def __extend_builtins(globals_):
# TODO: Is there any advantage to manually duplicate __builtins__, instead of passing our own?
globals_['__builtins__'] = python
# Add `pythonect.lang` to Python's `__builtins__`
for name in dir(lang):
# i.e. __builtins__.print_ = pythonect.lang.print_
setattr(globals_['__builtins__'], name, getattr(lang, name))
# Add GIL
setattr(globals_['__builtins__'], '__GIL__', global_interpreter_lock)
# Fix "copyright", "credits", and "license"
setattr(globals_['__builtins__'], 'copyright', site._Printer("copyright", "Copyright (c) 2012-2013 by Itzik Kotler and others.\nAll Rights Reserved."))
setattr(globals_['__builtins__'], 'credits', site._Printer("credits", "See www.pythonect.org for more information."))
setattr(globals_['__builtins__'], 'license', site._Printer("license", "See https://github.com/ikotler/pythonect/blob/master/LICENSE", ["LICENSE"], [os.path.abspath(__file__ + "/../../../")]))
# Map eval() to Pythonect's eval, and __eval__ to Python's eval
globals_['__eval__'] = getattr(globals_['__builtins__'], 'eval')
globals_['eval'] = eval
return globals_
def __extend_builtins(globals_):
# TODO: Is there any advantage to manually duplicate __builtins__, instead of passing our own?
globals_['__builtins__'] = python
# Add `pythonect.lang` to Python's `__builtins__`
for name in dir(lang):
# i.e. __builtins__.print_ = pythonect.lang.print_
setattr(globals_['__builtins__'], name, getattr(lang, name))
# Add GIL
setattr(globals_['__builtins__'], '__GIL__', global_interpreter_lock)
# Fix "copyright", "credits", and "license"
setattr(
globals_['__builtins__'], 'copyright',
site._Printer(
"copyright",
"Copyright (c) 2012-2013 by Itzik Kotler and others.\nAll Rights Reserved."
))
setattr(
globals_['__builtins__'], 'credits',
site._Printer("credits",
"See www.pythonect.org for more information."))
setattr(
globals_['__builtins__'], 'license',
site._Printer(
"license",
"See https://github.com/ikotler/pythonect/blob/master/LICENSE",
["LICENSE"], [os.path.abspath(__file__ + "/../../../")]))
# Map eval() to Pythonect's eval, and __eval__ to Python's eval
globals_['__eval__'] = getattr(globals_['__builtins__'], 'eval')
globals_['eval'] = eval
# Default `iterate_literal_arrays`
if not '__ITERATE_LITERAL_ARRAYS__' in globals_:
globals_['__ITERATE_LITERAL_ARRAYS__'] = True
return globals_
def setscientific():
"""Set 'scientific' in __builtin__"""
import __builtin__
from site import _Printer
infos = """\
This is a standard Python interpreter with preloaded tools for scientific
computing and visualization:
>>> import numpy as np # NumPy (multidimensional arrays, linear algebra, ...)
>>> import scipy as sp # SciPy (signal and image processing library)
>>> import matplotlib as mpl # Matplotlib (2D/3D plotting library)
>>> import matplotlib.pyplot as plt # Matplotlib's pyplot: MATLAB-like syntax
>>> from pylab import * # Matplotlib's pylab interface
>>> ion() # Turned on Matplotlib's interactive mode
"""
try:
import guiqwt #analysis:ignore
infos += """
>>> import guidata # GUI generation for easy dataset editing and display
>>> import guiqwt # Efficient 2D data-plotting features
>>> import guiqwt.pyplot as plt_ # guiqwt's pyplot: MATLAB-like syntax
>>> plt_.ion() # Turned on guiqwt's interactive mode
"""
except ImportError:
pass
infos += """
Within Spyder, this interpreter also provides:
* special commands (e.g. %ls, %pwd, %clear)
* system commands, i.e. all commands starting with '!' are subprocessed
(e.g. !dir on Windows or !ls on Linux, and so on)
"""
__builtin__.scientific = _Printer("scientific", infos)
def setscientific():
"""Set 'scientific' in __builtin__"""
infos = ""
if __has_numpy:
infos += """
This is a standard Python interpreter with preloaded tools for scientific
computing and visualization. It tries to import the following modules:
>>> import numpy as np # NumPy (multidimensional arrays, linear algebra, ...)"""
if __has_scipy:
infos += """
>>> import scipy as sp # SciPy (signal and image processing library)"""
if __has_matplotlib:
infos += """
>>> import matplotlib as mpl # Matplotlib (2D/3D plotting library)
>>> import matplotlib.pyplot as plt # Matplotlib's pyplot: MATLAB-like syntax
>>> from pylab import * # Matplotlib's pylab interface
>>> ion() # Turned on Matplotlib's interactive mode"""
try:
import guiqwt #analysis:ignore
infos += """
>>> import guidata # GUI generation for easy dataset editing and display
>>> import guiqwt # Efficient 2D data-plotting features
>>> import guiqwt.pyplot as plt_ # guiqwt's pyplot: MATLAB-like syntax
>>> plt_.ion() # Turned on guiqwt's interactive mode"""
except ImportError:
pass
if __has_numpy:
infos += "\n"
infos += """
Within Spyder, this interpreter also provides:
* special commands (e.g. %ls, %cd, %pwd, %clear)
- %ls: List files in the current directory
- %cd dir: Change to directory dir
- %pwd: Show current directory
- %clear x: Remove variable x from namespace
"""
try:
# Python 2
import __builtin__ as builtins
except ImportError:
# Python 3
import builtins
try:
from site import _Printer
except ImportError:
# Python 3.4
from _sitebuiltins import _Printer
builtins.scientific = _Printer("scientific", infos)
def setscientific():
"""Set 'scientific' in __builtin__"""
infos = ""
if __has_numpy:
infos += """
This is a standard Python interpreter with preloaded tools for scientific
computing and visualization. It tries to import the following modules:
>>> import numpy as np # NumPy (multidimensional arrays, linear algebra, ...)"""
if __has_scipy:
infos += """
>>> import scipy as sp # SciPy (signal and image processing library)"""
if __has_matplotlib:
infos += """
>>> import matplotlib as mpl # Matplotlib (2D/3D plotting library)
>>> import matplotlib.pyplot as plt # Matplotlib's pyplot: MATLAB-like syntax
>>> from pylab import * # Matplotlib's pylab interface
>>> ion() # Turned on Matplotlib's interactive mode"""
try:
import guiqwt #analysis:ignore
infos += """
>>> import guidata # GUI generation for easy dataset editing and display
>>> import guiqwt # Efficient 2D data-plotting features
>>> import guiqwt.pyplot as plt_ # guiqwt's pyplot: MATLAB-like syntax
>>> plt_.ion() # Turned on guiqwt's interactive mode"""
except ImportError:
pass
if __has_numpy:
infos += "\n"
infos += """
Within Spyder, this interpreter also provides:
* special commands (e.g. %ls, %cd, %pwd, %clear)
- %ls: List files in the current directory
- %cd dir: Change to directory dir
- %pwd: Show current directory
- %clear x: Remove variable x from namespace
"""
try:
# Python 2
import __builtin__ as builtins
except ImportError:
# Python 3
import builtins
try:
from site import _Printer
except ImportError:
# Python 3.4
from _sitebuiltins import _Printer
builtins.scientific = _Printer("scientific", infos)
def setscientific():
"""Set 'scientific' in __builtin__"""
import __builtin__
from site import _Printer
infos = ""
if __has_numpy:
infos += """
This is a standard Python interpreter with preloaded tools for scientific
computing and visualization. It tries to import the following modules:
>>> import numpy as np # NumPy (multidimensional arrays, linear algebra, ...)"""
if __has_scipy:
infos += """
>>> import scipy as sp # SciPy (signal and image processing library)"""
if __has_matplotlib:
infos += """
>>> import matplotlib as mpl # Matplotlib (2D/3D plotting library)
>>> import matplotlib.pyplot as plt # Matplotlib's pyplot: MATLAB-like syntax
>>> from pylab import * # Matplotlib's pylab interface
>>> ion() # Turned on Matplotlib's interactive mode"""
try:
import guiqwt #analysis:ignore
infos += """
>>> import guidata # GUI generation for easy dataset editing and display
>>> import guiqwt # Efficient 2D data-plotting features
>>> import guiqwt.pyplot as plt_ # guiqwt's pyplot: MATLAB-like syntax
>>> plt_.ion() # Turned on guiqwt's interactive mode"""
except ImportError:
pass
if __has_numpy:
infos += "\n"
infos += """
Within Spyder, this interpreter also provides:
* special commands (e.g. %ls, %pwd, %clear)
* system commands, i.e. all commands starting with '!' are subprocessed
(e.g. !dir on Windows or !ls on Linux, and so on)
"""
__builtin__.scientific = _Printer("scientific", infos)
