Maintainability

The CPython startup sequence as of Python 3.6 was difficult to understand, and even more difficult to modify. It was not clear what state the interpreter was in while much of the initialization code executed, leading to behaviour such as lists, dictionaries and Unicode values being created prior to the call to Py_Initialize when the -X or -W options are used [1].

By moving to an explicitly multi-phase startup sequence, developers should only need to understand:

• which APIs and features are available prior to pre-configuration (essentially none, except for the pre-configuration API itself)
• which APIs and features are available prior to core runtime configuration, and will implicitly run the pre-configuration with default settings that match the behaviour of Python 3.6 if the pre-configuration hasn’t been run explicitly
• which APIs and features are only available after the main interpreter has been fully configured (which will hopefully be a relatively small subset of the full C API)

The first two aspects of that are covered by PEP 587, while the details of the latter distinction are still being considered.

By basing the new design on a combination of C structures and Python data types, it should also be easier to modify the system in the future to add new configuration options.

Testability

One of the problems with the complexity of the CPython startup sequence is the combinatorial explosion of possible interactions between different configuration settings.

This concern impacts both the design of the new initialisation system, and the proposed approach for getting there.

Performance

CPython is used heavily to run short scripts where the runtime is dominated by the interpreter initialization time. Any changes to the startup sequence should minimise their impact on the startup overhead.

Experience with the importlib migration suggests that the startup time is dominated by IO operations. However, to monitor the impact of any changes, a simple benchmark can be used to check how long it takes to start and then tear down the interpreter:

python3 -m timeit -s "from subprocess import call" "call(['./python', '-Sc', 'pass'])"

Current numbers on my system for Python 3.7 (as built by the Fedora project):

$ python3 -m timeit -s "from subprocess import call" "call(['python3', '-Sc', 'pass'])"
50 loops, best of 5: 6.48 msec per loop

(TODO: run this microbenchmark with perf rather than the stdlib timeit)

This PEP is not expected to have any significant effect on the startup time, as it is aimed primarily at reordering the existing initialization sequence, without making substantial changes to the individual steps.

However, if this simple check suggests that the proposed changes to the initialization sequence may pose a performance problem, then a more sophisticated microbenchmark will be developed to assist in investigation.

Interpreter Initialization Phases

The following distinct interpreter initialisation phases are proposed:

• Uninitialized:
  • Not really a phase, but the absence of a phase
  • Py_IsInitializing() returns 0
  • Py_IsRuntimeInitialized() returns 0
  • Py_IsInitialized() returns 0
  • The embedding application determines which memory allocator to use, and which encoding to use to access operating system interfaces (or chooses to delegate those decisions to the Python runtime)
  • Application starts the initialization process by calling one of the Py_PreInitialize APIs (see PEP 587)
• Runtime Pre-Initialization:
  • no interpreter is available
  • Py_IsInitializing() returns 1
  • Py_IsRuntimeInitialized() returns 0
  • Py_IsInitialized() returns 0
  • The embedding application determines the settings required to initialize the core CPython runtime and create the main interpreter and moves to the next phase by calling Py_InitializeRuntime
  • Note: as of PEP 587, the embedding application instead calls Py_Main(), Py_UnixMain, or one of the Py_Initialize APIs, and hence jumps directly to the Initialized state.
• Main Interpreter Initialization:
  • the builtin data types and other core runtime services are available
  • the main interpreter is available, but only partially configured
  • Py_IsInitializing() returns 1
  • Py_IsRuntimeInitialized() returns 1
  • Py_IsInitialized() returns 0
  • The embedding application determines and applies the settings required to complete the initialization process by calling Py_InitializeMainInterpreter
  • Note: as of PEP 587, this state is not reachable via any public API, it only exists as an implicit internal state while one of the Py_Initialize functions is running
• Initialized:
  • the main interpreter is available and fully operational, but __main__ related metadata is incomplete
  • Py_IsInitializing() returns 0
  • Py_IsRuntimeInitialized() returns 1
  • Py_IsInitialized() returns 1

Invocation of Phases

All listed phases will be used by the standard CPython interpreter and the proposed System Python interpreter.

An embedding application may still continue to leave initialization almost entirely under CPython’s control by using the existing Py_Initialize or Py_Main() APIs - backwards compatibility will be preserved.

Alternatively, if an embedding application wants greater control over CPython’s initial state, it will be able to use the new, finer grained API, which allows the embedding application greater control over the initialization process.

PEP 587 covers an initial iteration of that API, separating out the pre-initialization phase without attempting to separate core runtime initialization from main interpreter initialization.

Uninitialized State

The uninitialized state is where an embedding application determines the settings which are required in order to be able to correctly pass configurations settings to the embedded Python runtime.

This covers telling Python which memory allocator to use, as well as which text encoding to use when processing provided settings.

PEP 587 defines the settings needed to exit this state in its PyPreConfig struct.

A new query API will allow code to determine if the interpreter hasn’t even started the initialization process:

int Py_IsInitializing();

The query for a completely uninitialized environment would then be !(Py_Initialized() || Py_Initializing()).

Runtime Pre-Initialization Phase

The pre-initialization phase is where an embedding application determines the settings which are absolutely required before the CPython runtime can be initialized at all. Currently, the primary configuration settings in this category are those related to the randomised hash algorithm - the hash algorithms must be consistent for the lifetime of the process, and so they must be in place before the core interpreter is created.

The essential settings needed are a flag indicating whether or not to use a specific seed value for the randomised hashes, and if so, the specific value for the seed (a seed value of zero disables randomised hashing). In addition, due to the possible use of PYTHONHASHSEED in configuring the hash randomisation, the question of whether or not to consider environment variables must also be addressed early. Finally, to support the CPython build process, an option is offered to completely disable the import system.

The proposed APIs for this step in the startup sequence are:

PyInitError Py_InitializeRuntime(
    const PyRuntimeConfig *config
);

PyInitError Py_InitializeRuntimeFromArgs(
    const PyRuntimeConfig *config, int argc, char **argv
);

PyInitError Py_InitializeRuntimeFromWideArgs(
    const PyRuntimeConfig *config, int argc, wchar_t **argv
);

If Py_IsInitializing() is false, the Py_InitializeRuntime functions will implicitly call the corresponding Py_PreInitialize function. The use_environment setting will be passed down, while other settings will be processed according to their defaults, as described in PEP 587.

The PyInitError return type is defined in PEP 587, and allows an embedding application to gracefully handle Python runtime initialization failures, rather than having the entire process abruptly terminated by Py_FatalError.

The new PyRuntimeConfig struct holds the settings required for preliminary configuration of the core runtime and creation of the main interpreter:

/* Note: if changing anything in PyRuntimeConfig, also update
 * PyRuntimeConfig_INIT */
typedef struct {
    bool use_environment;     /* as in PyPreConfig, PyConfig from PEP 587 */
    int use_hash_seed;        /* PYTHONHASHSEED, as in PyConfig from PEP 587 */
    unsigned long hash_seed;  /* PYTHONHASHSEED, as in PyConfig from PEP 587 */
    bool _install_importlib;  /* Needed by freeze_importlib */
} PyRuntimeConfig;

/* Rely on the "designated initializer" feature of C99 */
#define PyRuntimeConfig_INIT {.use_hash_seed=-1}

The core configuration settings pointer may be NULL, in which case the default values are as specified in PyRuntimeConfig_INIT.

The PyRuntimeConfig_INIT macro is designed to allow easy initialization of a struct instance with sensible defaults:

PyRuntimeConfig runtime_config = PyRuntimeConfig_INIT;

use_environment controls the processing of all Python related environment variables. If the flag is true, then PYTHONHASHSEED is processed normally. Otherwise, all Python-specific environment variables are considered undefined (exceptions may be made for some OS specific environment variables, such as those used on Mac OS X to communicate between the App bundle and the main Python binary).

use_hash_seed controls the configuration of the randomised hash algorithm. If it is zero, then randomised hashes with a random seed will be used. It is positive, then the value in hash_seed will be used to seed the random number generator. If the hash_seed is zero in this case, then the randomised hashing is disabled completely.

If use_hash_seed is negative (and use_environment is true), then CPython will inspect the PYTHONHASHSEED environment variable. If the environment variable is not set, is set to the empty string, or to the value "random", then randomised hashes with a random seed will be used. If the environment variable is set to the string "0" the randomised hashing will be disabled. Otherwise, the hash seed is expected to be a string representation of an integer in the range [0; 4294967295].

To make it easier for embedding applications to use the PYTHONHASHSEED processing with a different data source, the following helper function will be added to the C API:

int Py_ReadHashSeed(char *seed_text,
                    int *use_hash_seed,
                    unsigned long *hash_seed);

This function accepts a seed string in seed_text and converts it to the appropriate flag and seed values. If seed_text is NULL, the empty string or the value "random", both use_hash_seed and hash_seed will be set to zero. Otherwise, use_hash_seed will be set to 1 and the seed text will be interpreted as an integer and reported as hash_seed. On success the function will return zero. A non-zero return value indicates an error (most likely in the conversion to an integer).

The _install_importlib setting is used as part of the CPython build process to create an interpreter with no import capability at all. It is considered private to the CPython development team (hence the leading underscore), as the only currently supported use case is to permit compiler changes that invalidate the previously frozen bytecode for importlib._bootstrap without breaking the build process.

The aim is to keep this initial level of configuration as small as possible in order to keep the bootstrapping environment consistent across different embedding applications. If we can create a valid interpreter state without the setting, then the setting should appear solely in the comprehensive PyConfig struct rather than in the core runtime configuration.

A new query API will allow code to determine if the interpreter is in the bootstrapping state between the core runtime initialization and the creation of the main interpreter state and the completion of the bulk of the main interpreter initialization process:

int Py_IsRuntimeInitialized();

Attempting to call Py_InitializeRuntime() again when Py_IsRuntimeInitialized() is already true is reported as a user configuration error. (TBC, as existing public initialisation APIs support being called multiple times without error, and simply ignore changes to any write-once settings. It may make sense to keep that behaviour rather than trying to make the new API stricter than the old one)

As frozen bytecode may now be legitimately run in an interpreter which is not yet fully initialized, sys.flags will gain a new initialized flag.

With the core runtime initialised, the main interpreter and most of the CPython C API should be fully functional except that:

• compilation is not allowed (as the parser and compiler are not yet configured properly)
• creation of subinterpreters is not allowed
• creation of additional thread states is not allowed
• The following attributes in the sys module are all either missing or None: * sys.path * sys.argv * sys.executable * sys.base_exec_prefix * sys.base_prefix * sys.exec_prefix * sys.prefix * sys.warnoptions * sys.dont_write_bytecode * sys.stdin * sys.stdout
• The filesystem encoding is not yet defined
• The IO encoding is not yet defined
• CPython signal handlers are not yet installed
• Only builtin and frozen modules may be imported (due to above limitations)
• sys.stderr is set to a temporary IO object using unbuffered binary mode
• The sys.flags attribute exists, but the individual flags may not yet have their final values.
• The sys.flags.initialized attribute is set to 0
• The warnings module is not yet initialized
• The __main__ module does not yet exist

<TBD: identify any other notable missing functionality>

The main things made available by this step will be the core Python data types, in particular dictionaries, lists and strings. This allows them to be used safely for all of the remaining configuration steps (unlike the status quo).

In addition, the current thread will possess a valid Python thread state, allowing any further configuration data to be stored on the main interpreter object rather than in C process globals.

Any call to Py_InitializeRuntime() must have a matching call to Py_Finalize(). It is acceptable to skip calling Py_InitializeMainInterpreter() in between (e.g. if attempting to build the main interpreter configuration settings fails).

Determining the remaining configuration settings

The next step in the initialization sequence is to determine the remaining settings needed to complete the process. No changes are made to the interpreter state at this point. The core APIs for this step are:

int Py_BuildPythonConfig(
    PyConfigAsObjects *py_config, const PyConfig *c_config
);

int Py_BuildPythonConfigFromArgs(
    PyConfigAsObjects *py_config, const PyConfig *c_config, int argc, char **argv
);

int Py_BuildPythonConfigFromWideArgs(
    PyConfigAsObjects *py_config, const PyConfig *c_config, int argc, wchar_t **argv
);

The py_config argument should be a pointer to a PyConfigAsObjects struct (which may be a temporary one stored on the C stack). For any already configured value (i.e. any non-NULL pointer), CPython will sanity check the supplied value, but otherwise accept it as correct.

A struct is used rather than a Python dictionary as the struct is easier to work with from C, the list of supported fields is fixed for a given CPython version and only a read-only view needs to be exposed to Python code (which is relatively straightforward, thanks to the infrastructure already put in place to expose sys.implementation).

Unlike Py_InitializeRuntime, this call will raise a Python exception and report an error return rather than returning a Python initialization specific C struct if a problem is found with the config data.

Any supported configuration setting which is not already set will be populated appropriately in the supplied configuration struct. The default configuration can be overridden entirely by setting the value before calling Py_BuildPythonConfig. The provided value will then also be used in calculating any other settings derived from that value.

Alternatively, settings may be overridden after the Py_BuildPythonConfig call (this can be useful if an embedding application wants to adjust a setting rather than replace it completely, such as removing sys.path[0]).

The c_config argument is an optional pointer to a PyConfig structure, as defined in PEP 587. If provided, it is used in preference to reading settings directly from the environment or process global state.

Merely reading the configuration has no effect on the interpreter state: it only modifies the passed in configuration struct. The settings are not applied to the running interpreter until the Py_InitializeMainInterpreter call (see below).

Supported configuration settings

The interpreter configuration is split into two parts: settings which are either relevant only to the main interpreter or must be identical across the main interpreter and all subinterpreters, and settings which may vary across subinterpreters.

NOTE: For initial implementation purposes, only the flag indicating whether or not the interpreter is the main interpreter will be configured on a per interpreter basis. Other fields will be reviewed for whether or not they can feasibly be made interpreter specific over the course of the implementation.

The PyConfigAsObjects struct mirrors the PyConfig struct from PEP 587, but uses full Python objects to store values, rather than C level data types. It adds raw_argv and argv list fields, so later initialisation steps don’t need to accept those separately.

Fields are always pointers to Python data types, with unset values indicated by NULL:

typedef struct {
    /* Argument processing */
    PyListObject *raw_argv;
    PyListObject *argv;
    PyListObject *warnoptions; /* -W switch, PYTHONWARNINGS */
    PyDictObject *xoptions;    /* -X switch */

    /* Filesystem locations */
    PyUnicodeObject *program_name;
    PyUnicodeObject *executable;
    PyUnicodeObject *prefix;           /* PYTHONHOME */
    PyUnicodeObject *exec_prefix;      /* PYTHONHOME */
    PyUnicodeObject *base_prefix;      /* pyvenv.cfg */
    PyUnicodeObject *base_exec_prefix; /* pyvenv.cfg */

    /* Site module */
    PyBoolObject *enable_site_config;  /* -S switch (inverted) */
    PyBoolObject *no_user_site;        /* -s switch, PYTHONNOUSERSITE */

    /* Import configuration */
    PyBoolObject *dont_write_bytecode; /* -B switch, PYTHONDONTWRITEBYTECODE */
    PyBoolObject *ignore_module_case;  /* PYTHONCASEOK */
    PyListObject *import_path;        /* PYTHONPATH (etc) */

    /* Standard streams */
    PyBoolObject    *use_unbuffered_io; /* -u switch, PYTHONUNBUFFEREDIO */
    PyUnicodeObject *stdin_encoding;    /* PYTHONIOENCODING */
    PyUnicodeObject *stdin_errors;      /* PYTHONIOENCODING */
    PyUnicodeObject *stdout_encoding;   /* PYTHONIOENCODING */
    PyUnicodeObject *stdout_errors;     /* PYTHONIOENCODING */
    PyUnicodeObject *stderr_encoding;   /* PYTHONIOENCODING */
    PyUnicodeObject *stderr_errors;     /* PYTHONIOENCODING */

    /* Filesystem access */
    PyUnicodeObject *fs_encoding;

    /* Debugging output */
    PyBoolObject *debug_parser;    /* -d switch, PYTHONDEBUG */
    PyLongObject *verbosity;       /* -v switch */

    /* Code generation */
    PyLongObject *bytes_warnings;  /* -b switch */
    PyLongObject *optimize;        /* -O switch */

    /* Signal handling */
    PyBoolObject *install_signal_handlers;

    /* Implicit execution */
    PyUnicodeObject *startup_file;  /* PYTHONSTARTUP */

    /* Main module
     *
     * If prepare_main is set, at most one of the main_* settings should
     * be set before calling PyRun_PrepareMain (Py_ReadMainInterpreterConfig
     * will set one of them based on the command line arguments if
     * prepare_main is non-zero when that API is called).
    PyBoolObject    *prepare_main;
    PyUnicodeObject *main_source; /* -c switch */
    PyUnicodeObject *main_path;   /* filesystem path */
    PyUnicodeObject *main_module; /* -m switch */
    PyCodeObject    *main_code;   /* Run directly from a code object */
    PyObject        *main_stream; /* Run from stream */
    PyBoolObject    *run_implicit_code; /* Run implicit code during prep */

    /* Interactive main
     *
     * Note: Settings related to interactive mode are very much in flux.
     */
    PyObject *prompt_stream;      /* Output interactive prompt */
    PyBoolObject *show_banner;    /* -q switch (inverted) */
    PyBoolObject *inspect_main;   /* -i switch, PYTHONINSPECT */

} PyConfigAsObjects;

The PyInterpreterConfig struct holds the settings that may vary between the main interpreter and subinterpreters. For the main interpreter, these settings are automatically populated by Py_InitializeMainInterpreter().

typedef struct {
    PyBoolObject *is_main_interpreter;    /* Easily check for subinterpreters */
} PyInterpreterConfig;

As these structs consist solely of object pointers, no explicit initializer definitions are needed - C99’s default initialization of struct memory to zero is sufficient.

Completing the main interpreter initialization

The final step in the initialization process is to actually put the configuration settings into effect and finish bootstrapping the main interpreter up to full operation:

int Py_InitializeMainInterpreter(const PyConfigAsObjects *config);

Like Py_BuildPythonConfig, this call will raise an exception and report an error return rather than exhibiting fatal errors if a problem is found with the config data. (TBC, as existing public initialisation APIs support being called multiple times without error, and simply ignore changes to any write-once settings. It may make sense to keep that behaviour rather than trying to make the new API stricter than the old one)

All configuration settings are required - the configuration struct should always be passed through Py_BuildPythonConfig to ensure it is fully populated.

After a successful call Py_IsInitialized() will become true and Py_IsInitializing() will become false. The caveats described above for the interpreter during the phase where only the core runtime is initialized will no longer hold.

Attempting to call Py_InitializeMainInterpreter() again when Py_IsInitialized() is true is an error.

However, some metadata related to the __main__ module may still be incomplete:

• sys.argv[0] may not yet have its final value
  • it will be -m when executing a module or package with CPython
  • it will be the same as sys.path[0] rather than the location of the __main__ module when executing a valid sys.path entry (typically a zipfile or directory)
  • otherwise, it will be accurate:
    • the script name if running an ordinary script
    • -c if executing a supplied string
    • - or the empty string if running from stdin
• the metadata in the __main__ module will still indicate it is a builtin module

This function will normally implicitly import site as its final operation (after Py_IsInitialized() is already set). Setting the “enable_site_config” flag to Py_False in the configuration settings will disable this behaviour, as well as eliminating any side effects on global state if import site is later explicitly executed in the process.

Preparing the main module

This subphase completes the population of the __main__ module related metadata, without actually starting execution of the __main__ module code.

It is handled by calling the following API:

int PyRun_PrepareMain();

This operation is only permitted for the main interpreter, and will raise RuntimeError when invoked from a thread where the current thread state belongs to a subinterpreter.

The actual processing is driven by the main related settings stored in the interpreter state as part of the configuration struct.

If prepare_main is zero, this call does nothing.

If all of main_source, main_path, main_module, main_stream and main_code are NULL, this call does nothing.

If more than one of main_source, main_path, main_module, main_stream or main_code are set, RuntimeError will be reported.

If main_code is already set, then this call does nothing.

If main_stream is set, and run_implicit_code is also set, then the file identified in startup_file will be read, compiled and executed in the __main__ namespace.

If main_source, main_path or main_module are set, then this call will take whatever steps are needed to populate main_code:

• For main_source, the supplied string will be compiled and saved to main_code.
• For main_path:
  • if the supplied path is recognised as a valid sys.path entry, it is inserted as sys.path[0], main_module is set to __main__ and processing continues as for main_module below.
  • otherwise, path is read as a CPython bytecode file
  • if that fails, it is read as a Python source file and compiled
  • in the latter two cases, the code object is saved to main_code and __main__.__file__ is set appropriately
• For main_module:
  • any parent package is imported
  • the loader for the module is determined
  • if the loader indicates the module is a package, add .__main__ to the end of main_module and try again (if the final name segment is already .__main__ then fail immediately)
  • once the module source code is located, save the compiled module code as main_code and populate the following attributes in __main__ appropriately: __name__, __loader__, __file__, __cached__, __package__.

(Note: the behaviour described in this section isn’t new, it’s a write-up of the current behaviour of the CPython interpreter adjusted for the new configuration system)

Executing the main module

This subphase covers the execution of the actual __main__ module code.

It is handled by calling the following API:

int PyRun_ExecMain();

This operation is only permitted for the main interpreter, and will raise RuntimeError when invoked from a thread where the current thread state belongs to a subinterpreter.

The actual processing is driven by the main related settings stored in the interpreter state as part of the configuration struct.

If both main_stream and main_code are NULL, this call does nothing.

If both main_stream and main_code are set, RuntimeError will be reported.

If main_stream and prompt_stream are both set, main execution will be delegated to a new internal API:

int _PyRun_InteractiveMain(PyObject *input, PyObject* output);

If main_stream is set and prompt_stream is NULL, main execution will be delegated to a new internal API:

int _PyRun_StreamInMain(PyObject *input);

If main_code is set, main execution will be delegated to a new internal API:

int _PyRun_CodeInMain(PyCodeObject *code);

After execution of main completes, if inspect_main is set, or the PYTHONINSPECT environment variable has been set, then PyRun_ExecMain will invoke _PyRun_InteractiveMain(sys.__stdin__, sys.__stdout__).

Internal Storage of Configuration Data

The interpreter state will be updated to include details of the configuration settings supplied during initialization by extending the interpreter state object with at least an embedded copy of the PyConfigAsObjects and PyInterpreterConfig structs.

For debugging purposes, the configuration settings will be exposed as a sys._configuration simple namespace (similar to sys.flags and sys.implementation. The attributes will be themselves by simple namespaces corresponding to the two levels of configuration setting:

• all_interpreters
• active_interpreter

Field names will match those in the configuration structs, except for hash_seed, which will be deliberately excluded.

An underscored attribute is chosen deliberately, as these configuration settings are part of the CPython implementation, rather than part of the Python language definition. If new settings are needed to support cross-implementation compatibility in the standard library, then those should be agreed with the other implementations and exposed as new required attributes on sys.implementation, as described in PEP 421.

These are snapshots of the initial configuration settings. They are not modified by the interpreter during runtime (except as noted above).

Creating and Configuring Subinterpreters

As the new configuration settings are stored in the interpreter state, they need to be initialised when a new subinterpreter is created. This turns out to be trickier than one might expect due to PyThreadState_Swap(NULL); (which is fortunately exercised by CPython’s own embedding tests, allowing this problem to be detected during development).

To provide a straightforward solution for this case, the PEP proposes to add a new API:

Py_InterpreterState *Py_InterpreterState_Main();

This will be a counterpart to Py_InterpreterState_Head(), only reporting the oldest currently existing interpreter rather than the newest. If Py_NewInterpreter() is called from a thread with an existing thread state, then the interpreter configuration for that thread will be used when initialising the new subinterpreter. If there is no current thread state, the configuration from Py_InterpreterState_Main() will be used.

While the existing Py_InterpreterState_Head() API could be used instead, that reference changes as subinterpreters are created and destroyed, while PyInterpreterState_Main() will always refer to the initial interpreter state created in Py_InitializeRuntime().

A new constraint is also added to the embedding API: attempting to delete the main interpreter while subinterpreters still exist will now be a fatal error.

Stable ABI

Most of the APIs proposed in this PEP are excluded from the stable ABI, as embedding a Python interpreter involves a much higher degree of coupling than merely writing an extension module.

The only newly exposed APIs that will be part of the stable ABI are the Py_IsInitializing() and Py_IsRuntimeInitialized() queries.

Build time configuration

This PEP makes no changes to the handling of build time configuration settings, and thus has no effect on the contents of sys.implementation or the result of sysconfig.get_config_vars().

Backwards Compatibility

Backwards compatibility will be preserved primarily by ensuring that Py_BuildPythonConfig() interrogates all the previously defined configuration settings stored in global variables and environment variables, and that Py_InitializeMainInterpreter() writes affected settings back to the relevant locations.

One acknowledged incompatibility is that some environment variables which are currently read lazily may instead be read once during interpreter initialization. As the reference implementation matures, these will be discussed in more detail on a case-by-case basis. The environment variables which are currently known to be looked up dynamically are:

• PYTHONCASEOK: writing to os.environ['PYTHONCASEOK'] will no longer dynamically alter the interpreter’s handling of filename case differences on import (TBC)
• PYTHONINSPECT: os.environ['PYTHONINSPECT'] will still be checked after execution of the __main__ module terminates

The Py_Initialize() style of initialization will continue to be supported. It will use (at least some elements of) the new API internally, but will continue to exhibit the same behaviour as it does today, ensuring that sys.argv is not populated until a subsequent PySys_SetArgv call (TBC). All APIs that currently support being called prior to Py_Initialize() will continue to do so, and will also support being called prior to Py_InitializeRuntime().

Ignoring Environment Variables

The -E command line option allows all environment variables to be ignored when initializing the Python interpreter. An embedding application can enable this behaviour by setting Py_IgnoreEnvironmentFlag before calling Py_Initialize().

In the CPython source code, the Py_GETENV macro implicitly checks this flag, and always produces NULL if it is set.

<TBD: I believe PYTHONCASEOK is checked regardless of this setting > <TBD: Does -E also ignore Windows registry keys? >

Randomised Hashing

The randomised hashing is controlled via the -R command line option (in releases prior to 3.3), as well as the PYTHONHASHSEED environment variable.

In Python 3.3, only the environment variable remains relevant. It can be used to disable randomised hashing (by using a seed value of 0) or else to force a specific hash value (e.g. for repeatability of testing, or to share hash values between processes)

However, embedding applications must use the Py_HashRandomizationFlag to explicitly request hash randomisation (CPython sets it in Py_Main() rather than in Py_Initialize()).

The new configuration API should make it straightforward for an embedding application to reuse the PYTHONHASHSEED processing with a text based configuration setting provided by other means (e.g. a config file or separate environment variable).

Locating Python and the standard library

The location of the Python binary and the standard library is influenced by several elements. The algorithm used to perform the calculation is not documented anywhere other than in the source code [3], [4]. Even that description is incomplete, as it failed to be updated for the virtual environment support added in Python 3.3 (detailed in PEP 405).

These calculations are affected by the following function calls (made prior to calling Py_Initialize()) and environment variables:

• Py_SetProgramName()
• Py_SetPythonHome()
• PYTHONHOME

The filesystem is also inspected for pyvenv.cfg files (see PEP 405) or, failing that, a lib/os.py (Windows) or lib/python$VERSION/os.py file.

The build time settings for PREFIX and EXEC_PREFIX are also relevant, as are some registry settings on Windows. The hardcoded fallbacks are based on the layout of the CPython source tree and build output when working in a source checkout.

Configuring sys.path

An embedding application may call Py_SetPath() prior to Py_Initialize() to completely override the calculation of sys.path. It is not straightforward to only allow some of the calculations, as modifying sys.path after initialization is already complete means those modifications will not be in effect when standard library modules are imported during the startup sequence.

If Py_SetPath() is not used prior to the first call to Py_GetPath() (implicit in Py_Initialize()), then it builds on the location data calculations above to calculate suitable path entries, along with the PYTHONPATH environment variable.

<TBD: On Windows, there’s also a bunch of stuff to do with the registry>

The site module, which is implicitly imported at startup (unless disabled via the -S option) adds additional paths to this initial set of paths, as described in its documentation [5].

The -s command line option can be used to exclude the user site directory from the list of directories added. Embedding applications can control this by setting the Py_NoUserSiteDirectory global variable.

The following commands can be used to check the default path configurations for a given Python executable on a given system:

• ./python -c "import sys, pprint; pprint.pprint(sys.path)" - standard configuration
• ./python -s -c "import sys, pprint; pprint.pprint(sys.path)" - user site directory disabled
• ./python -S -c "import sys, pprint; pprint.pprint(sys.path)" - all site path modifications disabled

(Note: you can see similar information using -m site instead of -c, but this is slightly misleading as it calls os.abspath on all of the path entries, making relative path entries look absolute. Using the site module also causes problems in the last case, as on Python versions prior to 3.3, explicitly importing site will carry out the path modifications -S avoids, while on 3.3+ combining -m site with -S currently fails)

The calculation of sys.path[0] is comparatively straightforward:

• For an ordinary script (Python source or compiled bytecode), sys.path[0] will be the directory containing the script.
• For a valid sys.path entry (typically a zipfile or directory), sys.path[0] will be that path
• For an interactive session, running from stdin or when using the -c or -m switches, sys.path[0] will be the empty string, which the import system interprets as allowing imports from the current directory

Configuring sys.argv

Unlike most other settings discussed in this PEP, sys.argv is not set implicitly by Py_Initialize(). Instead, it must be set via an explicitly call to Py_SetArgv().

CPython calls this in Py_Main() after calling Py_Initialize(). The calculation of sys.argv[1:] is straightforward: they’re the command line arguments passed after the script name or the argument to the -c or -m options.

The calculation of sys.argv[0] is a little more complicated:

• For an ordinary script (source or bytecode), it will be the script name
• For a sys.path entry (typically a zipfile or directory) it will initially be the zipfile or directory name, but will later be changed by the runpy module to the full path to the imported __main__ module.
• For a module specified with the -m switch, it will initially be the string "-m", but will later be changed by the runpy module to the full path to the executed module.
• For a package specified with the -m switch, it will initially be the string "-m", but will later be changed by the runpy module to the full path to the executed __main__ submodule of the package.
• For a command executed with -c, it will be the string "-c"
• For explicitly requested input from stdin, it will be the string "-"
• Otherwise, it will be the empty string

Embedding applications must call Py_SetArgv themselves. The CPython logic for doing so is part of Py_Main() and is not exposed separately. However, the runpy module does provide roughly equivalent logic in runpy.run_module and runpy.run_path.

Other configuration settings

TBD: Cover the initialization of the following in more detail:

• Completely disabling the import system
• The initial warning system state:
  • sys.warnoptions
  • (-W option, PYTHONWARNINGS)
• Arbitrary extended options (e.g. to automatically enable faulthandler):
  • sys._xoptions
  • (-X option)
• The filesystem encoding used by:
  • sys.getfsencoding
  • os.fsencode
  • os.fsdecode
• The IO encoding and buffering used by:
  • sys.stdin
  • sys.stdout
  • sys.stderr
  • (-u option, PYTHONIOENCODING, PYTHONUNBUFFEREDIO)
• Whether or not to implicitly cache bytecode files:
  • sys.dont_write_bytecode
  • (-B option, PYTHONDONTWRITEBYTECODE)
• Whether or not to enforce correct case in filenames on case-insensitive platforms
  • os.environ["PYTHONCASEOK"]
• The other settings exposed to Python code in sys.flags:
  • debug (Enable debugging output in the pgen parser)
  • inspect (Enter interactive interpreter after __main__ terminates)
  • interactive (Treat stdin as a tty)
  • optimize (__debug__ status, write .pyc or .pyo, strip doc strings)
  • no_user_site (don’t add the user site directory to sys.path)
  • no_site (don’t implicitly import site during startup)
  • ignore_environment (whether environment vars are used during config)
  • verbose (enable all sorts of random output)
  • bytes_warning (warnings/errors for implicit str/bytes interaction)
  • quiet (disable banner output even if verbose is also enabled or stdin is a tty and the interpreter is launched in interactive mode)
• Whether or not CPython’s signal handlers should be installed

Much of the configuration of CPython is currently handled through C level global variables:

Py_BytesWarningFlag (-b)
Py_DebugFlag (-d option)
Py_InspectFlag (-i option, PYTHONINSPECT)
Py_InteractiveFlag (property of stdin, cannot be overridden)
Py_OptimizeFlag (-O option, PYTHONOPTIMIZE)
Py_DontWriteBytecodeFlag (-B option, PYTHONDONTWRITEBYTECODE)
Py_NoUserSiteDirectory (-s option, PYTHONNOUSERSITE)
Py_NoSiteFlag (-S option)
Py_UnbufferedStdioFlag (-u, PYTHONUNBUFFEREDIO)
Py_VerboseFlag (-v option, PYTHONVERBOSE)

For the above variables, the conversion of command line options and environment variables to C global variables is handled by Py_Main, so each embedding application must set those appropriately in order to change them from their defaults.

Some configuration can only be provided as OS level environment variables:

PYTHONSTARTUP
PYTHONCASEOK
PYTHONIOENCODING

The Py_InitializeEx() API also accepts a boolean flag to indicate whether or not CPython’s signal handlers should be installed.

Finally, some interactive behaviour (such as printing the introductory banner) is triggered only when standard input is reported as a terminal connection by the operating system.

TBD: Document how the “-x” option is handled (skips processing of the first comment line in the main script)

Also see detailed sequence of operations notes at [1].