir()))
print('t_var2 present outside:  ' + str('t_var2' in dir()))
print('t_var3 present outside:  ' + str('t_var3' in dir()))
print(' tv1.retained_tempvars:  ' + str(tv1.retained_tempvars))
print(' tv2.retained_tempvars:  ' + str(tv2.retained_tempvars))

Output:

      x present inside:  False
 t_var1 present inside:  False
 t_var2 present inside:  False
        y value inside:  20
     tv1.stored_nsvars:  {'x': 15}
     tv2.stored_nsvars:  {'t_var1': 5, 't_var2': 7}
 (x, t_var3, y) inside:  (-3, -7, 20)
   -------------------------------
        (x, y) outside:  (15, 20)
t_var1 present outside:  False
t_var2 present outside:  False
t_var3 present outside:  False
 tv1.retained_tempvars:  {'x': -3}
 tv2.retained_tempvars:  {'t_var3': -7}

Administrative

Branches named with the prefix v. are volatile. The history there may be rewritten dramatically, without warning.

Available on PyPI: pip install tempvars.

Source on GitHub.

Full documentation (pending) at Read the Docs.

Copyright (c) Brian Skinn 2017

License: The MIT License. See LICENSE.txt for full license terms.