A minimal Python kernel, so you can run Python in your Python.
All the clever stuff in this library is provided by Python's builtin ast
module and compilation/exec/eval system, along with IPython's CachingCompiler
which does some deep magic. tinykernel
just brings them together with a little glue.
With pip:
pip install tinykernel
With conda:
conda install -c fastai tinykernel
This library provides a single class, TinyKernel
, which is a tiny persistent kernel for Python code:
k = TinyKernel()
Call it, passing Python code, to have the code executed in a separate Python environment:
k("a=1")
Expressions return the value of the expression:
k('a')
1
All variables are persisted across calls:
k("a+=1")
k('a')
2
Multi-line inputs are supported. If the last line is an expression, it is returned:
k("""import types
b = types.SimpleNamespace(foo=a)
b""")
namespace(foo=2)
The original source code is stored, so inspect.getsource
works and, tracebacks have full details.
k("""def f(): pass # a comment
import inspect
inspect.getsource(f)""")
'def f(): pass # a comment\n'
When creating a TinyKernel
, you can pass a dict of globals to initialize the environment:
k = TinyKernel(glb={'foo':'bar'})
k('foo*2')
'barbar'
Pass name
to customize the string that appears in tracebacks ("kernel" by default):
k = TinyKernel(name='myapp')
code = '''def f():
return 1/0
print(f())'''
try: k(code)
except Exception as e: print(traceback.format_exc())
Traceback (most recent call last):
File "<ipython-input-37-8b370e64c5cb>", line 5, in <module>
try: k(code)
File "/home/jhoward/git/tinykernel/tinykernel/__init__.py", line 20, in __call__
if expr: return self._run(Expression(expr.value), nm, 'eval')
File "/home/jhoward/git/tinykernel/tinykernel/__init__.py", line 12, in _run
def _run(self, p, nm, mode='exec'): return eval(compiler(p, nm, mode), self.glb)
File "<myapp--1-57331cf14e08>", line 3, in <module>
print(f())
File "<myapp--1-57331cf14e08>", line 2, in f
return 1/0
ZeroDivisionError: division by zero
Thanks to Christopher Prohm, Matthias Bussonnier, and Aaron Meurer for their helpful insights in this twitter thread.