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7600bc7a-33a5-4e67-a7d5-2b3c2d6edf4a
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file://datasets/cpython/Doc/faq/programming.rst
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Note that using a module is also the basis for implementing the singleton design pattern, for the same reason. What are the "best practices" for using import in a module? -----------------------------------------------------------
trusted_official_docs
CPython Docs
Note that using a module is also the basis for implementing the singleton design pattern, for the same reason. What are the "best practices" for using import in a module? -----------------------------------------------------------
Note that using a module is also the basis for implementing the singleton design pattern, for the same reason. What are the "best practices" for using import in a module? -----------------------------------------------------------
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exports (globals, functions, and classes that don't need imported base classes) * ``import`` statements * active code (including globals that are initialized from imported values). Van Rossum doesn't like this approach much because the imports appear in a strange place, but it does work.
trusted_official_docs
CPython Docs
exports (globals, functions, and classes that don't need imported base classes) * ``import`` statements * active code (including globals that are initialized from imported values). Van Rossum doesn't like this approach much because the imports appear in a strange place, but it does work.
exports (globals, functions, and classes that don't need imported base classes) * ``import`` statements * active code (including globals that are initialized from imported values). Van Rossum doesn't like this approach much because the imports appear in a strange place, but it does work.
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What is self? ------------- Self is merely a conventional name for the first argument of a method. A method defined as ``meth(self, a, b, c)`` should be called as ``x.meth(a, b, c)`` for some instance ``x`` of the class in which the definition occurs; the called method will think it is called as ``meth(x, a, b, c)``.
trusted_official_docs
CPython Docs
What is self? ------------- Self is merely a conventional name for the first argument of a method. A method defined as ``meth(self, a, b, c)`` should be called as ``x.meth(a, b, c)`` for some instance ``x`` of the class in which the definition occurs; the called method will think it is called as ``meth(x, a, b, c)``.
What is self? ------------- Self is merely a conventional name for the first argument of a method. A method defined as ``meth(self, a, b, c)`` should be called as ``x.meth(a, b, c)`` for some instance ``x`` of the class in which the definition occurs; the called method will think it is called as ``meth(x, a, b, c)``.
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x >>> x = x + 1 # 5 can't be mutated, we are creating a new object here >>> x 6 >>> y 5 we can see that in this case ``x`` and ``y`` are not equal anymore. This is because integers are :term:`immutable`, and when we do ``x = x + 1`` we are not mutating the int ``5`` by incrementing its value; instead, we are creating a...
trusted_official_docs
CPython Docs
x >>> x = x + 1 # 5 can't be mutated, we are creating a new object here >>> x 6 >>> y 5 we can see that in this case ``x`` and ``y`` are not equal anymore. This is because integers are :term:`immutable`, and when we do ``x = x + 1`` we are not mutating the int ``5`` by incrementing its value; instead, we are creating a...
x >>> x = x + 1 # 5 can't be mutated, we are creating a new object here >>> x 6 >>> y 5 we can see that in this case ``x`` and ``y`` are not equal anymore. This is because integers are :term:`immutable`, and when we do ``x = x + 1`` we are not mutating the int ``5`` by incrementing its value; instead, we are creating a...
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What are the "best practices" for using import in a module? ----------------------------------------------------------- In general, don't use ``from modulename import *``. Doing so clutters the importer's namespace, and makes it much harder for linters to detect undefined names.
trusted_official_docs
CPython Docs
What are the "best practices" for using import in a module? ----------------------------------------------------------- In general, don't use ``from modulename import *``. Doing so clutters the importer's namespace, and makes it much harder for linters to detect undefined names.
What are the "best practices" for using import in a module? ----------------------------------------------------------- In general, don't use ``from modulename import *``. Doing so clutters the importer's namespace, and makes it much harder for linters to detect undefined names.
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w, h = 2, 3 A = [[None] * w for i in range(h)] Or, you can use an extension that provides a matrix datatype; `NumPy <https://numpy.org/>`_ is the best known.
trusted_official_docs
CPython Docs
w, h = 2, 3 A = [[None] * w for i in range(h)] Or, you can use an extension that provides a matrix datatype; `NumPy <https://numpy.org/>`_ is the best known.
w, h = 2, 3 A = [[None] * w for i in range(h)] Or, you can use an extension that provides a matrix datatype; `NumPy <https://numpy.org/>`_ is the best known.
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>>> c = C() >>> isinstance(c, C) # direct True >>> isinstance(c, P) # indirect True >>> isinstance(c, Mapping) # virtual True # Actual inheritance chain >>> type(c).__mro__ (<class 'C'>, <class 'P'>, <class 'object'>)
trusted_official_docs
CPython Docs
>>> c = C() >>> isinstance(c, C) # direct True >>> isinstance(c, P) # indirect True >>> isinstance(c, Mapping) # virtual True # Actual inheritance chain >>> type(c).__mro__ (<class 'C'>, <class 'P'>, <class 'object'>)
>>> c = C() >>> isinstance(c, C) # direct True >>> isinstance(c, P) # indirect True >>> isinstance(c, Mapping) # virtual True # Actual inheritance chain >>> type(c).__mro__ (<class 'C'>, <class 'P'>, <class 'object'>)
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... >>> B = A >>> a = B() >>> b = a >>> print(b) <__main__.A object at 0x16D07CC> >>> print(a) <__main__.A object at 0x16D07CC> Arguably the class has a name: even though it is bound to two names and invoked through the name ``B`` the created instance is still reported as an instance of class ``A``. However, it is impo...
trusted_official_docs
CPython Docs
... >>> B = A >>> a = B() >>> b = a >>> print(b) <__main__.A object at 0x16D07CC> >>> print(a) <__main__.A object at 0x16D07CC> Arguably the class has a name: even though it is bound to two names and invoked through the name ``B`` the created instance is still reported as an instance of class ``A``. However, it is impo...
... >>> B = A >>> a = B() >>> b = a >>> print(b) <__main__.A object at 0x16D07CC> >>> print(a) <__main__.A object at 0x16D07CC> Arguably the class has a name: even though it is bound to two names and invoked through the name ``B`` the created instance is still reported as an instance of class ``A``. However, it is impo...
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CPython Docs
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>>> a = 0o10 >>> a 8 Hexadecimal is just as easy. Simply precede the hexadecimal number with a zero, and then a lower or uppercase "x". Hexadecimal digits can be specified in lower or uppercase. For example, in the Python interpreter::
trusted_official_docs
CPython Docs
>>> a = 0o10 >>> a 8 Hexadecimal is just as easy. Simply precede the hexadecimal number with a zero, and then a lower or uppercase "x". Hexadecimal digits can be specified in lower or uppercase. For example, in the Python interpreter::
>>> a = 0o10 >>> a 8 Hexadecimal is just as easy. Simply precede the hexadecimal number with a zero, and then a lower or uppercase "x". Hexadecimal digits can be specified in lower or uppercase. For example, in the Python interpreter::
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The same is true of the various assignment operators (``=``, ``+=``, and so on). They are not truly operators but syntactic delimiters in assignment statements. Is there an equivalent of C's "?:" ternary operator? ----------------------------------------------------
trusted_official_docs
CPython Docs
The same is true of the various assignment operators (``=``, ``+=``, and so on). They are not truly operators but syntactic delimiters in assignment statements. Is there an equivalent of C's "?:" ternary operator? ----------------------------------------------------
The same is true of the various assignment operators (``=``, ``+=``, and so on). They are not truly operators but syntactic delimiters in assignment statements. Is there an equivalent of C's "?:" ternary operator? ----------------------------------------------------
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Is it possible to write obfuscated one-liners in Python? -------------------------------------------------------- Yes. Usually this is done by nesting :keyword:`lambda` within :keyword:`!lambda`. See the following three examples, slightly adapted from Ulf Bartelt::
trusted_official_docs
CPython Docs
Is it possible to write obfuscated one-liners in Python? -------------------------------------------------------- Yes. Usually this is done by nesting :keyword:`lambda` within :keyword:`!lambda`. See the following three examples, slightly adapted from Ulf Bartelt::
Is it possible to write obfuscated one-liners in Python? -------------------------------------------------------- Yes. Usually this is done by nesting :keyword:`lambda` within :keyword:`!lambda`. See the following three examples, slightly adapted from Ulf Bartelt::
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one imports the same basic module, the basic module would be parsed and re-parsed many times. To force re-reading of a changed module, do this:: import importlib import modname importlib.reload(modname)
trusted_official_docs
CPython Docs
one imports the same basic module, the basic module would be parsed and re-parsed many times. To force re-reading of a changed module, do this:: import importlib import modname importlib.reload(modname)
one imports the same basic module, the basic module would be parsed and re-parsed many times. To force re-reading of a changed module, do this:: import importlib import modname importlib.reload(modname)
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call :meth:`!__del__` directly -- :meth:`!__del__` should call ``close()`` and ``close()`` should make sure that it can be called more than once for the same object. Another way to avoid cyclical references is to use the :mod:`weakref` module, which allows you to point to objects without incrementing their reference co...
trusted_official_docs
CPython Docs
call :meth:`!__del__` directly -- :meth:`!__del__` should call ``close()`` and ``close()`` should make sure that it can be called more than once for the same object. Another way to avoid cyclical references is to use the :mod:`weakref` module, which allows you to point to objects without incrementing their reference co...
call :meth:`!__del__` directly -- :meth:`!__del__` should call ``close()`` and ``close()`` should make sure that it can be called more than once for the same object. Another way to avoid cyclical references is to use the :mod:`weakref` module, which allows you to point to objects without incrementing their reference co...
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CPython Docs
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def __init__(self, station_id): self._station_id = station_id # The _station_id is private and immutable def current_temperature(self): "Latest hourly observation" # Do not cache this because old results # can be out of date.
trusted_official_docs
CPython Docs
def __init__(self, station_id): self._station_id = station_id # The _station_id is private and immutable def current_temperature(self): "Latest hourly observation" # Do not cache this because old results # can be out of date.
def __init__(self, station_id): self._station_id = station_id # The _station_id is private and immutable def current_temperature(self): "Latest hourly observation" # Do not cache this because old results # can be out of date.
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The following packages can help with the creation of console and GUI executables: * `Nuitka <https://nuitka.net/>`_ (Cross-platform) * `PyInstaller <https://pyinstaller.org/>`_ (Cross-platform) * `PyOxidizer <https://pyoxidizer.readthedocs.io/en/stable/>`_ (Cross-platform) * `cx_Freeze <https://marcelotduarte.github.io...
trusted_official_docs
CPython Docs
The following packages can help with the creation of console and GUI executables: * `Nuitka <https://nuitka.net/>`_ (Cross-platform) * `PyInstaller <https://pyinstaller.org/>`_ (Cross-platform) * `PyOxidizer <https://pyoxidizer.readthedocs.io/en/stable/>`_ (Cross-platform) * `cx_Freeze <https://marcelotduarte.github.io...
The following packages can help with the creation of console and GUI executables: * `Nuitka <https://nuitka.net/>`_ (Cross-platform) * `PyInstaller <https://pyinstaller.org/>`_ (Cross-platform) * `PyOxidizer <https://pyoxidizer.readthedocs.io/en/stable/>`_ (Cross-platform) * `cx_Freeze <https://marcelotduarte.github.io...
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it from. However, if you need an object with the ability to modify in-place Unicode data, try using an :class:`io.StringIO` object or the :mod:`array` module:: >>> import io >>> s = "Hello, world" >>> sio = io.StringIO(s) >>> sio.getvalue() 'Hello, world' >>> sio.seek(7) 7 >>> sio.write("there!") 6 >>> sio.get...
trusted_official_docs
CPython Docs
it from. However, if you need an object with the ability to modify in-place Unicode data, try using an :class:`io.StringIO` object or the :mod:`array` module:: >>> import io >>> s = "Hello, world" >>> sio = io.StringIO(s) >>> sio.getvalue() 'Hello, world' >>> sio.seek(7) 7 >>> sio.write("there!") 6 >>> sio.get...
it from. However, if you need an object with the ability to modify in-place Unicode data, try using an :class:`io.StringIO` object or the :mod:`array` module:: >>> import io >>> s = "Hello, world" >>> sio = io.StringIO(s) >>> sio.getvalue() 'Hello, world' >>> sio.seek(7) 7 >>> sio.write("there!") 6 >>> sio.get...
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@cached_property def location(self): "Return the longitude/latitude coordinates of the station" # Result only depends on the station_id @lru_cache(maxsize=20) def historic_rainfall(self, date, units='mm'): "Rainfall on a given date" # Depends on the station_id, date, and units.
trusted_official_docs
CPython Docs
@cached_property def location(self): "Return the longitude/latitude coordinates of the station" # Result only depends on the station_id @lru_cache(maxsize=20) def historic_rainfall(self, date, units='mm'): "Rainfall on a given date" # Depends on the station_id, date, and units.
@cached_property def location(self): "Return the longitude/latitude coordinates of the station" # Result only depends on the station_id @lru_cache(maxsize=20) def historic_rainfall(self, date, units='mm'): "Rainfall on a given date" # Depends on the station_id, date, and units.
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How can I organize my code to make it easier to change the base class? ---------------------------------------------------------------------- You could assign the base class to an alias and derive from the alias. Then all you have to change is the value assigned to the alias. Incidentally, this trick is also handy if y...
trusted_official_docs
CPython Docs
How can I organize my code to make it easier to change the base class? ---------------------------------------------------------------------- You could assign the base class to an alias and derive from the alias. Then all you have to change is the value assigned to the alias. Incidentally, this trick is also handy if y...
How can I organize my code to make it easier to change the base class? ---------------------------------------------------------------------- You could assign the base class to an alias and derive from the alias. Then all you have to change is the value assigned to the alias. Incidentally, this trick is also handy if y...
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There are (at least) three possible workarounds for this problem. Guido van Rossum recommends avoiding all uses of ``from <module> import ...``, and placing all code inside functions. Initializations of global variables and class variables should use constants or built-in functions only. This means everything from an i...
trusted_official_docs
CPython Docs
There are (at least) three possible workarounds for this problem. Guido van Rossum recommends avoiding all uses of ``from <module> import ...``, and placing all code inside functions. Initializations of global variables and class variables should use constants or built-in functions only. This means everything from an i...
There are (at least) three possible workarounds for this problem. Guido van Rossum recommends avoiding all uses of ``from <module> import ...``, and placing all code inside functions. Initializations of global variables and class variables should use constants or built-in functions only. This means everything from an i...
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work when the *station_id* is mutable, the class needs to define the :meth:`~object.__eq__` and :meth:`~object.__hash__` methods so that the cache can detect relevant attribute updates:: class Weather: "Example with a mutable station identifier"
trusted_official_docs
CPython Docs
work when the *station_id* is mutable, the class needs to define the :meth:`~object.__eq__` and :meth:`~object.__hash__` methods so that the cache can detect relevant attribute updates:: class Weather: "Example with a mutable station identifier"
work when the *station_id* is mutable, the class needs to define the :meth:`~object.__eq__` and :meth:`~object.__hash__` methods so that the cache can detect relevant attribute updates:: class Weather: "Example with a mutable station identifier"
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slash at the end of the parameter list means that both parameters are positional-only. Thus, calling :func:`divmod` with keyword arguments would lead to an error:: >>> divmod(x=3, y=4) Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: divmod() takes no keyword arguments
trusted_official_docs
CPython Docs
slash at the end of the parameter list means that both parameters are positional-only. Thus, calling :func:`divmod` with keyword arguments would lead to an error:: >>> divmod(x=3, y=4) Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: divmod() takes no keyword arguments
slash at the end of the parameter list means that both parameters are positional-only. Thus, calling :func:`divmod` with keyword arguments would lead to an error:: >>> divmod(x=3, y=4) Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: divmod() takes no keyword arguments
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lisp_list = ("like", ("this", ("example", None) ) ) If mutability is desired, you could use lists instead of tuples. Here the analogue of a Lisp *car* is ``lisp_list[0]`` and the analogue of *cdr* is ``lisp_list[1]``. Only do this if you're sure you really need to, because it's usually a lot slower than using Python li...
trusted_official_docs
CPython Docs
lisp_list = ("like", ("this", ("example", None) ) ) If mutability is desired, you could use lists instead of tuples. Here the analogue of a Lisp *car* is ``lisp_list[0]`` and the analogue of *cdr* is ``lisp_list[1]``. Only do this if you're sure you really need to, because it's usually a lot slower than using Python li...
lisp_list = ("like", ("this", ("example", None) ) ) If mutability is desired, you could use lists instead of tuples. Here the analogue of a Lisp *car* is ``lisp_list[0]`` and the analogue of *cdr* is ``lisp_list[1]``. Only do this if you're sure you really need to, because it's usually a lot slower than using Python li...
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Why do lambdas defined in a loop with different values all return the same result? ---------------------------------------------------------------------------------- Assume you use a for loop to define a few different lambdas (or even plain functions), for example::
trusted_official_docs
CPython Docs
Why do lambdas defined in a loop with different values all return the same result? ---------------------------------------------------------------------------------- Assume you use a for loop to define a few different lambdas (or even plain functions), for example::
Why do lambdas defined in a loop with different values all return the same result? ---------------------------------------------------------------------------------- Assume you use a for loop to define a few different lambdas (or even plain functions), for example::
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What's a negative index? ------------------------ Python sequences are indexed with positive numbers and negative numbers. For positive numbers 0 is the first index 1 is the second index and so forth. For negative indices -1 is the last index and -2 is the penultimate (next to last) index and so forth. Think of ``seq[-...
trusted_official_docs
CPython Docs
What's a negative index? ------------------------ Python sequences are indexed with positive numbers and negative numbers. For positive numbers 0 is the first index 1 is the second index and so forth. For negative indices -1 is the last index and -2 is the penultimate (next to last) index and so forth. Think of ``seq[-...
What's a negative index? ------------------------ Python sequences are indexed with positive numbers and negative numbers. For positive numbers 0 is the first index 1 is the second index and so forth. For negative indices -1 is the last index and -2 is the penultimate (next to last) index and so forth. Think of ``seq[-...
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When I edit an imported module and reimport it, the changes don't show up. Why does this happen? ------------------------------------------------------------------------------------------------- For reasons of efficiency as well as consistency, Python only reads the module file on the first time a module is imported. I...
trusted_official_docs
CPython Docs
When I edit an imported module and reimport it, the changes don't show up. Why does this happen? ------------------------------------------------------------------------------------------------- For reasons of efficiency as well as consistency, Python only reads the module file on the first time a module is imported. I...
When I edit an imported module and reimport it, the changes don't show up. Why does this happen? ------------------------------------------------------------------------------------------------- For reasons of efficiency as well as consistency, Python only reads the module file on the first time a module is imported. I...
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def __getattr__(self, name): return getattr(self._outfile, name) Here the ``UpperOut`` class redefines the ``write()`` method to convert the argument string to uppercase before calling the underlying ``self._outfile.write()`` method. All other methods are delegated to the underlying ``self._outfile`` object. The delega...
trusted_official_docs
CPython Docs
def __getattr__(self, name): return getattr(self._outfile, name) Here the ``UpperOut`` class redefines the ``write()`` method to convert the argument string to uppercase before calling the underlying ``self._outfile.write()`` method. All other methods are delegated to the underlying ``self._outfile`` object. The delega...
def __getattr__(self, name): return getattr(self._outfile, name) Here the ``UpperOut`` class redefines the ``write()`` method to convert the argument string to uppercase before calling the underlying ``self._outfile.write()`` method. All other methods are delegated to the underlying ``self._outfile`` object. The delega...
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C arrays; with a C compiler you can embed all your modules into a new program, which is then linked with the standard Python modules. It works by scanning your source recursively for import statements (in both forms) and looking for the modules in the standard Python path as well as in the source directory (for built-i...
trusted_official_docs
CPython Docs
C arrays; with a C compiler you can embed all your modules into a new program, which is then linked with the standard Python modules. It works by scanning your source recursively for import statements (in both forms) and looking for the modules in the standard Python path as well as in the source directory (for built-i...
C arrays; with a C compiler you can embed all your modules into a new program, which is then linked with the standard Python modules. It works by scanning your source recursively for import statements (in both forms) and looking for the modules in the standard Python path as well as in the source directory (for built-i...
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scope. Using one import per line makes it easy to add and delete module imports, but using multiple imports per line uses less screen space. It's good practice if you import modules in the following order:
trusted_official_docs
CPython Docs
scope. Using one import per line makes it easy to add and delete module imports, but using multiple imports per line uses less screen space. It's good practice if you import modules in the following order:
scope. Using one import per line makes it easy to add and delete module imports, but using multiple imports per line uses less screen space. It's good practice if you import modules in the following order:
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tools that determine the set of modules required by a program and bind these modules together with a Python binary to produce a single executable. One is to use the freeze tool, which is included in the Python source tree as :source:`Tools/freeze`. It converts Python byte code to C arrays; with a C compiler you can emb...
trusted_official_docs
CPython Docs
tools that determine the set of modules required by a program and bind these modules together with a Python binary to produce a single executable. One is to use the freeze tool, which is included in the Python source tree as :source:`Tools/freeze`. It converts Python byte code to C arrays; with a C compiler you can emb...
tools that determine the set of modules required by a program and bind these modules together with a Python binary to produce a single executable. One is to use the freeze tool, which is included in the Python source tree as :source:`Tools/freeze`. It converts Python byte code to C arrays; with a C compiler you can emb...
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>>> a = 10_000_000 >>> b = 5_000_000 >>> c = b + 5_000_000 >>> a is c False >>> a = 'Python' >>> b = 'Py' >>> c = b + 'thon' >>> a is c False
trusted_official_docs
CPython Docs
>>> a = 10_000_000 >>> b = 5_000_000 >>> c = b + 5_000_000 >>> a is c False >>> a = 'Python' >>> b = 'Py' >>> c = b + 'thon' >>> a is c False
>>> a = 10_000_000 >>> b = 5_000_000 >>> c = b + 5_000_000 >>> a is c False >>> a = 'Python' >>> b = 'Py' >>> c = b + 'thon' >>> a is c False
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to the underlying ``self._outfile`` object. The delegation is accomplished via the :meth:`~object.__getattr__` method; consult :ref:`the language reference <attribute-access>` for more information about controlling attribute access. Note that for more general cases delegation can get trickier. When attributes must be s...
trusted_official_docs
CPython Docs
to the underlying ``self._outfile`` object. The delegation is accomplished via the :meth:`~object.__getattr__` method; consult :ref:`the language reference <attribute-access>` for more information about controlling attribute access. Note that for more general cases delegation can get trickier. When attributes must be s...
to the underlying ``self._outfile`` object. The delegation is accomplished via the :meth:`~object.__getattr__` method; consult :ref:`the language reference <attribute-access>` for more information about controlling attribute access. Note that for more general cases delegation can get trickier. When attributes must be s...
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mutable object has changed from ``[]`` to ``[10]``. Since both the variables refer to the same object, using either name accesses the modified value ``[10]``. If we instead assign an immutable object to ``x``::
trusted_official_docs
CPython Docs
mutable object has changed from ``[]`` to ``[10]``. Since both the variables refer to the same object, using either name accesses the modified value ``[10]``. If we instead assign an immutable object to ``x``::
mutable object has changed from ``[]`` to ``[10]``. Since both the variables refer to the same object, using either name accesses the modified value ``[10]``. If we instead assign an immutable object to ``x``::
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How do you make a higher order function in Python? -------------------------------------------------- You have two choices: you can use nested scopes or you can use callable objects. For example, suppose you wanted to define ``linear(a,b)`` which returns a function ``f(x)`` that computes the value ``a*x+b``. Using nest...
trusted_official_docs
CPython Docs
How do you make a higher order function in Python? -------------------------------------------------- You have two choices: you can use nested scopes or you can use callable objects. For example, suppose you wanted to define ``linear(a,b)`` which returns a function ``f(x)`` that computes the value ``a*x+b``. Using nest...
How do you make a higher order function in Python? -------------------------------------------------- You have two choices: you can use nested scopes or you can use callable objects. For example, suppose you wanted to define ``linear(a,b)`` which returns a function ``f(x)`` that computes the value ``a*x+b``. Using nest...
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The suggested approach is to create a list of the desired length first and then fill in each element with a newly created list:: A = [None] * 3 for i in range(3): A[i] = [None] * 2
trusted_official_docs
CPython Docs
The suggested approach is to create a list of the desired length first and then fill in each element with a newly created list:: A = [None] * 3 for i in range(3): A[i] = [None] * 2
The suggested approach is to create a list of the desired length first and then fill in each element with a newly created list:: A = [None] * 3 for i in range(3): A[i] = [None] * 2
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In Python you have to write a single constructor that catches all cases using default arguments. For example:: class C: def __init__(self, i=None): if i is None: print("No arguments") else: print("Argument is", i)
trusted_official_docs
CPython Docs
In Python you have to write a single constructor that catches all cases using default arguments. For example:: class C: def __init__(self, i=None): if i is None: print("No arguments") else: print("Argument is", i)
In Python you have to write a single constructor that catches all cases using default arguments. For example:: class C: def __init__(self, i=None): if i is None: print("No arguments") else: print("Argument is", i)
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module and Python has the ability (permissions, free space, and so on) to create a ``__pycache__`` subdirectory and write the compiled module to that subdirectory. Running Python on a top-level script is not considered an import and no ``.pyc`` will be created. For example, if you have a top-level module ``foo.py`` tha...
trusted_official_docs
CPython Docs
module and Python has the ability (permissions, free space, and so on) to create a ``__pycache__`` subdirectory and write the compiled module to that subdirectory. Running Python on a top-level script is not considered an import and no ``.pyc`` will be created. For example, if you have a top-level module ``foo.py`` tha...
module and Python has the ability (permissions, free space, and so on) to create a ``__pycache__`` subdirectory and write the compiled module to that subdirectory. Running Python on a top-level script is not considered an import and no ``.pyc`` will be created. For example, if you have a top-level module ``foo.py`` tha...
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a container that stores object references does not change object identity. After the list assignment ``s[0] = x``, it is guaranteed that ``s[0] is x``. 3) If an object is a singleton, it means that only one instance of that object can exist. After the assignments ``a = None`` and ``b = None``, it is guaranteed that `...
trusted_official_docs
CPython Docs
a container that stores object references does not change object identity. After the list assignment ``s[0] = x``, it is guaranteed that ``s[0] is x``. 3) If an object is a singleton, it means that only one instance of that object can exist. After the assignments ``a = None`` and ``b = None``, it is guaranteed that `...
a container that stores object references does not change object identity. After the list assignment ``s[0] = x``, it is guaranteed that ``s[0] is x``. 3) If an object is a singleton, it means that only one instance of that object can exist. After the assignments ``a = None`` and ``b = None``, it is guaranteed that `...
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can use callable objects. For example, suppose you wanted to define ``linear(a,b)`` which returns a function ``f(x)`` that computes the value ``a*x+b``. Using nested scopes:: def linear(a, b): def result(x): return a * x + b return result
trusted_official_docs
CPython Docs
can use callable objects. For example, suppose you wanted to define ``linear(a,b)`` which returns a function ``f(x)`` that computes the value ``a*x+b``. Using nested scopes:: def linear(a, b): def result(x): return a * x + b return result
can use callable objects. For example, suppose you wanted to define ``linear(a,b)`` which returns a function ``f(x)`` that computes the value ``a*x+b``. Using nested scopes:: def linear(a, b): def result(x): return a * x + b return result
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file://datasets/cpython/Doc/faq/programming.rst
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| |______ columns on screen # | | |__________ maximum of "iterations" # | |_________________ range on y axis # |____________________________ range on x axis Don't try this at home, kids!
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CPython Docs
| |______ columns on screen # | | |__________ maximum of "iterations" # | |_________________ range on y axis # |____________________________ range on x axis Don't try this at home, kids!
| |______ columns on screen # | | |__________ maximum of "iterations" # | |_________________ range on y axis # |____________________________ range on x axis Don't try this at home, kids!
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use the built-in functions :func:`hex` or :func:`oct`. For fancy formatting, see the :ref:`f-strings` and :ref:`formatstrings` sections. For example, ``"{:04d}".format(144)`` yields ``'0144'`` and ``"{:.3f}".format(1.0/3.0)`` yields ``'0.333'``. How do I modify a string in place? ----------------------------------
trusted_official_docs
CPython Docs
use the built-in functions :func:`hex` or :func:`oct`. For fancy formatting, see the :ref:`f-strings` and :ref:`formatstrings` sections. For example, ``"{:04d}".format(144)`` yields ``'0144'`` and ``"{:.3f}".format(1.0/3.0)`` yields ``'0.333'``. How do I modify a string in place? ----------------------------------
use the built-in functions :func:`hex` or :func:`oct`. For fancy formatting, see the :ref:`f-strings` and :ref:`formatstrings` sections. For example, ``"{:04d}".format(144)`` yields ``'0144'`` and ``"{:.3f}".format(1.0/3.0)`` yields ``'0.333'``. How do I modify a string in place? ----------------------------------
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If your code is structured so as to define one class (or tightly related class hierarchy) per module, this supplies the desired encapsulation. How can I overload constructors (or methods) in Python? -------------------------------------------------------
trusted_official_docs
CPython Docs
If your code is structured so as to define one class (or tightly related class hierarchy) per module, this supplies the desired encapsulation. How can I overload constructors (or methods) in Python? -------------------------------------------------------
If your code is structured so as to define one class (or tightly related class hierarchy) per module, this supplies the desired encapsulation. How can I overload constructors (or methods) in Python? -------------------------------------------------------
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How do I specify hexadecimal and octal integers? ------------------------------------------------ To specify an octal digit, precede the octal value with a zero, and then a lower or uppercase "o". For example, to set the variable "a" to the octal value "10" (8 in decimal), type::
trusted_official_docs
CPython Docs
How do I specify hexadecimal and octal integers? ------------------------------------------------ To specify an octal digit, precede the octal value with a zero, and then a lower or uppercase "o". For example, to set the variable "a" to the octal value "10" (8 in decimal), type::
How do I specify hexadecimal and octal integers? ------------------------------------------------ To specify an octal digit, precede the octal value with a zero, and then a lower or uppercase "o". For example, to set the variable "a" to the octal value "10" (8 in decimal), type::
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code significantly faster than when interpreted. If you are confident in your C programming skills, you can also :ref:`write a C extension module <extending-index>` yourself. .. seealso:: The wiki page devoted to `performance tips <https://wiki.python.org/moin/PythonSpeed/PerformanceTips>`_.
trusted_official_docs
CPython Docs
code significantly faster than when interpreted. If you are confident in your C programming skills, you can also :ref:`write a C extension module <extending-index>` yourself. .. seealso:: The wiki page devoted to `performance tips <https://wiki.python.org/moin/PythonSpeed/PerformanceTips>`_.
code significantly faster than when interpreted. If you are confident in your C programming skills, you can also :ref:`write a C extension module <extending-index>` yourself. .. seealso:: The wiki page devoted to `performance tips <https://wiki.python.org/moin/PythonSpeed/PerformanceTips>`_.
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even though ``result`` points to the same object that ``a_tuple[0]`` already points to, that final assignment still results in an error, because tuples are immutable. I want to do a complicated sort: can you do a Schwartzian Transform in Python? --------------------------------------------------------------------------...
trusted_official_docs
CPython Docs
even though ``result`` points to the same object that ``a_tuple[0]`` already points to, that final assignment still results in an error, because tuples are immutable. I want to do a complicated sort: can you do a Schwartzian Transform in Python? --------------------------------------------------------------------------...
even though ``result`` points to the same object that ``a_tuple[0]`` already points to, that final assignment still results in an error, because tuples are immutable. I want to do a complicated sort: can you do a Schwartzian Transform in Python? --------------------------------------------------------------------------...
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alias between an argument name in the caller and callee, and consequently no call-by-reference. You can achieve the desired effect in a number of ways. 1) By returning a tuple of the results::
trusted_official_docs
CPython Docs
alias between an argument name in the caller and callee, and consequently no call-by-reference. You can achieve the desired effect in a number of ways. 1) By returning a tuple of the results::
alias between an argument name in the caller and callee, and consequently no call-by-reference. You can achieve the desired effect in a number of ways. 1) By returning a tuple of the results::
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as a tuple and the keyword arguments as a dictionary. You can then pass these arguments when calling another function by using ``*`` and ``**``:: def f(x, *args, **kwargs): ... kwargs['width'] = '14.3c' ... g(x, *args, **kwargs)
trusted_official_docs
CPython Docs
as a tuple and the keyword arguments as a dictionary. You can then pass these arguments when calling another function by using ``*`` and ``**``:: def f(x, *args, **kwargs): ... kwargs['width'] = '14.3c' ... g(x, *args, **kwargs)
as a tuple and the keyword arguments as a dictionary. You can then pass these arguments when calling another function by using ``*`` and ``**``:: def f(x, *args, **kwargs): ... kwargs['width'] = '14.3c' ... g(x, *args, **kwargs)
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a zero, and then a lower or uppercase "o". For example, to set the variable "a" to the octal value "10" (8 in decimal), type:: >>> a = 0o10 >>> a 8
trusted_official_docs
CPython Docs
a zero, and then a lower or uppercase "o". For example, to set the variable "a" to the octal value "10" (8 in decimal), type:: >>> a = 0o10 >>> a 8
a zero, and then a lower or uppercase "o". For example, to set the variable "a" to the octal value "10" (8 in decimal), type:: >>> a = 0o10 >>> a 8
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values using :func:`int` or :func:`float`. :meth:`!split` supports an optional "sep" parameter which is useful if the line uses something other than whitespace as a separator. For more complicated input parsing, regular expressions are more powerful than C's ``sscanf`` and better suited for the task.
trusted_official_docs
CPython Docs
values using :func:`int` or :func:`float`. :meth:`!split` supports an optional "sep" parameter which is useful if the line uses something other than whitespace as a separator. For more complicated input parsing, regular expressions are more powerful than C's ``sscanf`` and better suited for the task.
values using :func:`int` or :func:`float`. :meth:`!split` supports an optional "sep" parameter which is useful if the line uses something other than whitespace as a separator. For more complicated input parsing, regular expressions are more powerful than C's ``sscanf`` and better suited for the task.
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the assignment is a no-op, since it is a pointer to the same object that ``a_list`` was previously pointing to, but the assignment still happens. Thus, in our tuple example what is happening is equivalent to::
trusted_official_docs
CPython Docs
the assignment is a no-op, since it is a pointer to the same object that ``a_list`` was previously pointing to, but the assignment still happens. Thus, in our tuple example what is happening is equivalent to::
the assignment is a no-op, since it is a pointer to the same object that ``a_list`` was previously pointing to, but the assignment still happens. Thus, in our tuple example what is happening is equivalent to::
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In general, try :func:`copy.copy` or :func:`copy.deepcopy` for the general case. Not all objects can be copied, but most can. Some objects can be copied more easily. Dictionaries have a :meth:`~dict.copy` method::
trusted_official_docs
CPython Docs
In general, try :func:`copy.copy` or :func:`copy.deepcopy` for the general case. Not all objects can be copied, but most can. Some objects can be copied more easily. Dictionaries have a :meth:`~dict.copy` method::
In general, try :func:`copy.copy` or :func:`copy.deepcopy` for the general case. Not all objects can be copied, but most can. Some objects can be copied more easily. Dictionaries have a :meth:`~dict.copy` method::
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What is a class? ---------------- A class is the particular object type created by executing a class statement. Class objects are used as templates to create instance objects, which embody both the data (attributes) and code (methods) specific to a datatype.
trusted_official_docs
CPython Docs
What is a class? ---------------- A class is the particular object type created by executing a class statement. Class objects are used as templates to create instance objects, which embody both the data (attributes) and code (methods) specific to a datatype.
What is a class? ---------------- A class is the particular object type created by executing a class statement. Class objects are used as templates to create instance objects, which embody both the data (attributes) and code (methods) specific to a datatype.
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I want to do a complicated sort: can you do a Schwartzian Transform in Python? ------------------------------------------------------------------------------ The technique, attributed to Randal Schwartz of the Perl community, sorts the elements of a list by a metric which maps each element to its "sort value". In Pytho...
trusted_official_docs
CPython Docs
I want to do a complicated sort: can you do a Schwartzian Transform in Python? ------------------------------------------------------------------------------ The technique, attributed to Randal Schwartz of the Perl community, sorts the elements of a list by a metric which maps each element to its "sort value". In Pytho...
I want to do a complicated sort: can you do a Schwartzian Transform in Python? ------------------------------------------------------------------------------ The technique, attributed to Randal Schwartz of the Perl community, sorts the elements of a list by a metric which maps each element to its "sort value". In Pytho...
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import io >>> s = "Hello, world" >>> sio = io.StringIO(s) >>> sio.getvalue() 'Hello, world' >>> sio.seek(7) 7 >>> sio.write("there!") 6 >>> sio.getvalue() 'Hello, there!' >>> import array >>> a = array.array('w', s) >>> print(a) array('w', 'Hello, world') >>> a[0] = 'y' >>> print(a) array('w', 'yello, world') >>...
trusted_official_docs
CPython Docs
import io >>> s = "Hello, world" >>> sio = io.StringIO(s) >>> sio.getvalue() 'Hello, world' >>> sio.seek(7) 7 >>> sio.write("there!") 6 >>> sio.getvalue() 'Hello, there!' >>> import array >>> a = array.array('w', s) >>> print(a) array('w', 'Hello, world') >>> a[0] = 'y' >>> print(a) array('w', 'yello, world') >>...
import io >>> s = "Hello, world" >>> sio = io.StringIO(s) >>> sio.getvalue() 'Hello, world' >>> sio.seek(7) 7 >>> sio.write("there!") 6 >>> sio.getvalue() 'Hello, there!' >>> import array >>> a = array.array('w', s) >>> print(a) array('w', 'Hello, world') >>> a[0] = 'y' >>> print(a) array('w', 'yello, world') >>...
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the generated C code and links it with the rest of the Python interpreter to form a self-contained binary which acts exactly like your script. The following packages can help with the creation of console and GUI executables:
trusted_official_docs
CPython Docs
the generated C code and links it with the rest of the Python interpreter to form a self-contained binary which acts exactly like your script. The following packages can help with the creation of console and GUI executables:
the generated C code and links it with the rest of the Python interpreter to form a self-contained binary which acts exactly like your script. The following packages can help with the creation of console and GUI executables:
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-1 is the last index and -2 is the penultimate (next to last) index and so forth. Think of ``seq[-n]`` as the same as ``seq[len(seq)-n]``. Using negative indices can be very convenient. For example ``S[:-1]`` is all of the string except for its last character, which is useful for removing the trailing newline from a st...
trusted_official_docs
CPython Docs
-1 is the last index and -2 is the penultimate (next to last) index and so forth. Think of ``seq[-n]`` as the same as ``seq[len(seq)-n]``. Using negative indices can be very convenient. For example ``S[:-1]`` is all of the string except for its last character, which is useful for removing the trailing newline from a st...
-1 is the last index and -2 is the penultimate (next to last) index and so forth. Think of ``seq[-n]`` as the same as ``seq[len(seq)-n]``. Using negative indices can be very convenient. For example ``S[:-1]`` is all of the string except for its last character, which is useful for removing the trailing newline from a st...
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function is defined. If that object is changed, like the dictionary in this example, subsequent calls to the function will refer to this changed object. By definition, immutable objects such as numbers, strings, tuples, and ``None``, are safe from change. Changes to mutable objects such as dictionaries, lists, and clas...
trusted_official_docs
CPython Docs
function is defined. If that object is changed, like the dictionary in this example, subsequent calls to the function will refer to this changed object. By definition, immutable objects such as numbers, strings, tuples, and ``None``, are safe from change. Changes to mutable objects such as dictionaries, lists, and clas...
function is defined. If that object is changed, like the dictionary in this example, subsequent calls to the function will refer to this changed object. By definition, immutable objects such as numbers, strings, tuples, and ``None``, are safe from change. Changes to mutable objects such as dictionaries, lists, and clas...
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CPython Docs
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Callers can only provide two parameters and optionally pass _cache by keyword def expensive(arg1, arg2, *, _cache={}): if (arg1, arg2) in _cache: return _cache[(arg1, arg2)] # Calculate the value result = ... expensive computation ... _cache[(arg1, arg2)] = result # Store result in the cache return result
trusted_official_docs
CPython Docs
Callers can only provide two parameters and optionally pass _cache by keyword def expensive(arg1, arg2, *, _cache={}): if (arg1, arg2) in _cache: return _cache[(arg1, arg2)] # Calculate the value result = ... expensive computation ... _cache[(arg1, arg2)] = result # Store result in the cache return result
Callers can only provide two parameters and optionally pass _cache by keyword def expensive(arg1, arg2, *, _cache={}): if (arg1, arg2) in _cache: return _cache[(arg1, arg2)] # Calculate the value result = ... expensive computation ... _cache[(arg1, arg2)] = result # Store result in the cache return result
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Under the covers, what this augmented assignment statement is doing is approximately this:: >>> result = a_tuple[0] + 1 >>> a_tuple[0] = result Traceback (most recent call last): ... TypeError: 'tuple' object does not support item assignment
trusted_official_docs
CPython Docs
Under the covers, what this augmented assignment statement is doing is approximately this:: >>> result = a_tuple[0] + 1 >>> a_tuple[0] = result Traceback (most recent call last): ... TypeError: 'tuple' object does not support item assignment
Under the covers, what this augmented assignment statement is doing is approximately this:: >>> result = a_tuple[0] + 1 >>> a_tuple[0] = result Traceback (most recent call last): ... TypeError: 'tuple' object does not support item assignment
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together is inefficient as each concatenation creates a new object. In the general case, the total runtime cost is quadratic in the total string length. To accumulate many :class:`str` objects, the recommended idiom is to place them into a list and call :meth:`str.join` at the end::
trusted_official_docs
CPython Docs
together is inefficient as each concatenation creates a new object. In the general case, the total runtime cost is quadratic in the total string length. To accumulate many :class:`str` objects, the recommended idiom is to place them into a list and call :meth:`str.join` at the end::
together is inefficient as each concatenation creates a new object. In the general case, the total runtime cost is quadratic in the total string length. To accumulate many :class:`str` objects, the recommended idiom is to place them into a list and call :meth:`str.join` at the end::
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the class must define a :meth:`~object.__setattr__` method too, and it must do so carefully. The basic implementation of :meth:`!__setattr__` is roughly equivalent to the following:: class X: ... def __setattr__(self, name, value): self.__dict__[name] = value ...
trusted_official_docs
CPython Docs
the class must define a :meth:`~object.__setattr__` method too, and it must do so carefully. The basic implementation of :meth:`!__setattr__` is roughly equivalent to the following:: class X: ... def __setattr__(self, name, value): self.__dict__[name] = value ...
the class must define a :meth:`~object.__setattr__` method too, and it must do so carefully. The basic implementation of :meth:`!__setattr__` is roughly equivalent to the following:: class X: ... def __setattr__(self, name, value): self.__dict__[name] = value ...
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Trying to lookup an ``int`` literal attribute in the normal manner gives a :exc:`SyntaxError` because the period is seen as a decimal point:: >>> 1.__class__ File "<stdin>", line 1 1.__class__ ^ SyntaxError: invalid decimal literal
trusted_official_docs
CPython Docs
Trying to lookup an ``int`` literal attribute in the normal manner gives a :exc:`SyntaxError` because the period is seen as a decimal point:: >>> 1.__class__ File "<stdin>", line 1 1.__class__ ^ SyntaxError: invalid decimal literal
Trying to lookup an ``int`` literal attribute in the normal manner gives a :exc:`SyntaxError` because the period is seen as a decimal point:: >>> 1.__class__ File "<stdin>", line 1 1.__class__ ^ SyntaxError: invalid decimal literal
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You could use a global variable containing a dictionary instead of the default value; it's a matter of taste. How can I pass optional or keyword parameters from one function to another? ---------------------------------------------------------------------------
trusted_official_docs
CPython Docs
You could use a global variable containing a dictionary instead of the default value; it's a matter of taste. How can I pass optional or keyword parameters from one function to another? ---------------------------------------------------------------------------
You could use a global variable containing a dictionary instead of the default value; it's a matter of taste. How can I pass optional or keyword parameters from one function to another? ---------------------------------------------------------------------------
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contains a single item. The second time, ``mydict`` contains two items because when ``foo()`` begins executing, ``mydict`` starts out with an item already in it. It is often expected that a function call creates new objects for default values. This is not what happens. Default values are created exactly once, when the ...
trusted_official_docs
CPython Docs
contains a single item. The second time, ``mydict`` contains two items because when ``foo()`` begins executing, ``mydict`` starts out with an item already in it. It is often expected that a function call creates new objects for default values. This is not what happens. Default values are created exactly once, when the ...
contains a single item. The second time, ``mydict`` contains two items because when ``foo()`` begins executing, ``mydict`` starts out with an item already in it. It is often expected that a function call creates new objects for default values. This is not what happens. Default values are created exactly once, when the ...
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How can I sort one list by values from another list? ---------------------------------------------------- Merge them into an iterator of tuples, sort the resulting list, and then pick out the element you want.
trusted_official_docs
CPython Docs
How can I sort one list by values from another list? ---------------------------------------------------- Merge them into an iterator of tuples, sort the resulting list, and then pick out the element you want.
How can I sort one list by values from another list? ---------------------------------------------------- Merge them into an iterator of tuples, sort the resulting list, and then pick out the element you want.
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instead of the :meth:`~object.__init__` method. The latter only runs *after* an instance is created, which is too late to alter data in an immutable instance. All of these immutable classes have a different signature than their parent class:
trusted_official_docs
CPython Docs
instead of the :meth:`~object.__init__` method. The latter only runs *after* an instance is created, which is too late to alter data in an immutable instance. All of these immutable classes have a different signature than their parent class:
instead of the :meth:`~object.__init__` method. The latter only runs *after* an instance is created, which is too late to alter data in an immutable instance. All of these immutable classes have a different signature than their parent class:
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def pop(self, key, default=_sentinel): if key in self: value = self[key] del self[key] return value if default is _sentinel: raise KeyError(key) return default 3) Container implementations sometimes need to augment equality tests with identity tests. This prevents the code from being confused by objects such as ``flo...
trusted_official_docs
CPython Docs
def pop(self, key, default=_sentinel): if key in self: value = self[key] del self[key] return value if default is _sentinel: raise KeyError(key) return default 3) Container implementations sometimes need to augment equality tests with identity tests. This prevents the code from being confused by objects such as ``flo...
def pop(self, key, default=_sentinel): if key in self: value = self[key] del self[key] return value if default is _sentinel: raise KeyError(key) return default 3) Container implementations sometimes need to augment equality tests with identity tests. This prevents the code from being confused by objects such as ``flo...
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>>> x = 10 >>> def foobar(): ... global x ... print(x) ... x += 1 ... >>> foobar() 10 This explicit declaration is required in order to remind you that (unlike the superficially analogous situation with class and instance variables) you are actually modifying the value of the variable in the outer scope:
trusted_official_docs
CPython Docs
>>> x = 10 >>> def foobar(): ... global x ... print(x) ... x += 1 ... >>> foobar() 10 This explicit declaration is required in order to remind you that (unlike the superficially analogous situation with class and instance variables) you are actually modifying the value of the variable in the outer scope:
>>> x = 10 >>> def foobar(): ... global x ... print(x) ... x += 1 ... >>> foobar() 10 This explicit declaration is required in order to remind you that (unlike the superficially analogous situation with class and instance variables) you are actually modifying the value of the variable in the outer scope:
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two leading underscores, at most one trailing underscore) is textually replaced with ``_classname__spam``, where ``classname`` is the current class name with any leading underscores stripped. The identifier can be used unchanged within the class, but to access it outside the class, the mangled name must be used:
trusted_official_docs
CPython Docs
two leading underscores, at most one trailing underscore) is textually replaced with ``_classname__spam``, where ``classname`` is the current class name with any leading underscores stripped. The identifier can be used unchanged within the class, but to access it outside the class, the mangled name must be used:
two leading underscores, at most one trailing underscore) is textually replaced with ``_classname__spam``, where ``classname`` is the current class name with any leading underscores stripped. The identifier can be used unchanged within the class, but to access it outside the class, the mangled name must be used:
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Many modules that are usually used by importing them also provide a command-line interface or a self-test, and only execute this code after checking ``__name__``:: def main(): print('Running test...') ...
trusted_official_docs
CPython Docs
Many modules that are usually used by importing them also provide a command-line interface or a self-test, and only execute this code after checking ``__name__``:: def main(): print('Running test...') ...
Many modules that are usually used by importing them also provide a command-line interface or a self-test, and only execute this code after checking ``__name__``:: def main(): print('Running test...') ...
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only one object (the list), and both ``x`` and ``y`` refer to it. 2) Lists are :term:`mutable`, which means that you can change their content. After the call to :meth:`~sequence.append`, the content of the mutable object has changed from ``[]`` to ``[10]``. Since both the variables refer to the same object, using eithe...
trusted_official_docs
CPython Docs
only one object (the list), and both ``x`` and ``y`` refer to it. 2) Lists are :term:`mutable`, which means that you can change their content. After the call to :meth:`~sequence.append`, the content of the mutable object has changed from ``[]`` to ``[10]``. Since both the variables refer to the same object, using eithe...
only one object (the list), and both ``x`` and ``y`` refer to it. 2) Lists are :term:`mutable`, which means that you can change their content. After the call to :meth:`~sequence.append`, the content of the mutable object has changed from ``[]`` to ``[10]``. Since both the variables refer to the same object, using eithe...
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How do I get a list of all instances of a given class? ------------------------------------------------------ Python does not keep track of all instances of a class (or of a built-in type). You can program the class's constructor to keep track of all instances by keeping a list of weak references to each instance.
trusted_official_docs
CPython Docs
How do I get a list of all instances of a given class? ------------------------------------------------------ Python does not keep track of all instances of a class (or of a built-in type). You can program the class's constructor to keep track of all instances by keeping a list of weak references to each instance.
How do I get a list of all instances of a given class? ------------------------------------------------------ Python does not keep track of all instances of a class (or of a built-in type). You can program the class's constructor to keep track of all instances by keeping a list of weak references to each instance.
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CPython Docs
file://datasets/cpython/Doc/faq/programming.rst
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`Ruff <https://docs.astral.sh/ruff/>`__, `Pylint <https://pylint.readthedocs.io/>`__ and `Pyflakes <https://github.com/PyCQA/pyflakes>`__ do basic checking that will help you catch bugs sooner. Static type checkers such as `mypy <https://mypy-lang.org/>`__, `ty <https://docs.astral.sh/ty/>`__, `Pyrefly <https://pyrefly...
trusted_official_docs
CPython Docs
`Ruff <https://docs.astral.sh/ruff/>`__, `Pylint <https://pylint.readthedocs.io/>`__ and `Pyflakes <https://github.com/PyCQA/pyflakes>`__ do basic checking that will help you catch bugs sooner. Static type checkers such as `mypy <https://mypy-lang.org/>`__, `ty <https://docs.astral.sh/ty/>`__, `Pyrefly <https://pyrefly...
`Ruff <https://docs.astral.sh/ruff/>`__, `Pylint <https://pylint.readthedocs.io/>`__ and `Pyflakes <https://github.com/PyCQA/pyflakes>`__ do basic checking that will help you catch bugs sooner. Static type checkers such as `mypy <https://mypy-lang.org/>`__, `ty <https://docs.astral.sh/ty/>`__, `Pyrefly <https://pyrefly...
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Namespace ... args.b = args.b + 1 # change object in-place ... >>> args = Namespace(a='old-value', b=99) >>> func4(args) >>> vars(args) {'a': 'new-value', 'b': 100} There's almost never a good reason to get this complicated.
trusted_official_docs
CPython Docs
Namespace ... args.b = args.b + 1 # change object in-place ... >>> args = Namespace(a='old-value', b=99) >>> func4(args) >>> vars(args) {'a': 'new-value', 'b': 100} There's almost never a good reason to get this complicated.
Namespace ... args.b = args.b + 1 # change object in-place ... >>> args = Namespace(a='old-value', b=99) >>> func4(args) >>> vars(args) {'a': 'new-value', 'b': 100} There's almost never a good reason to get this complicated.
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>>> A[0][0] = 5 >>> A [[5, None], [5, None], [5, None]] The reason is that replicating a list with ``*`` doesn't create copies, it only creates references to the existing objects. The ``*3`` creates a list containing 3 references to the same list of length two. Changes to one row will show in all rows, which is almost ...
trusted_official_docs
CPython Docs
>>> A[0][0] = 5 >>> A [[5, None], [5, None], [5, None]] The reason is that replicating a list with ``*`` doesn't create copies, it only creates references to the existing objects. The ``*3`` creates a list containing 3 references to the same list of length two. Changes to one row will show in all rows, which is almost ...
>>> A[0][0] = 5 >>> A [[5, None], [5, None], [5, None]] The reason is that replicating a list with ``*`` doesn't create copies, it only creates references to the existing objects. The ``*3`` creates a list containing 3 references to the same list of length two. Changes to one row will show in all rows, which is almost ...
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of the modules at the top of the file. In this case, importing the correct modules in the corresponding platform-specific code is a good option. Only move imports into a local scope, such as inside a function definition, if it's necessary to solve a problem such as avoiding a circular import or are trying to reduce the...
trusted_official_docs
CPython Docs
of the modules at the top of the file. In this case, importing the correct modules in the corresponding platform-specific code is a good option. Only move imports into a local scope, such as inside a function definition, if it's necessary to solve a problem such as avoiding a circular import or are trying to reduce the...
of the modules at the top of the file. In this case, importing the correct modules in the corresponding platform-specific code is a good option. Only move imports into a local scope, such as inside a function definition, if it's necessary to solve a problem such as avoiding a circular import or are trying to reduce the...
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CPython Docs
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It's primarily driven by the desire that ``i % j`` have the same sign as ``j``. If you want that, and also want:: i == (i // j) * j + (i % j)
trusted_official_docs
CPython Docs
It's primarily driven by the desire that ``i % j`` have the same sign as ``j``. If you want that, and also want:: i == (i // j) * j + (i % j)
It's primarily driven by the desire that ``i % j`` have the same sign as ``j``. If you want that, and also want:: i == (i // j) * j + (i % j)
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CPython Docs
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is equivalent to calling :meth:`~sequence.extend` on the list and returning the list. That's why we say that for lists, ``+=`` is a "shorthand" for :meth:`list.extend`:: >>> a_list = [] >>> a_list += [1] >>> a_list [1]
trusted_official_docs
CPython Docs
is equivalent to calling :meth:`~sequence.extend` on the list and returning the list. That's why we say that for lists, ``+=`` is a "shorthand" for :meth:`list.extend`:: >>> a_list = [] >>> a_list += [1] >>> a_list [1]
is equivalent to calling :meth:`~sequence.extend` on the list and returning the list. That's why we say that for lists, ``+=`` is a "shorthand" for :meth:`list.extend`:: >>> a_list = [] >>> a_list += [1] >>> a_list [1]
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CPython Docs
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def foo(mydict={}): # Danger: shared reference to one dict for all calls ... compute something ... mydict[key] = value return mydict The first time you call this function, ``mydict`` contains a single item. The second time, ``mydict`` contains two items because when ``foo()`` begins executing, ``mydict`` starts out wit...
trusted_official_docs
CPython Docs
def foo(mydict={}): # Danger: shared reference to one dict for all calls ... compute something ... mydict[key] = value return mydict The first time you call this function, ``mydict`` contains a single item. The second time, ``mydict`` contains two items because when ``foo()`` begins executing, ``mydict`` starts out wit...
def foo(mydict={}): # Danger: shared reference to one dict for all calls ... compute something ... mydict[key] = value return mydict The first time you call this function, ``mydict`` contains a single item. The second time, ``mydict`` contains two items because when ``foo()`` begins executing, ``mydict`` starts out wit...
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data, simply define a class attribute. To assign a new value to the attribute, you have to explicitly use the class name in the assignment:: class C: count = 0 # number of times C.__init__ called
trusted_official_docs
CPython Docs
data, simply define a class attribute. To assign a new value to the attribute, you have to explicitly use the class name in the assignment:: class C: count = 0 # number of times C.__init__ called
data, simply define a class attribute. To assign a new value to the attribute, you have to explicitly use the class name in the assignment:: class C: count = 0 # number of times C.__init__ called
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["this", 1, "is", "an", "array"] Lists are equivalent to C or Pascal arrays in their time complexity; the primary difference is that a Python list can contain objects of many different types.
trusted_official_docs
CPython Docs
["this", 1, "is", "an", "array"] Lists are equivalent to C or Pascal arrays in their time complexity; the primary difference is that a Python list can contain objects of many different types.
["this", 1, "is", "an", "array"] Lists are equivalent to C or Pascal arrays in their time complexity; the primary difference is that a Python list can contain objects of many different types.
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convenient. For example ``S[:-1]`` is all of the string except for its last character, which is useful for removing the trailing newline from a string. How do I iterate over a sequence in reverse order? --------------------------------------------------
trusted_official_docs
CPython Docs
convenient. For example ``S[:-1]`` is all of the string except for its last character, which is useful for removing the trailing newline from a string. How do I iterate over a sequence in reverse order? --------------------------------------------------
convenient. For example ``S[:-1]`` is all of the string except for its last character, which is useful for removing the trailing newline from a string. How do I iterate over a sequence in reverse order? --------------------------------------------------
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>>> foo() Traceback (most recent call last): ... UnboundLocalError: cannot access local variable 'x' where it is not associated with a value This is because when you make an assignment to a variable in a scope, that variable becomes local to that scope and shadows any similarly named variable in the outer scope. Since ...
trusted_official_docs
CPython Docs
>>> foo() Traceback (most recent call last): ... UnboundLocalError: cannot access local variable 'x' where it is not associated with a value This is because when you make an assignment to a variable in a scope, that variable becomes local to that scope and shadows any similarly named variable in the outer scope. Since ...
>>> foo() Traceback (most recent call last): ... UnboundLocalError: cannot access local variable 'x' where it is not associated with a value This is because when you make an assignment to a variable in a scope, that variable becomes local to that scope and shadows any similarly named variable in the outer scope. Since ...
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`Nuitka <https://nuitka.net/>`_ (Cross-platform) * `PyInstaller <https://pyinstaller.org/>`_ (Cross-platform) * `PyOxidizer <https://pyoxidizer.readthedocs.io/en/stable/>`_ (Cross-platform) * `cx_Freeze <https://marcelotduarte.github.io/cx_Freeze/>`_ (Cross-platform) * `py2app <https://github.com/ronaldoussoren/py2app>...
trusted_official_docs
CPython Docs
`Nuitka <https://nuitka.net/>`_ (Cross-platform) * `PyInstaller <https://pyinstaller.org/>`_ (Cross-platform) * `PyOxidizer <https://pyoxidizer.readthedocs.io/en/stable/>`_ (Cross-platform) * `cx_Freeze <https://marcelotduarte.github.io/cx_Freeze/>`_ (Cross-platform) * `py2app <https://github.com/ronaldoussoren/py2app>...
`Nuitka <https://nuitka.net/>`_ (Cross-platform) * `PyInstaller <https://pyinstaller.org/>`_ (Cross-platform) * `PyOxidizer <https://pyoxidizer.readthedocs.io/en/stable/>`_ (Cross-platform) * `cx_Freeze <https://marcelotduarte.github.io/cx_Freeze/>`_ (Cross-platform) * `py2app <https://github.com/ronaldoussoren/py2app>...
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arguments. It does not create a reference to the instance. The cached method result will be kept only as long as the instance is alive. The advantage is that when an instance is no longer used, the cached method result will be released right away. The disadvantage is that if instances accumulate, so too will the accumu...
trusted_official_docs
CPython Docs
arguments. It does not create a reference to the instance. The cached method result will be kept only as long as the instance is alive. The advantage is that when an instance is no longer used, the cached method result will be released right away. The disadvantage is that if instances accumulate, so too will the accumu...
arguments. It does not create a reference to the instance. The cached method result will be kept only as long as the instance is alive. The advantage is that when an instance is no longer used, the cached method result will be released right away. The disadvantage is that if instances accumulate, so too will the accumu...
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as Python expressions, so that, for example, ``eval('09')`` gives a syntax error because Python does not allow leading '0' in a decimal number (except '0'). How do I convert a number to a string? --------------------------------------
trusted_official_docs
CPython Docs
as Python expressions, so that, for example, ``eval('09')`` gives a syntax error because Python does not allow leading '0' in a decimal number (except '0'). How do I convert a number to a string? --------------------------------------
as Python expressions, so that, for example, ``eval('09')`` gives a syntax error because Python does not allow leading '0' in a decimal number (except '0'). How do I convert a number to a string? --------------------------------------
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a copy but returns the same object, so it is cheap to call :func:`tuple` when you aren't sure that an object is already a tuple. The type constructor ``list(seq)`` converts any sequence or iterable into a list with the same items in the same order. For example, ``list((1, 2, 3))`` yields ``[1, 2, 3]`` and ``list('abc')...
trusted_official_docs
CPython Docs
a copy but returns the same object, so it is cheap to call :func:`tuple` when you aren't sure that an object is already a tuple. The type constructor ``list(seq)`` converts any sequence or iterable into a list with the same items in the same order. For example, ``list((1, 2, 3))`` yields ``[1, 2, 3]`` and ``list('abc')...
a copy but returns the same object, so it is cheap to call :func:`tuple` when you aren't sure that an object is already a tuple. The type constructor ``list(seq)`` converts any sequence or iterable into a list with the same items in the same order. For example, ``list((1, 2, 3))`` yields ``[1, 2, 3]`` and ``list('abc')...
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>>> a_tuple[0] ['foo', 'item'] To see why this happens, you need to know that (a) if an object implements an :meth:`~object.__iadd__` magic method, it gets called when the ``+=`` augmented assignment is executed, and its return value is what gets used in the assignment statement; and (b) for lists, :meth:`!__iadd__` is...
trusted_official_docs
CPython Docs
>>> a_tuple[0] ['foo', 'item'] To see why this happens, you need to know that (a) if an object implements an :meth:`~object.__iadd__` magic method, it gets called when the ``+=`` augmented assignment is executed, and its return value is what gets used in the assignment statement; and (b) for lists, :meth:`!__iadd__` is...
>>> a_tuple[0] ['foo', 'item'] To see why this happens, you need to know that (a) if an object implements an :meth:`~object.__iadd__` magic method, it gets called when the ``+=`` augmented assignment is executed, and its return value is what gets used in the assignment statement; and (b) for lists, :meth:`!__iadd__` is...
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equivalent to C or Pascal arrays in their time complexity; the primary difference is that a Python list can contain objects of many different types. The ``array`` module also provides methods for creating arrays of fixed types with compact representations, but they are slower to index than lists. Also note that `NumPy ...
trusted_official_docs
CPython Docs
equivalent to C or Pascal arrays in their time complexity; the primary difference is that a Python list can contain objects of many different types. The ``array`` module also provides methods for creating arrays of fixed types with compact representations, but they are slower to index than lists. Also note that `NumPy ...
equivalent to C or Pascal arrays in their time complexity; the primary difference is that a Python list can contain objects of many different types. The ``array`` module also provides methods for creating arrays of fixed types with compact representations, but they are slower to index than lists. Also note that `NumPy ...
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Why am I getting an UnboundLocalError when the variable has a value? -------------------------------------------------------------------- It can be a surprise to get the :exc:`UnboundLocalError` in previously working code when it is modified by adding an assignment statement somewhere in the body of a function.
trusted_official_docs
CPython Docs
Why am I getting an UnboundLocalError when the variable has a value? -------------------------------------------------------------------- It can be a surprise to get the :exc:`UnboundLocalError` in previously working code when it is modified by adding an assignment statement somewhere in the body of a function.
Why am I getting an UnboundLocalError when the variable has a value? -------------------------------------------------------------------- It can be a surprise to get the :exc:`UnboundLocalError` in previously working code when it is modified by adding an assignment statement somewhere in the body of a function.
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divmod(x, y, /) Return the tuple (x//y, x%y). Invariant: div*y + mod == x. The slash at the end of the parameter list means that both parameters are positional-only. Thus, calling :func:`divmod` with keyword arguments would lead to an error::
trusted_official_docs
CPython Docs
divmod(x, y, /) Return the tuple (x//y, x%y). Invariant: div*y + mod == x. The slash at the end of the parameter list means that both parameters are positional-only. Thus, calling :func:`divmod` with keyword arguments would lead to an error::
divmod(x, y, /) Return the tuple (x//y, x%y). Invariant: div*y + mod == x. The slash at the end of the parameter list means that both parameters are positional-only. Thus, calling :func:`divmod` with keyword arguments would lead to an error::
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in that function's stack frame as contained in the stack trace. Normally, calling :func:`sys.exc_clear` will take care of this by clearing the last recorded exception. Finally, if your :meth:`!__del__` method raises an exception, a warning message is printed to :data:`sys.stderr`.
trusted_official_docs
CPython Docs
in that function's stack frame as contained in the stack trace. Normally, calling :func:`sys.exc_clear` will take care of this by clearing the last recorded exception. Finally, if your :meth:`!__del__` method raises an exception, a warning message is printed to :data:`sys.stderr`.
in that function's stack frame as contained in the stack trace. Normally, calling :func:`sys.exc_clear` will take care of this by clearing the last recorded exception. Finally, if your :meth:`!__del__` method raises an exception, a warning message is printed to :data:`sys.stderr`.
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>>> os.path.join(r'C:\this\will\work', '') 'C:\\this\\will\\work\\' Note that while a backslash will "escape" a quote for the purposes of determining where the raw string ends, no escaping occurs when interpreting the value of the raw string. That is, the backslash remains present in the value of the raw string::
trusted_official_docs
CPython Docs
>>> os.path.join(r'C:\this\will\work', '') 'C:\\this\\will\\work\\' Note that while a backslash will "escape" a quote for the purposes of determining where the raw string ends, no escaping occurs when interpreting the value of the raw string. That is, the backslash remains present in the value of the raw string::
>>> os.path.join(r'C:\this\will\work', '') 'C:\\this\\will\\work\\' Note that while a backslash will "escape" a quote for the purposes of determining where the raw string ends, no escaping occurs when interpreting the value of the raw string. That is, the backslash remains present in the value of the raw string::
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How do I modify a string in place? ---------------------------------- You can't, because strings are immutable. In most situations, you should simply construct a new string from the various parts you want to assemble it from. However, if you need an object with the ability to modify in-place Unicode data, try using an ...
trusted_official_docs
CPython Docs
How do I modify a string in place? ---------------------------------- You can't, because strings are immutable. In most situations, you should simply construct a new string from the various parts you want to assemble it from. However, if you need an object with the ability to modify in-place Unicode data, try using an ...
How do I modify a string in place? ---------------------------------- You can't, because strings are immutable. In most situations, you should simply construct a new string from the various parts you want to assemble it from. However, if you need an object with the ability to modify in-place Unicode data, try using an ...
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CPython Docs
file://datasets/cpython/Doc/faq/programming.rst
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supabase-export-v2
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return ``4**2``, that is ``16``. You can also verify this by changing the value of ``x`` and see how the results of the lambdas change:: >>> x = 8 >>> squares[2]() 64
trusted_official_docs
CPython Docs
return ``4**2``, that is ``16``. You can also verify this by changing the value of ``x`` and see how the results of the lambdas change:: >>> x = 8 >>> squares[2]() 64
return ``4**2``, that is ``16``. You can also verify this by changing the value of ``x`` and see how the results of the lambdas change:: >>> x = 8 >>> squares[2]() 64
python, official-docs, cpython, P0
Local_Trusted_Corpus
cf2d796d-71f3-41e0-92a5-9f8fd9860837
CPython Docs
file://datasets/cpython/Doc/faq/programming.rst
unknown
edda7b58-bd69-4060-9295-d9036b4690eb
1,845
supabase-export-v2
5b56ef2a9e3d9a9a
string ``S`` represents more than one line, with several empty lines at the end, the line terminators for all the blank lines will be removed:: >>> lines = ("line 1 \r\n" ... "\r\n" ... "\r\n") >>> lines.rstrip("\n\r") 'line 1 '
trusted_official_docs
CPython Docs
string ``S`` represents more than one line, with several empty lines at the end, the line terminators for all the blank lines will be removed:: >>> lines = ("line 1 \r\n" ... "\r\n" ... "\r\n") >>> lines.rstrip("\n\r") 'line 1 '
string ``S`` represents more than one line, with several empty lines at the end, the line terminators for all the blank lines will be removed:: >>> lines = ("line 1 \r\n" ... "\r\n" ... "\r\n") >>> lines.rstrip("\n\r") 'line 1 '
python, official-docs, cpython, P0
Local_Trusted_Corpus
cf97ba9e-834e-4dc4-adfd-a00f6f7c08f1
CPython Docs
file://datasets/cpython/Doc/faq/programming.rst
unknown
edda7b58-bd69-4060-9295-d9036b4690eb
2,082
supabase-export-v2
0ebf529cc1baa840
def __contains__(self, value): for v in self: if v is value or v == value: return True return False How can a subclass control what data is stored in an immutable instance? ------------------------------------------------------------------------
trusted_official_docs
CPython Docs
def __contains__(self, value): for v in self: if v is value or v == value: return True return False How can a subclass control what data is stored in an immutable instance? ------------------------------------------------------------------------
def __contains__(self, value): for v in self: if v is value or v == value: return True return False How can a subclass control what data is stored in an immutable instance? ------------------------------------------------------------------------
python, official-docs, cpython, P0
Local_Trusted_Corpus
cfeca28c-1311-4b13-94c4-f230c4a94074
CPython Docs
file://datasets/cpython/Doc/faq/programming.rst
unknown
edda7b58-bd69-4060-9295-d9036b4690eb
1,792
supabase-export-v2
0450be812e41b4d6
# First 10 Fibonacci numbers print(list(map(lambda x,f=lambda x,f:(f(x-1,f)+f(x-2,f)) if x>1 else 1: f(x,f), range(10)))) # Mandelbrot set print((lambda Ru,Ro,Iu,Io,IM,Sx,Sy:reduce(lambda x,y:x+'\n'+y,map(lambda y, Iu=Iu,Io=Io,Ru=Ru,Ro=Ro,Sy=Sy,L=lambda yc,Iu=Iu,Io=Io,Ru=Ru,Ro=Ro,i=IM, Sx=Sx,Sy=Sy:reduce(lambda x,y:...
trusted_official_docs
CPython Docs
# First 10 Fibonacci numbers print(list(map(lambda x,f=lambda x,f:(f(x-1,f)+f(x-2,f)) if x>1 else 1: f(x,f), range(10)))) # Mandelbrot set print((lambda Ru,Ro,Iu,Io,IM,Sx,Sy:reduce(lambda x,y:x+'\n'+y,map(lambda y, Iu=Iu,Io=Io,Ru=Ru,Ro=Ro,Sy=Sy,L=lambda yc,Iu=Iu,Io=Io,Ru=Ru,Ro=Ro,i=IM, Sx=Sx,Sy=Sy:reduce(lambda x,y:...
# First 10 Fibonacci numbers print(list(map(lambda x,f=lambda x,f:(f(x-1,f)+f(x-2,f)) if x>1 else 1: f(x,f), range(10)))) # Mandelbrot set print((lambda Ru,Ro,Iu,Io,IM,Sx,Sy:reduce(lambda x,y:x+'\n'+y,map(lambda y, Iu=Iu,Io=Io,Ru=Ru,Ro=Ro,Sy=Sy,L=lambda yc,Iu=Iu,Io=Io,Ru=Ru,Ro=Ro,i=IM, Sx=Sx,Sy=Sy:reduce(lambda x,y:...
python, official-docs, cpython, P0
Local_Trusted_Corpus
d045c504-831d-4972-bfe0-d7a19e84b9c8
CPython Docs
file://datasets/cpython/Doc/faq/programming.rst
unknown
edda7b58-bd69-4060-9295-d9036b4690eb
1,948
supabase-export-v2
d4d5ebaf204b4276
>>> result = a_tuple[0] + 1 >>> a_tuple[0] = result Traceback (most recent call last): ... TypeError: 'tuple' object does not support item assignment It is the assignment part of the operation that produces the error, since a tuple is immutable.
trusted_official_docs
CPython Docs
>>> result = a_tuple[0] + 1 >>> a_tuple[0] = result Traceback (most recent call last): ... TypeError: 'tuple' object does not support item assignment It is the assignment part of the operation that produces the error, since a tuple is immutable.
>>> result = a_tuple[0] + 1 >>> a_tuple[0] = result Traceback (most recent call last): ... TypeError: 'tuple' object does not support item assignment It is the assignment part of the operation that produces the error, since a tuple is immutable.
python, official-docs, cpython, P0
Local_Trusted_Corpus
d0b94cb5-b0e2-43d8-8009-a3cd224dd709
CPython Docs
file://datasets/cpython/Doc/faq/programming.rst
unknown
edda7b58-bd69-4060-9295-d9036b4690eb
1,728
supabase-export-v2
fb20ddc9f1bc1d35
you want to know if two variables refer to the same object or not, you can use the :keyword:`is` operator, or the built-in function :func:`id`. How do I write a function with output parameters (call by reference)? ---------------------------------------------------------------------
trusted_official_docs
CPython Docs
you want to know if two variables refer to the same object or not, you can use the :keyword:`is` operator, or the built-in function :func:`id`. How do I write a function with output parameters (call by reference)? ---------------------------------------------------------------------
you want to know if two variables refer to the same object or not, you can use the :keyword:`is` operator, or the built-in function :func:`id`. How do I write a function with output parameters (call by reference)? ---------------------------------------------------------------------
python, official-docs, cpython, P0
Local_Trusted_Corpus
d32b1d6d-dcca-4a15-8230-288825cba5d8
CPython Docs
file://datasets/cpython/Doc/faq/programming.rst
unknown
edda7b58-bd69-4060-9295-d9036b4690eb
1,767
supabase-export-v2
8911f7155b632de4
How can my code discover the name of an object? ----------------------------------------------- Generally speaking, it can't, because objects don't really have names. Essentially, assignment always binds a name to a value; the same is true of ``def`` and ``class`` statements, but in that case the value is a callable. C...
trusted_official_docs
CPython Docs
How can my code discover the name of an object? ----------------------------------------------- Generally speaking, it can't, because objects don't really have names. Essentially, assignment always binds a name to a value; the same is true of ``def`` and ``class`` statements, but in that case the value is a callable. C...
How can my code discover the name of an object? ----------------------------------------------- Generally speaking, it can't, because objects don't really have names. Essentially, assignment always binds a name to a value; the same is true of ``def`` and ``class`` statements, but in that case the value is a callable. C...
python, official-docs, cpython, P0
Local_Trusted_Corpus