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cdgriffith/Reusables
reusables/log.py
get_file_handler
def get_file_handler(file_path="out.log", level=logging.INFO, log_format=log_formats.easy_read, handler=logging.FileHandler, **handler_kwargs): """ Set up a file handler to add to a logger. :param file_path: file to write the log to, defaults to out.log :param level: logging level to set handler at :param log_format: formatter to use :param handler: logging handler to use, defaults to FileHandler :param handler_kwargs: options to pass to the handler :return: handler """ fh = handler(file_path, **handler_kwargs) fh.setLevel(level) fh.setFormatter(logging.Formatter(log_format)) return fh
python
def get_file_handler(file_path="out.log", level=logging.INFO, log_format=log_formats.easy_read, handler=logging.FileHandler, **handler_kwargs): """ Set up a file handler to add to a logger. :param file_path: file to write the log to, defaults to out.log :param level: logging level to set handler at :param log_format: formatter to use :param handler: logging handler to use, defaults to FileHandler :param handler_kwargs: options to pass to the handler :return: handler """ fh = handler(file_path, **handler_kwargs) fh.setLevel(level) fh.setFormatter(logging.Formatter(log_format)) return fh
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Set up a file handler to add to a logger. :param file_path: file to write the log to, defaults to out.log :param level: logging level to set handler at :param log_format: formatter to use :param handler: logging handler to use, defaults to FileHandler :param handler_kwargs: options to pass to the handler :return: handler
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/log.py#L62-L79
cdgriffith/Reusables
reusables/log.py
setup_logger
def setup_logger(module_name=None, level=logging.INFO, stream=sys.stderr, file_path=None, log_format=log_formats.easy_read, suppress_warning=True): """ Grabs the specified logger and adds wanted handlers to it. Will default to adding a stream handler. :param module_name: logger name to use :param level: logging level to set logger at :param stream: stream to log to, or None :param file_path: file path to log to, or None :param log_format: format to set the handlers to use :param suppress_warning: add a NullHandler if no other handler is specified :return: configured logger """ new_logger = logging.getLogger(module_name) if stream: new_logger.addHandler(get_stream_handler(stream, level, log_format)) elif not file_path and suppress_warning and not new_logger.handlers: new_logger.addHandler(logging.NullHandler()) if file_path: new_logger.addHandler(get_file_handler(file_path, level, log_format)) if level > 0: new_logger.setLevel(level) return new_logger
python
def setup_logger(module_name=None, level=logging.INFO, stream=sys.stderr, file_path=None, log_format=log_formats.easy_read, suppress_warning=True): """ Grabs the specified logger and adds wanted handlers to it. Will default to adding a stream handler. :param module_name: logger name to use :param level: logging level to set logger at :param stream: stream to log to, or None :param file_path: file path to log to, or None :param log_format: format to set the handlers to use :param suppress_warning: add a NullHandler if no other handler is specified :return: configured logger """ new_logger = logging.getLogger(module_name) if stream: new_logger.addHandler(get_stream_handler(stream, level, log_format)) elif not file_path and suppress_warning and not new_logger.handlers: new_logger.addHandler(logging.NullHandler()) if file_path: new_logger.addHandler(get_file_handler(file_path, level, log_format)) if level > 0: new_logger.setLevel(level) return new_logger
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/log.py#L82-L108
cdgriffith/Reusables
reusables/log.py
add_stream_handler
def add_stream_handler(logger=None, stream=sys.stderr, level=logging.INFO, log_format=log_formats.easy_read): """ Addes a newly created stream handler to the specified logger :param logger: logging name or object to modify, defaults to root logger :param stream: which stream to use, defaults to sys.stderr :param level: logging level to set handler at :param log_format: formatter to use """ if not isinstance(logger, logging.Logger): logger = logging.getLogger(logger) logger.addHandler(get_stream_handler(stream, level, log_format))
python
def add_stream_handler(logger=None, stream=sys.stderr, level=logging.INFO, log_format=log_formats.easy_read): """ Addes a newly created stream handler to the specified logger :param logger: logging name or object to modify, defaults to root logger :param stream: which stream to use, defaults to sys.stderr :param level: logging level to set handler at :param log_format: formatter to use """ if not isinstance(logger, logging.Logger): logger = logging.getLogger(logger) logger.addHandler(get_stream_handler(stream, level, log_format))
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Addes a newly created stream handler to the specified logger :param logger: logging name or object to modify, defaults to root logger :param stream: which stream to use, defaults to sys.stderr :param level: logging level to set handler at :param log_format: formatter to use
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/log.py#L118-L131
cdgriffith/Reusables
reusables/log.py
add_file_handler
def add_file_handler(logger=None, file_path="out.log", level=logging.INFO, log_format=log_formats.easy_read): """ Addes a newly created file handler to the specified logger :param logger: logging name or object to modify, defaults to root logger :param file_path: path to file to log to :param level: logging level to set handler at :param log_format: formatter to use """ if not isinstance(logger, logging.Logger): logger = logging.getLogger(logger) logger.addHandler(get_file_handler(file_path, level, log_format))
python
def add_file_handler(logger=None, file_path="out.log", level=logging.INFO, log_format=log_formats.easy_read): """ Addes a newly created file handler to the specified logger :param logger: logging name or object to modify, defaults to root logger :param file_path: path to file to log to :param level: logging level to set handler at :param log_format: formatter to use """ if not isinstance(logger, logging.Logger): logger = logging.getLogger(logger) logger.addHandler(get_file_handler(file_path, level, log_format))
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Addes a newly created file handler to the specified logger :param logger: logging name or object to modify, defaults to root logger :param file_path: path to file to log to :param level: logging level to set handler at :param log_format: formatter to use
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/log.py#L134-L147
cdgriffith/Reusables
reusables/log.py
add_rotating_file_handler
def add_rotating_file_handler(logger=None, file_path="out.log", level=logging.INFO, log_format=log_formats.easy_read, max_bytes=10*sizes.mb, backup_count=5, **handler_kwargs): """ Adds a rotating file handler to the specified logger. :param logger: logging name or object to modify, defaults to root logger :param file_path: path to file to log to :param level: logging level to set handler at :param log_format: log formatter :param max_bytes: Max file size in bytes before rotating :param backup_count: Number of backup files :param handler_kwargs: options to pass to the handler """ if not isinstance(logger, logging.Logger): logger = logging.getLogger(logger) logger.addHandler(get_file_handler(file_path, level, log_format, handler=RotatingFileHandler, maxBytes=max_bytes, backupCount=backup_count, **handler_kwargs))
python
def add_rotating_file_handler(logger=None, file_path="out.log", level=logging.INFO, log_format=log_formats.easy_read, max_bytes=10*sizes.mb, backup_count=5, **handler_kwargs): """ Adds a rotating file handler to the specified logger. :param logger: logging name or object to modify, defaults to root logger :param file_path: path to file to log to :param level: logging level to set handler at :param log_format: log formatter :param max_bytes: Max file size in bytes before rotating :param backup_count: Number of backup files :param handler_kwargs: options to pass to the handler """ if not isinstance(logger, logging.Logger): logger = logging.getLogger(logger) logger.addHandler(get_file_handler(file_path, level, log_format, handler=RotatingFileHandler, maxBytes=max_bytes, backupCount=backup_count, **handler_kwargs))
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Adds a rotating file handler to the specified logger. :param logger: logging name or object to modify, defaults to root logger :param file_path: path to file to log to :param level: logging level to set handler at :param log_format: log formatter :param max_bytes: Max file size in bytes before rotating :param backup_count: Number of backup files :param handler_kwargs: options to pass to the handler
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/log.py#L150-L172
cdgriffith/Reusables
reusables/log.py
add_timed_rotating_file_handler
def add_timed_rotating_file_handler(logger=None, file_path="out.log", level=logging.INFO, log_format=log_formats.easy_read, when='w0', interval=1, backup_count=5, **handler_kwargs): """ Adds a timed rotating file handler to the specified logger. Defaults to weekly rotation, with 5 backups. :param logger: logging name or object to modify, defaults to root logger :param file_path: path to file to log to :param level: logging level to set handler at :param log_format: log formatter :param when: :param interval: :param backup_count: Number of backup files :param handler_kwargs: options to pass to the handler """ if not isinstance(logger, logging.Logger): logger = logging.getLogger(logger) logger.addHandler(get_file_handler(file_path, level, log_format, handler=TimedRotatingFileHandler, when=when, interval=interval, backupCount=backup_count, **handler_kwargs))
python
def add_timed_rotating_file_handler(logger=None, file_path="out.log", level=logging.INFO, log_format=log_formats.easy_read, when='w0', interval=1, backup_count=5, **handler_kwargs): """ Adds a timed rotating file handler to the specified logger. Defaults to weekly rotation, with 5 backups. :param logger: logging name or object to modify, defaults to root logger :param file_path: path to file to log to :param level: logging level to set handler at :param log_format: log formatter :param when: :param interval: :param backup_count: Number of backup files :param handler_kwargs: options to pass to the handler """ if not isinstance(logger, logging.Logger): logger = logging.getLogger(logger) logger.addHandler(get_file_handler(file_path, level, log_format, handler=TimedRotatingFileHandler, when=when, interval=interval, backupCount=backup_count, **handler_kwargs))
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Adds a timed rotating file handler to the specified logger. Defaults to weekly rotation, with 5 backups. :param logger: logging name or object to modify, defaults to root logger :param file_path: path to file to log to :param level: logging level to set handler at :param log_format: log formatter :param when: :param interval: :param backup_count: Number of backup files :param handler_kwargs: options to pass to the handler
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/log.py#L175-L200
cdgriffith/Reusables
reusables/log.py
remove_stream_handlers
def remove_stream_handlers(logger=None): """ Remove only stream handlers from the specified logger :param logger: logging name or object to modify, defaults to root logger """ if not isinstance(logger, logging.Logger): logger = logging.getLogger(logger) new_handlers = [] for handler in logger.handlers: # FileHandler is a subclass of StreamHandler so # 'if not a StreamHandler' does not work if (isinstance(handler, logging.FileHandler) or isinstance(handler, logging.NullHandler) or (isinstance(handler, logging.Handler) and not isinstance(handler, logging.StreamHandler))): new_handlers.append(handler) logger.handlers = new_handlers
python
def remove_stream_handlers(logger=None): """ Remove only stream handlers from the specified logger :param logger: logging name or object to modify, defaults to root logger """ if not isinstance(logger, logging.Logger): logger = logging.getLogger(logger) new_handlers = [] for handler in logger.handlers: # FileHandler is a subclass of StreamHandler so # 'if not a StreamHandler' does not work if (isinstance(handler, logging.FileHandler) or isinstance(handler, logging.NullHandler) or (isinstance(handler, logging.Handler) and not isinstance(handler, logging.StreamHandler))): new_handlers.append(handler) logger.handlers = new_handlers
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Remove only stream handlers from the specified logger :param logger: logging name or object to modify, defaults to root logger
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/log.py#L203-L221
cdgriffith/Reusables
reusables/log.py
remove_file_handlers
def remove_file_handlers(logger=None): """ Remove only file handlers from the specified logger. Will go through and close each handler for safety. :param logger: logging name or object to modify, defaults to root logger """ if not isinstance(logger, logging.Logger): logger = logging.getLogger(logger) new_handlers = [] for handler in logger.handlers: if isinstance(handler, logging.FileHandler): handler.close() else: new_handlers.append(handler) logger.handlers = new_handlers
python
def remove_file_handlers(logger=None): """ Remove only file handlers from the specified logger. Will go through and close each handler for safety. :param logger: logging name or object to modify, defaults to root logger """ if not isinstance(logger, logging.Logger): logger = logging.getLogger(logger) new_handlers = [] for handler in logger.handlers: if isinstance(handler, logging.FileHandler): handler.close() else: new_handlers.append(handler) logger.handlers = new_handlers
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Remove only file handlers from the specified logger. Will go through and close each handler for safety. :param logger: logging name or object to modify, defaults to root logger
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/log.py#L224-L240
cdgriffith/Reusables
reusables/log.py
remove_all_handlers
def remove_all_handlers(logger=None): """ Safely remove all handlers from the logger :param logger: logging name or object to modify, defaults to root logger """ if not isinstance(logger, logging.Logger): logger = logging.getLogger(logger) remove_file_handlers(logger) logger.handlers = []
python
def remove_all_handlers(logger=None): """ Safely remove all handlers from the logger :param logger: logging name or object to modify, defaults to root logger """ if not isinstance(logger, logging.Logger): logger = logging.getLogger(logger) remove_file_handlers(logger) logger.handlers = []
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Safely remove all handlers from the logger :param logger: logging name or object to modify, defaults to root logger
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/log.py#L243-L253
cdgriffith/Reusables
reusables/log.py
change_logger_levels
def change_logger_levels(logger=None, level=logging.DEBUG): """ Go through the logger and handlers and update their levels to the one specified. :param logger: logging name or object to modify, defaults to root logger :param level: logging level to set at (10=Debug, 20=Info, 30=Warn, 40=Error) """ if not isinstance(logger, logging.Logger): logger = logging.getLogger(logger) logger.setLevel(level) for handler in logger.handlers: handler.level = level
python
def change_logger_levels(logger=None, level=logging.DEBUG): """ Go through the logger and handlers and update their levels to the one specified. :param logger: logging name or object to modify, defaults to root logger :param level: logging level to set at (10=Debug, 20=Info, 30=Warn, 40=Error) """ if not isinstance(logger, logging.Logger): logger = logging.getLogger(logger) logger.setLevel(level) for handler in logger.handlers: handler.level = level
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Go through the logger and handlers and update their levels to the one specified. :param logger: logging name or object to modify, defaults to root logger :param level: logging level to set at (10=Debug, 20=Info, 30=Warn, 40=Error)
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/log.py#L256-L269
cdgriffith/Reusables
reusables/log.py
get_registered_loggers
def get_registered_loggers(hide_children=False, hide_reusables=False): """ Find the names of all loggers currently registered :param hide_children: only return top level logger names :param hide_reusables: hide the reusables loggers :return: list of logger names """ return [logger for logger in logging.Logger.manager.loggerDict.keys() if not (hide_reusables and "reusables" in logger) and not (hide_children and "." in logger)]
python
def get_registered_loggers(hide_children=False, hide_reusables=False): """ Find the names of all loggers currently registered :param hide_children: only return top level logger names :param hide_reusables: hide the reusables loggers :return: list of logger names """ return [logger for logger in logging.Logger.manager.loggerDict.keys() if not (hide_reusables and "reusables" in logger) and not (hide_children and "." in logger)]
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Find the names of all loggers currently registered :param hide_children: only return top level logger names :param hide_reusables: hide the reusables loggers :return: list of logger names
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/log.py#L272-L283
cdgriffith/Reusables
reusables/wrappers.py
unique
def unique(max_retries=10, wait=0, alt_return="-no_alt_return-", exception=Exception, error_text=None): """ Wrapper. Makes sure the function's return value has not been returned before or else it run with the same inputs again. .. code: python import reusables import random @reusables.unique(max_retries=100) def poor_uuid(): return random.randint(0, 10) print([poor_uuid() for _ in range(10)]) # [8, 9, 6, 3, 0, 7, 2, 5, 4, 10] print([poor_uuid() for _ in range(100)]) # Exception: No result was unique Message format options: {func} {args} {kwargs} :param max_retries: int of number of retries to attempt before failing :param wait: float of seconds to wait between each try, defaults to 0 :param exception: Exception type of raise :param error_text: text of the exception :param alt_return: if specified, an exception is not raised on failure, instead the provided value of any type of will be returned """ def func_wrap(func): @wraps(func) def wrapper(*args, **kwargs): msg = (error_text if error_text else "No result was unique for function '{func}'") if not error_text: msg = _add_args(msg, *args, **kwargs) for i in range(max_retries): value = func(*args, **kwargs) if value not in unique_cache[func.__name__]: unique_cache[func.__name__].append(value) return value if wait: time.sleep(wait) else: if alt_return != "-no_alt_return-": return alt_return raise exception(msg.format(func=func.__name__, args=args, kwargs=kwargs)) return wrapper return func_wrap
python
def unique(max_retries=10, wait=0, alt_return="-no_alt_return-", exception=Exception, error_text=None): """ Wrapper. Makes sure the function's return value has not been returned before or else it run with the same inputs again. .. code: python import reusables import random @reusables.unique(max_retries=100) def poor_uuid(): return random.randint(0, 10) print([poor_uuid() for _ in range(10)]) # [8, 9, 6, 3, 0, 7, 2, 5, 4, 10] print([poor_uuid() for _ in range(100)]) # Exception: No result was unique Message format options: {func} {args} {kwargs} :param max_retries: int of number of retries to attempt before failing :param wait: float of seconds to wait between each try, defaults to 0 :param exception: Exception type of raise :param error_text: text of the exception :param alt_return: if specified, an exception is not raised on failure, instead the provided value of any type of will be returned """ def func_wrap(func): @wraps(func) def wrapper(*args, **kwargs): msg = (error_text if error_text else "No result was unique for function '{func}'") if not error_text: msg = _add_args(msg, *args, **kwargs) for i in range(max_retries): value = func(*args, **kwargs) if value not in unique_cache[func.__name__]: unique_cache[func.__name__].append(value) return value if wait: time.sleep(wait) else: if alt_return != "-no_alt_return-": return alt_return raise exception(msg.format(func=func.__name__, args=args, kwargs=kwargs)) return wrapper return func_wrap
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Wrapper. Makes sure the function's return value has not been returned before or else it run with the same inputs again. .. code: python import reusables import random @reusables.unique(max_retries=100) def poor_uuid(): return random.randint(0, 10) print([poor_uuid() for _ in range(10)]) # [8, 9, 6, 3, 0, 7, 2, 5, 4, 10] print([poor_uuid() for _ in range(100)]) # Exception: No result was unique Message format options: {func} {args} {kwargs} :param max_retries: int of number of retries to attempt before failing :param wait: float of seconds to wait between each try, defaults to 0 :param exception: Exception type of raise :param error_text: text of the exception :param alt_return: if specified, an exception is not raised on failure, instead the provided value of any type of will be returned
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/wrappers.py#L37-L87
cdgriffith/Reusables
reusables/wrappers.py
lock_it
def lock_it(lock=g_lock): """ Wrapper. Simple wrapper to make sure a function is only run once at a time. .. code: python import reusables import time def func_one(_): time.sleep(5) @reusables.lock_it() def func_two(_): time.sleep(5) @reusables.time_it(message="test_1 took {0:.2f} seconds") def test_1(): reusables.run_in_pool(func_one, (1, 2, 3), threaded=True) @reusables.time_it(message="test_2 took {0:.2f} seconds") def test_2(): reusables.run_in_pool(func_two, (1, 2, 3), threaded=True) test_1() test_2() # test_1 took 5.04 seconds # test_2 took 15.07 seconds :param lock: Which lock to use, uses unique default """ def func_wrapper(func): @wraps(func) def wrapper(*args, **kwargs): with lock: return func(*args, **kwargs) return wrapper return func_wrapper
python
def lock_it(lock=g_lock): """ Wrapper. Simple wrapper to make sure a function is only run once at a time. .. code: python import reusables import time def func_one(_): time.sleep(5) @reusables.lock_it() def func_two(_): time.sleep(5) @reusables.time_it(message="test_1 took {0:.2f} seconds") def test_1(): reusables.run_in_pool(func_one, (1, 2, 3), threaded=True) @reusables.time_it(message="test_2 took {0:.2f} seconds") def test_2(): reusables.run_in_pool(func_two, (1, 2, 3), threaded=True) test_1() test_2() # test_1 took 5.04 seconds # test_2 took 15.07 seconds :param lock: Which lock to use, uses unique default """ def func_wrapper(func): @wraps(func) def wrapper(*args, **kwargs): with lock: return func(*args, **kwargs) return wrapper return func_wrapper
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Wrapper. Simple wrapper to make sure a function is only run once at a time. .. code: python import reusables import time def func_one(_): time.sleep(5) @reusables.lock_it() def func_two(_): time.sleep(5) @reusables.time_it(message="test_1 took {0:.2f} seconds") def test_1(): reusables.run_in_pool(func_one, (1, 2, 3), threaded=True) @reusables.time_it(message="test_2 took {0:.2f} seconds") def test_2(): reusables.run_in_pool(func_two, (1, 2, 3), threaded=True) test_1() test_2() # test_1 took 5.04 seconds # test_2 took 15.07 seconds :param lock: Which lock to use, uses unique default
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/wrappers.py#L90-L129
cdgriffith/Reusables
reusables/wrappers.py
time_it
def time_it(log=None, message=None, append=None): """ Wrapper. Time the amount of time it takes the execution of the function and print it. If log is true, make sure to set the logging level of 'reusables' to INFO level or lower. .. code:: python import time import reusables reusables.add_stream_handler('reusables') @reusables.time_it(log=True, message="{seconds:.2f} seconds") def test_time(length): time.sleep(length) return "slept {0}".format(length) result = test_time(5) # 2016-11-09 16:59:39,935 - reusables.wrappers INFO 5.01 seconds print(result) # slept 5 Message format options: {func} {seconds} {args} {kwargs} :param log: log as INFO level instead of printing :param message: string to format with total time as the only input :param append: list to append item too """ def func_wrapper(func): @wraps(func) def wrapper(*args, **kwargs): # Can't use nonlocal in 2.x msg = (message if message else "Function '{func}' took a total of {seconds} seconds") if not message: msg = _add_args(msg, *args, **kwargs) time_func = (time.perf_counter if python_version >= (3, 3) else time.time) start_time = time_func() try: return func(*args, **kwargs) finally: total_time = time_func() - start_time time_string = msg.format(func=func.__name__, seconds=total_time, args=args, kwargs=kwargs) if log: my_logger = logging.getLogger(log) if isinstance(log, str)\ else logger my_logger.info(time_string) else: print(time_string) if isinstance(append, list): append.append(total_time) return wrapper return func_wrapper
python
def time_it(log=None, message=None, append=None): """ Wrapper. Time the amount of time it takes the execution of the function and print it. If log is true, make sure to set the logging level of 'reusables' to INFO level or lower. .. code:: python import time import reusables reusables.add_stream_handler('reusables') @reusables.time_it(log=True, message="{seconds:.2f} seconds") def test_time(length): time.sleep(length) return "slept {0}".format(length) result = test_time(5) # 2016-11-09 16:59:39,935 - reusables.wrappers INFO 5.01 seconds print(result) # slept 5 Message format options: {func} {seconds} {args} {kwargs} :param log: log as INFO level instead of printing :param message: string to format with total time as the only input :param append: list to append item too """ def func_wrapper(func): @wraps(func) def wrapper(*args, **kwargs): # Can't use nonlocal in 2.x msg = (message if message else "Function '{func}' took a total of {seconds} seconds") if not message: msg = _add_args(msg, *args, **kwargs) time_func = (time.perf_counter if python_version >= (3, 3) else time.time) start_time = time_func() try: return func(*args, **kwargs) finally: total_time = time_func() - start_time time_string = msg.format(func=func.__name__, seconds=total_time, args=args, kwargs=kwargs) if log: my_logger = logging.getLogger(log) if isinstance(log, str)\ else logger my_logger.info(time_string) else: print(time_string) if isinstance(append, list): append.append(total_time) return wrapper return func_wrapper
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Wrapper. Time the amount of time it takes the execution of the function and print it. If log is true, make sure to set the logging level of 'reusables' to INFO level or lower. .. code:: python import time import reusables reusables.add_stream_handler('reusables') @reusables.time_it(log=True, message="{seconds:.2f} seconds") def test_time(length): time.sleep(length) return "slept {0}".format(length) result = test_time(5) # 2016-11-09 16:59:39,935 - reusables.wrappers INFO 5.01 seconds print(result) # slept 5 Message format options: {func} {seconds} {args} {kwargs} :param log: log as INFO level instead of printing :param message: string to format with total time as the only input :param append: list to append item too
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/wrappers.py#L132-L193
cdgriffith/Reusables
reusables/wrappers.py
queue_it
def queue_it(queue=g_queue, **put_args): """ Wrapper. Instead of returning the result of the function, add it to a queue. .. code: python import reusables import queue my_queue = queue.Queue() @reusables.queue_it(my_queue) def func(a): return a func(10) print(my_queue.get()) # 10 :param queue: Queue to add result into """ def func_wrapper(func): @wraps(func) def wrapper(*args, **kwargs): queue.put(func(*args, **kwargs), **put_args) return wrapper return func_wrapper
python
def queue_it(queue=g_queue, **put_args): """ Wrapper. Instead of returning the result of the function, add it to a queue. .. code: python import reusables import queue my_queue = queue.Queue() @reusables.queue_it(my_queue) def func(a): return a func(10) print(my_queue.get()) # 10 :param queue: Queue to add result into """ def func_wrapper(func): @wraps(func) def wrapper(*args, **kwargs): queue.put(func(*args, **kwargs), **put_args) return wrapper return func_wrapper
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Wrapper. Instead of returning the result of the function, add it to a queue. .. code: python import reusables import queue my_queue = queue.Queue() @reusables.queue_it(my_queue) def func(a): return a func(10) print(my_queue.get()) # 10 :param queue: Queue to add result into
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/wrappers.py#L196-L224
cdgriffith/Reusables
reusables/wrappers.py
log_exception
def log_exception(log="reusables", message=None, exceptions=(Exception, ), level=logging.ERROR, show_traceback=True): """ Wrapper. Log the traceback to any exceptions raised. Possible to raise custom exception. .. code :: python @reusables.log_exception() def test(): raise Exception("Bad") # 2016-12-26 12:38:01,381 - reusables ERROR Exception in test - Bad # Traceback (most recent call last): # File "<input>", line 1, in <module> # File "reusables\wrappers.py", line 200, in wrapper # raise err # Exception: Bad Message format options: {func} {err} {args} {kwargs} :param exceptions: types of exceptions to catch :param log: log name to use :param message: message to use in log :param level: logging level :param show_traceback: include full traceback or just error message """ def func_wrapper(func): @wraps(func) def wrapper(*args, **kwargs): msg = message if message else "Exception in '{func}': {err}" if not message: msg = _add_args(msg, *args, **kwargs) try: return func(*args, **kwargs) except exceptions as err: my_logger = (logging.getLogger(log) if isinstance(log, str) else log) my_logger.log(level, msg.format(func=func.__name__, err=str(err), args=args, kwargs=kwargs), exc_info=show_traceback) raise err return wrapper return func_wrapper
python
def log_exception(log="reusables", message=None, exceptions=(Exception, ), level=logging.ERROR, show_traceback=True): """ Wrapper. Log the traceback to any exceptions raised. Possible to raise custom exception. .. code :: python @reusables.log_exception() def test(): raise Exception("Bad") # 2016-12-26 12:38:01,381 - reusables ERROR Exception in test - Bad # Traceback (most recent call last): # File "<input>", line 1, in <module> # File "reusables\wrappers.py", line 200, in wrapper # raise err # Exception: Bad Message format options: {func} {err} {args} {kwargs} :param exceptions: types of exceptions to catch :param log: log name to use :param message: message to use in log :param level: logging level :param show_traceback: include full traceback or just error message """ def func_wrapper(func): @wraps(func) def wrapper(*args, **kwargs): msg = message if message else "Exception in '{func}': {err}" if not message: msg = _add_args(msg, *args, **kwargs) try: return func(*args, **kwargs) except exceptions as err: my_logger = (logging.getLogger(log) if isinstance(log, str) else log) my_logger.log(level, msg.format(func=func.__name__, err=str(err), args=args, kwargs=kwargs), exc_info=show_traceback) raise err return wrapper return func_wrapper
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Wrapper. Log the traceback to any exceptions raised. Possible to raise custom exception. .. code :: python @reusables.log_exception() def test(): raise Exception("Bad") # 2016-12-26 12:38:01,381 - reusables ERROR Exception in test - Bad # Traceback (most recent call last): # File "<input>", line 1, in <module> # File "reusables\wrappers.py", line 200, in wrapper # raise err # Exception: Bad Message format options: {func} {err} {args} {kwargs} :param exceptions: types of exceptions to catch :param log: log name to use :param message: message to use in log :param level: logging level :param show_traceback: include full traceback or just error message
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/wrappers.py#L227-L272
cdgriffith/Reusables
reusables/wrappers.py
catch_it
def catch_it(exceptions=(Exception, ), default=None, handler=None): """ If the function encounters an exception, catch it, and return the specified default or sent to a handler function instead. .. code :: python def handle_error(exception, func, *args, **kwargs): print(f"{func.__name__} raised {exception} when called with {args}") @reusables.catch_it(handler=err_func) def will_raise(message="Hello") raise Exception(message) :param exceptions: tuple of exceptions to catch :param default: what to return if the exception is caught :param handler: function to send exception, func, *args and **kwargs """ def func_wrapper(func): @wraps(func) def wrapper(*args, **kwargs): try: return func(*args, **kwargs) except exceptions as err: if handler: return handler(err, func, *args, **kwargs) return default return wrapper return func_wrapper
python
def catch_it(exceptions=(Exception, ), default=None, handler=None): """ If the function encounters an exception, catch it, and return the specified default or sent to a handler function instead. .. code :: python def handle_error(exception, func, *args, **kwargs): print(f"{func.__name__} raised {exception} when called with {args}") @reusables.catch_it(handler=err_func) def will_raise(message="Hello") raise Exception(message) :param exceptions: tuple of exceptions to catch :param default: what to return if the exception is caught :param handler: function to send exception, func, *args and **kwargs """ def func_wrapper(func): @wraps(func) def wrapper(*args, **kwargs): try: return func(*args, **kwargs) except exceptions as err: if handler: return handler(err, func, *args, **kwargs) return default return wrapper return func_wrapper
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If the function encounters an exception, catch it, and return the specified default or sent to a handler function instead. .. code :: python def handle_error(exception, func, *args, **kwargs): print(f"{func.__name__} raised {exception} when called with {args}") @reusables.catch_it(handler=err_func) def will_raise(message="Hello") raise Exception(message) :param exceptions: tuple of exceptions to catch :param default: what to return if the exception is caught :param handler: function to send exception, func, *args and **kwargs
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/wrappers.py#L275-L304
cdgriffith/Reusables
reusables/wrappers.py
retry_it
def retry_it(exceptions=(Exception, ), tries=10, wait=0, handler=None, raised_exception=ReusablesError, raised_message=None): """ Retry a function if an exception is raised, or if output_check returns False. Message format options: {func} {args} {kwargs} :param exceptions: tuple of exceptions to catch :param tries: number of tries to retry the function :param wait: time to wait between executions in seconds :param handler: function to check if output is valid, must return bool :param raised_exception: default is ReusablesError :param raised_message: message to pass to raised exception """ def func_wrapper(func): @wraps(func) def wrapper(*args, **kwargs): msg = (raised_message if raised_message else "Max retries exceeded for function '{func}'") if not raised_message: msg = _add_args(msg, *args, **kwargs) try: result = func(*args, **kwargs) except exceptions: if tries: if wait: time.sleep(wait) return retry_it(exceptions=exceptions, tries=tries-1, handler=handler, wait=wait)(func)(*args, **kwargs) if raised_exception: exc = raised_exception(msg.format(func=func.__name__, args=args, kwargs=kwargs)) exc.__cause__ = None raise exc else: if handler: if not handler(result): return retry_it(exceptions=exceptions, tries=tries - 1, handler=handler, wait=wait)(func)(*args, **kwargs) return result return wrapper return func_wrapper
python
def retry_it(exceptions=(Exception, ), tries=10, wait=0, handler=None, raised_exception=ReusablesError, raised_message=None): """ Retry a function if an exception is raised, or if output_check returns False. Message format options: {func} {args} {kwargs} :param exceptions: tuple of exceptions to catch :param tries: number of tries to retry the function :param wait: time to wait between executions in seconds :param handler: function to check if output is valid, must return bool :param raised_exception: default is ReusablesError :param raised_message: message to pass to raised exception """ def func_wrapper(func): @wraps(func) def wrapper(*args, **kwargs): msg = (raised_message if raised_message else "Max retries exceeded for function '{func}'") if not raised_message: msg = _add_args(msg, *args, **kwargs) try: result = func(*args, **kwargs) except exceptions: if tries: if wait: time.sleep(wait) return retry_it(exceptions=exceptions, tries=tries-1, handler=handler, wait=wait)(func)(*args, **kwargs) if raised_exception: exc = raised_exception(msg.format(func=func.__name__, args=args, kwargs=kwargs)) exc.__cause__ = None raise exc else: if handler: if not handler(result): return retry_it(exceptions=exceptions, tries=tries - 1, handler=handler, wait=wait)(func)(*args, **kwargs) return result return wrapper return func_wrapper
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Retry a function if an exception is raised, or if output_check returns False. Message format options: {func} {args} {kwargs} :param exceptions: tuple of exceptions to catch :param tries: number of tries to retry the function :param wait: time to wait between executions in seconds :param handler: function to check if output is valid, must return bool :param raised_exception: default is ReusablesError :param raised_message: message to pass to raised exception
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/wrappers.py#L307-L351
cdgriffith/Reusables
reusables/file_operations.py
extract
def extract(archive_file, path=".", delete_on_success=False, enable_rar=False): """ Automatically detect archive type and extract all files to specified path. .. code:: python import os os.listdir(".") # ['test_structure.zip'] reusables.extract("test_structure.zip") os.listdir(".") # [ 'test_structure', 'test_structure.zip'] :param archive_file: path to file to extract :param path: location to extract to :param delete_on_success: Will delete the original archive if set to True :param enable_rar: include the rarfile import and extract :return: path to extracted files """ if not os.path.exists(archive_file) or not os.path.getsize(archive_file): logger.error("File {0} unextractable".format(archive_file)) raise OSError("File does not exist or has zero size") arch = None if zipfile.is_zipfile(archive_file): logger.debug("File {0} detected as a zip file".format(archive_file)) arch = zipfile.ZipFile(archive_file) elif tarfile.is_tarfile(archive_file): logger.debug("File {0} detected as a tar file".format(archive_file)) arch = tarfile.open(archive_file) elif enable_rar: import rarfile if rarfile.is_rarfile(archive_file): logger.debug("File {0} detected as " "a rar file".format(archive_file)) arch = rarfile.RarFile(archive_file) if not arch: raise TypeError("File is not a known archive") logger.debug("Extracting files to {0}".format(path)) try: arch.extractall(path=path) finally: arch.close() if delete_on_success: logger.debug("Archive {0} will now be deleted".format(archive_file)) os.unlink(archive_file) return os.path.abspath(path)
python
def extract(archive_file, path=".", delete_on_success=False, enable_rar=False): """ Automatically detect archive type and extract all files to specified path. .. code:: python import os os.listdir(".") # ['test_structure.zip'] reusables.extract("test_structure.zip") os.listdir(".") # [ 'test_structure', 'test_structure.zip'] :param archive_file: path to file to extract :param path: location to extract to :param delete_on_success: Will delete the original archive if set to True :param enable_rar: include the rarfile import and extract :return: path to extracted files """ if not os.path.exists(archive_file) or not os.path.getsize(archive_file): logger.error("File {0} unextractable".format(archive_file)) raise OSError("File does not exist or has zero size") arch = None if zipfile.is_zipfile(archive_file): logger.debug("File {0} detected as a zip file".format(archive_file)) arch = zipfile.ZipFile(archive_file) elif tarfile.is_tarfile(archive_file): logger.debug("File {0} detected as a tar file".format(archive_file)) arch = tarfile.open(archive_file) elif enable_rar: import rarfile if rarfile.is_rarfile(archive_file): logger.debug("File {0} detected as " "a rar file".format(archive_file)) arch = rarfile.RarFile(archive_file) if not arch: raise TypeError("File is not a known archive") logger.debug("Extracting files to {0}".format(path)) try: arch.extractall(path=path) finally: arch.close() if delete_on_success: logger.debug("Archive {0} will now be deleted".format(archive_file)) os.unlink(archive_file) return os.path.abspath(path)
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Automatically detect archive type and extract all files to specified path. .. code:: python import os os.listdir(".") # ['test_structure.zip'] reusables.extract("test_structure.zip") os.listdir(".") # [ 'test_structure', 'test_structure.zip'] :param archive_file: path to file to extract :param path: location to extract to :param delete_on_success: Will delete the original archive if set to True :param enable_rar: include the rarfile import and extract :return: path to extracted files
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L35-L92
cdgriffith/Reusables
reusables/file_operations.py
archive
def archive(files_to_archive, name="archive.zip", archive_type=None, overwrite=False, store=False, depth=None, err_non_exist=True, allow_zip_64=True, **tarfile_kwargs): """ Archive a list of files (or files inside a folder), can chose between - zip - tar - gz (tar.gz, tgz) - bz2 (tar.bz2) .. code:: python reusables.archive(['reusables', '.travis.yml'], name="my_archive.bz2") # 'C:\\Users\\Me\\Reusables\\my_archive.bz2' :param files_to_archive: list of files and folders to archive :param name: path and name of archive file :param archive_type: auto-detects unless specified :param overwrite: overwrite if archive exists :param store: zipfile only, True will not compress files :param depth: specify max depth for folders :param err_non_exist: raise error if provided file does not exist :param allow_zip_64: must be enabled for zip files larger than 2GB :param tarfile_kwargs: extra args to pass to tarfile.open :return: path to created archive """ if not isinstance(files_to_archive, (list, tuple)): files_to_archive = [files_to_archive] if not archive_type: if name.lower().endswith("zip"): archive_type = "zip" elif name.lower().endswith("gz"): archive_type = "gz" elif name.lower().endswith("z2"): archive_type = "bz2" elif name.lower().endswith("tar"): archive_type = "tar" else: err_msg = ("Could not determine archive " "type based off {0}".format(name)) logger.error(err_msg) raise ValueError(err_msg) logger.debug("{0} file detected for {1}".format(archive_type, name)) elif archive_type not in ("tar", "gz", "bz2", "zip"): err_msg = ("archive_type must be zip, gz, bz2," " or gz, was {0}".format(archive_type)) logger.error(err_msg) raise ValueError(err_msg) if not overwrite and os.path.exists(name): err_msg = "File {0} exists and overwrite not specified".format(name) logger.error(err_msg) raise OSError(err_msg) if archive_type == "zip": arch = zipfile.ZipFile(name, 'w', zipfile.ZIP_STORED if store else zipfile.ZIP_DEFLATED, allowZip64=allow_zip_64) write = arch.write elif archive_type in ("tar", "gz", "bz2"): mode = archive_type if archive_type != "tar" else "" arch = tarfile.open(name, 'w:{0}'.format(mode), **tarfile_kwargs) write = arch.add else: raise ValueError("archive_type must be zip, gz, bz2, or gz") try: for file_path in files_to_archive: if os.path.isfile(file_path): if err_non_exist and not os.path.exists(file_path): raise OSError("File {0} does not exist".format(file_path)) write(file_path) elif os.path.isdir(file_path): for nf in find_files(file_path, abspath=False, depth=depth): write(nf) except (Exception, KeyboardInterrupt) as err: logger.exception("Could not archive {0}".format(files_to_archive)) try: arch.close() finally: os.unlink(name) raise err else: arch.close() return os.path.abspath(name)
python
def archive(files_to_archive, name="archive.zip", archive_type=None, overwrite=False, store=False, depth=None, err_non_exist=True, allow_zip_64=True, **tarfile_kwargs): """ Archive a list of files (or files inside a folder), can chose between - zip - tar - gz (tar.gz, tgz) - bz2 (tar.bz2) .. code:: python reusables.archive(['reusables', '.travis.yml'], name="my_archive.bz2") # 'C:\\Users\\Me\\Reusables\\my_archive.bz2' :param files_to_archive: list of files and folders to archive :param name: path and name of archive file :param archive_type: auto-detects unless specified :param overwrite: overwrite if archive exists :param store: zipfile only, True will not compress files :param depth: specify max depth for folders :param err_non_exist: raise error if provided file does not exist :param allow_zip_64: must be enabled for zip files larger than 2GB :param tarfile_kwargs: extra args to pass to tarfile.open :return: path to created archive """ if not isinstance(files_to_archive, (list, tuple)): files_to_archive = [files_to_archive] if not archive_type: if name.lower().endswith("zip"): archive_type = "zip" elif name.lower().endswith("gz"): archive_type = "gz" elif name.lower().endswith("z2"): archive_type = "bz2" elif name.lower().endswith("tar"): archive_type = "tar" else: err_msg = ("Could not determine archive " "type based off {0}".format(name)) logger.error(err_msg) raise ValueError(err_msg) logger.debug("{0} file detected for {1}".format(archive_type, name)) elif archive_type not in ("tar", "gz", "bz2", "zip"): err_msg = ("archive_type must be zip, gz, bz2," " or gz, was {0}".format(archive_type)) logger.error(err_msg) raise ValueError(err_msg) if not overwrite and os.path.exists(name): err_msg = "File {0} exists and overwrite not specified".format(name) logger.error(err_msg) raise OSError(err_msg) if archive_type == "zip": arch = zipfile.ZipFile(name, 'w', zipfile.ZIP_STORED if store else zipfile.ZIP_DEFLATED, allowZip64=allow_zip_64) write = arch.write elif archive_type in ("tar", "gz", "bz2"): mode = archive_type if archive_type != "tar" else "" arch = tarfile.open(name, 'w:{0}'.format(mode), **tarfile_kwargs) write = arch.add else: raise ValueError("archive_type must be zip, gz, bz2, or gz") try: for file_path in files_to_archive: if os.path.isfile(file_path): if err_non_exist and not os.path.exists(file_path): raise OSError("File {0} does not exist".format(file_path)) write(file_path) elif os.path.isdir(file_path): for nf in find_files(file_path, abspath=False, depth=depth): write(nf) except (Exception, KeyboardInterrupt) as err: logger.exception("Could not archive {0}".format(files_to_archive)) try: arch.close() finally: os.unlink(name) raise err else: arch.close() return os.path.abspath(name)
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Archive a list of files (or files inside a folder), can chose between - zip - tar - gz (tar.gz, tgz) - bz2 (tar.bz2) .. code:: python reusables.archive(['reusables', '.travis.yml'], name="my_archive.bz2") # 'C:\\Users\\Me\\Reusables\\my_archive.bz2' :param files_to_archive: list of files and folders to archive :param name: path and name of archive file :param archive_type: auto-detects unless specified :param overwrite: overwrite if archive exists :param store: zipfile only, True will not compress files :param depth: specify max depth for folders :param err_non_exist: raise error if provided file does not exist :param allow_zip_64: must be enabled for zip files larger than 2GB :param tarfile_kwargs: extra args to pass to tarfile.open :return: path to created archive
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L95-L183
cdgriffith/Reusables
reusables/file_operations.py
list_to_csv
def list_to_csv(my_list, csv_file): """ Save a matrix (list of lists) to a file as a CSV .. code:: python my_list = [["Name", "Location"], ["Chris", "South Pole"], ["Harry", "Depth of Winter"], ["Bob", "Skull"]] reusables.list_to_csv(my_list, "example.csv") example.csv .. code:: csv "Name","Location" "Chris","South Pole" "Harry","Depth of Winter" "Bob","Skull" :param my_list: list of lists to save to CSV :param csv_file: File to save data to """ if PY3: csv_handler = open(csv_file, 'w', newline='') else: csv_handler = open(csv_file, 'wb') try: writer = csv.writer(csv_handler, delimiter=',', quoting=csv.QUOTE_ALL) writer.writerows(my_list) finally: csv_handler.close()
python
def list_to_csv(my_list, csv_file): """ Save a matrix (list of lists) to a file as a CSV .. code:: python my_list = [["Name", "Location"], ["Chris", "South Pole"], ["Harry", "Depth of Winter"], ["Bob", "Skull"]] reusables.list_to_csv(my_list, "example.csv") example.csv .. code:: csv "Name","Location" "Chris","South Pole" "Harry","Depth of Winter" "Bob","Skull" :param my_list: list of lists to save to CSV :param csv_file: File to save data to """ if PY3: csv_handler = open(csv_file, 'w', newline='') else: csv_handler = open(csv_file, 'wb') try: writer = csv.writer(csv_handler, delimiter=',', quoting=csv.QUOTE_ALL) writer.writerows(my_list) finally: csv_handler.close()
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Save a matrix (list of lists) to a file as a CSV .. code:: python my_list = [["Name", "Location"], ["Chris", "South Pole"], ["Harry", "Depth of Winter"], ["Bob", "Skull"]] reusables.list_to_csv(my_list, "example.csv") example.csv .. code:: csv "Name","Location" "Chris","South Pole" "Harry","Depth of Winter" "Bob","Skull" :param my_list: list of lists to save to CSV :param csv_file: File to save data to
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L186-L220
cdgriffith/Reusables
reusables/file_operations.py
csv_to_list
def csv_to_list(csv_file): """ Open and transform a CSV file into a matrix (list of lists). .. code:: python reusables.csv_to_list("example.csv") # [['Name', 'Location'], # ['Chris', 'South Pole'], # ['Harry', 'Depth of Winter'], # ['Bob', 'Skull']] :param csv_file: Path to CSV file as str :return: list """ with open(csv_file, 'r' if PY3 else 'rb') as f: return list(csv.reader(f))
python
def csv_to_list(csv_file): """ Open and transform a CSV file into a matrix (list of lists). .. code:: python reusables.csv_to_list("example.csv") # [['Name', 'Location'], # ['Chris', 'South Pole'], # ['Harry', 'Depth of Winter'], # ['Bob', 'Skull']] :param csv_file: Path to CSV file as str :return: list """ with open(csv_file, 'r' if PY3 else 'rb') as f: return list(csv.reader(f))
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Open and transform a CSV file into a matrix (list of lists). .. code:: python reusables.csv_to_list("example.csv") # [['Name', 'Location'], # ['Chris', 'South Pole'], # ['Harry', 'Depth of Winter'], # ['Bob', 'Skull']] :param csv_file: Path to CSV file as str :return: list
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L223-L239
cdgriffith/Reusables
reusables/file_operations.py
load_json
def load_json(json_file, **kwargs): """ Open and load data from a JSON file .. code:: python reusables.load_json("example.json") # {u'key_1': u'val_1', u'key_for_dict': {u'sub_dict_key': 8}} :param json_file: Path to JSON file as string :param kwargs: Additional arguments for the json.load command :return: Dictionary """ with open(json_file) as f: return json.load(f, **kwargs)
python
def load_json(json_file, **kwargs): """ Open and load data from a JSON file .. code:: python reusables.load_json("example.json") # {u'key_1': u'val_1', u'key_for_dict': {u'sub_dict_key': 8}} :param json_file: Path to JSON file as string :param kwargs: Additional arguments for the json.load command :return: Dictionary """ with open(json_file) as f: return json.load(f, **kwargs)
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Open and load data from a JSON file .. code:: python reusables.load_json("example.json") # {u'key_1': u'val_1', u'key_for_dict': {u'sub_dict_key': 8}} :param json_file: Path to JSON file as string :param kwargs: Additional arguments for the json.load command :return: Dictionary
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L242-L256
cdgriffith/Reusables
reusables/file_operations.py
save_json
def save_json(data, json_file, indent=4, **kwargs): """ Takes a dictionary and saves it to a file as JSON .. code:: python my_dict = {"key_1": "val_1", "key_for_dict": {"sub_dict_key": 8}} reusables.save_json(my_dict,"example.json") example.json .. code:: { "key_1": "val_1", "key_for_dict": { "sub_dict_key": 8 } } :param data: dictionary to save as JSON :param json_file: Path to save file location as str :param indent: Format the JSON file with so many numbers of spaces :param kwargs: Additional arguments for the json.dump command """ with open(json_file, "w") as f: json.dump(data, f, indent=indent, **kwargs)
python
def save_json(data, json_file, indent=4, **kwargs): """ Takes a dictionary and saves it to a file as JSON .. code:: python my_dict = {"key_1": "val_1", "key_for_dict": {"sub_dict_key": 8}} reusables.save_json(my_dict,"example.json") example.json .. code:: { "key_1": "val_1", "key_for_dict": { "sub_dict_key": 8 } } :param data: dictionary to save as JSON :param json_file: Path to save file location as str :param indent: Format the JSON file with so many numbers of spaces :param kwargs: Additional arguments for the json.dump command """ with open(json_file, "w") as f: json.dump(data, f, indent=indent, **kwargs)
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Takes a dictionary and saves it to a file as JSON .. code:: python my_dict = {"key_1": "val_1", "key_for_dict": {"sub_dict_key": 8}} reusables.save_json(my_dict,"example.json") example.json .. code:: { "key_1": "val_1", "key_for_dict": { "sub_dict_key": 8 } } :param data: dictionary to save as JSON :param json_file: Path to save file location as str :param indent: Format the JSON file with so many numbers of spaces :param kwargs: Additional arguments for the json.dump command
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L259-L287
cdgriffith/Reusables
reusables/file_operations.py
config_dict
def config_dict(config_file=None, auto_find=False, verify=True, **cfg_options): """ Return configuration options as dictionary. Accepts either a single config file or a list of files. Auto find will search for all .cfg, .config and .ini in the execution directory and package root (unsafe but handy). .. code:: python reusables.config_dict(os.path.join("test", "data", "test_config.ini")) # {'General': {'example': 'A regular string'}, # 'Section 2': {'anint': '234', # 'examplelist': '234,123,234,543', # 'floatly': '4.4', # 'my_bool': 'yes'}} :param config_file: path or paths to the files location :param auto_find: look for a config type file at this location or below :param verify: make sure the file exists before trying to read :param cfg_options: options to pass to the parser :return: dictionary of the config files """ if not config_file: config_file = [] cfg_parser = ConfigParser.ConfigParser(**cfg_options) cfg_files = [] if config_file: if not isinstance(config_file, (list, tuple)): if isinstance(config_file, str): cfg_files.append(config_file) else: raise TypeError("config_files must be a list or a string") else: cfg_files.extend(config_file) if auto_find: cfg_files.extend(find_files_list( current_root if isinstance(auto_find, bool) else auto_find, ext=(".cfg", ".config", ".ini"))) logger.info("config files to be used: {0}".format(cfg_files)) if verify: cfg_parser.read([cfg for cfg in cfg_files if os.path.exists(cfg)]) else: cfg_parser.read(cfg_files) return dict((section, dict(cfg_parser.items(section))) for section in cfg_parser.sections())
python
def config_dict(config_file=None, auto_find=False, verify=True, **cfg_options): """ Return configuration options as dictionary. Accepts either a single config file or a list of files. Auto find will search for all .cfg, .config and .ini in the execution directory and package root (unsafe but handy). .. code:: python reusables.config_dict(os.path.join("test", "data", "test_config.ini")) # {'General': {'example': 'A regular string'}, # 'Section 2': {'anint': '234', # 'examplelist': '234,123,234,543', # 'floatly': '4.4', # 'my_bool': 'yes'}} :param config_file: path or paths to the files location :param auto_find: look for a config type file at this location or below :param verify: make sure the file exists before trying to read :param cfg_options: options to pass to the parser :return: dictionary of the config files """ if not config_file: config_file = [] cfg_parser = ConfigParser.ConfigParser(**cfg_options) cfg_files = [] if config_file: if not isinstance(config_file, (list, tuple)): if isinstance(config_file, str): cfg_files.append(config_file) else: raise TypeError("config_files must be a list or a string") else: cfg_files.extend(config_file) if auto_find: cfg_files.extend(find_files_list( current_root if isinstance(auto_find, bool) else auto_find, ext=(".cfg", ".config", ".ini"))) logger.info("config files to be used: {0}".format(cfg_files)) if verify: cfg_parser.read([cfg for cfg in cfg_files if os.path.exists(cfg)]) else: cfg_parser.read(cfg_files) return dict((section, dict(cfg_parser.items(section))) for section in cfg_parser.sections())
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Return configuration options as dictionary. Accepts either a single config file or a list of files. Auto find will search for all .cfg, .config and .ini in the execution directory and package root (unsafe but handy). .. code:: python reusables.config_dict(os.path.join("test", "data", "test_config.ini")) # {'General': {'example': 'A regular string'}, # 'Section 2': {'anint': '234', # 'examplelist': '234,123,234,543', # 'floatly': '4.4', # 'my_bool': 'yes'}} :param config_file: path or paths to the files location :param auto_find: look for a config type file at this location or below :param verify: make sure the file exists before trying to read :param cfg_options: options to pass to the parser :return: dictionary of the config files
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L290-L340
cdgriffith/Reusables
reusables/file_operations.py
config_namespace
def config_namespace(config_file=None, auto_find=False, verify=True, **cfg_options): """ Return configuration options as a Namespace. .. code:: python reusables.config_namespace(os.path.join("test", "data", "test_config.ini")) # <Namespace: {'General': {'example': 'A regul...> :param config_file: path or paths to the files location :param auto_find: look for a config type file at this location or below :param verify: make sure the file exists before trying to read :param cfg_options: options to pass to the parser :return: Namespace of the config files """ return ConfigNamespace(**config_dict(config_file, auto_find, verify, **cfg_options))
python
def config_namespace(config_file=None, auto_find=False, verify=True, **cfg_options): """ Return configuration options as a Namespace. .. code:: python reusables.config_namespace(os.path.join("test", "data", "test_config.ini")) # <Namespace: {'General': {'example': 'A regul...> :param config_file: path or paths to the files location :param auto_find: look for a config type file at this location or below :param verify: make sure the file exists before trying to read :param cfg_options: options to pass to the parser :return: Namespace of the config files """ return ConfigNamespace(**config_dict(config_file, auto_find, verify, **cfg_options))
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Return configuration options as a Namespace. .. code:: python reusables.config_namespace(os.path.join("test", "data", "test_config.ini")) # <Namespace: {'General': {'example': 'A regul...> :param config_file: path or paths to the files location :param auto_find: look for a config type file at this location or below :param verify: make sure the file exists before trying to read :param cfg_options: options to pass to the parser :return: Namespace of the config files
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L343-L362
cdgriffith/Reusables
reusables/file_operations.py
_walk
def _walk(directory, enable_scandir=False, **kwargs): """ Internal function to return walk generator either from os or scandir :param directory: directory to traverse :param enable_scandir: on python < 3.5 enable external scandir package :param kwargs: arguments to pass to walk function :return: walk generator """ walk = os.walk if python_version < (3, 5) and enable_scandir: import scandir walk = scandir.walk return walk(directory, **kwargs)
python
def _walk(directory, enable_scandir=False, **kwargs): """ Internal function to return walk generator either from os or scandir :param directory: directory to traverse :param enable_scandir: on python < 3.5 enable external scandir package :param kwargs: arguments to pass to walk function :return: walk generator """ walk = os.walk if python_version < (3, 5) and enable_scandir: import scandir walk = scandir.walk return walk(directory, **kwargs)
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Internal function to return walk generator either from os or scandir :param directory: directory to traverse :param enable_scandir: on python < 3.5 enable external scandir package :param kwargs: arguments to pass to walk function :return: walk generator
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L365-L378
cdgriffith/Reusables
reusables/file_operations.py
os_tree
def os_tree(directory, enable_scandir=False): """ Return a directories contents as a dictionary hierarchy. .. code:: python reusables.os_tree(".") # {'doc': {'build': {'doctrees': {}, # 'html': {'_sources': {}, '_static': {}}}, # 'source': {}}, # 'reusables': {'__pycache__': {}}, # 'test': {'__pycache__': {}, 'data': {}}} :param directory: path to directory to created the tree of. :param enable_scandir: on python < 3.5 enable external scandir package :return: dictionary of the directory """ if not os.path.exists(directory): raise OSError("Directory does not exist") if not os.path.isdir(directory): raise OSError("Path is not a directory") full_list = [] for root, dirs, files in _walk(directory, enable_scandir=enable_scandir): full_list.extend([os.path.join(root, d).lstrip(directory) + os.sep for d in dirs]) tree = {os.path.basename(directory): {}} for item in full_list: separated = item.split(os.sep) is_dir = separated[-1:] == [''] if is_dir: separated = separated[:-1] parent = tree[os.path.basename(directory)] for index, path in enumerate(separated): if path in parent: parent = parent[path] continue else: parent[path] = dict() parent = parent[path] return tree
python
def os_tree(directory, enable_scandir=False): """ Return a directories contents as a dictionary hierarchy. .. code:: python reusables.os_tree(".") # {'doc': {'build': {'doctrees': {}, # 'html': {'_sources': {}, '_static': {}}}, # 'source': {}}, # 'reusables': {'__pycache__': {}}, # 'test': {'__pycache__': {}, 'data': {}}} :param directory: path to directory to created the tree of. :param enable_scandir: on python < 3.5 enable external scandir package :return: dictionary of the directory """ if not os.path.exists(directory): raise OSError("Directory does not exist") if not os.path.isdir(directory): raise OSError("Path is not a directory") full_list = [] for root, dirs, files in _walk(directory, enable_scandir=enable_scandir): full_list.extend([os.path.join(root, d).lstrip(directory) + os.sep for d in dirs]) tree = {os.path.basename(directory): {}} for item in full_list: separated = item.split(os.sep) is_dir = separated[-1:] == [''] if is_dir: separated = separated[:-1] parent = tree[os.path.basename(directory)] for index, path in enumerate(separated): if path in parent: parent = parent[path] continue else: parent[path] = dict() parent = parent[path] return tree
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Return a directories contents as a dictionary hierarchy. .. code:: python reusables.os_tree(".") # {'doc': {'build': {'doctrees': {}, # 'html': {'_sources': {}, '_static': {}}}, # 'source': {}}, # 'reusables': {'__pycache__': {}}, # 'test': {'__pycache__': {}, 'data': {}}} :param directory: path to directory to created the tree of. :param enable_scandir: on python < 3.5 enable external scandir package :return: dictionary of the directory
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L381-L422
cdgriffith/Reusables
reusables/file_operations.py
file_hash
def file_hash(path, hash_type="md5", block_size=65536, hex_digest=True): """ Hash a given file with md5, or any other and return the hex digest. You can run `hashlib.algorithms_available` to see which are available on your system unless you have an archaic python version, you poor soul). This function is designed to be non memory intensive. .. code:: python reusables.file_hash(test_structure.zip") # '61e387de305201a2c915a4f4277d6663' :param path: location of the file to hash :param hash_type: string name of the hash to use :param block_size: amount of bytes to add to hasher at a time :param hex_digest: returned as hexdigest, false will return digest :return: file's hash """ hashed = hashlib.new(hash_type) with open(path, "rb") as infile: buf = infile.read(block_size) while len(buf) > 0: hashed.update(buf) buf = infile.read(block_size) return hashed.hexdigest() if hex_digest else hashed.digest()
python
def file_hash(path, hash_type="md5", block_size=65536, hex_digest=True): """ Hash a given file with md5, or any other and return the hex digest. You can run `hashlib.algorithms_available` to see which are available on your system unless you have an archaic python version, you poor soul). This function is designed to be non memory intensive. .. code:: python reusables.file_hash(test_structure.zip") # '61e387de305201a2c915a4f4277d6663' :param path: location of the file to hash :param hash_type: string name of the hash to use :param block_size: amount of bytes to add to hasher at a time :param hex_digest: returned as hexdigest, false will return digest :return: file's hash """ hashed = hashlib.new(hash_type) with open(path, "rb") as infile: buf = infile.read(block_size) while len(buf) > 0: hashed.update(buf) buf = infile.read(block_size) return hashed.hexdigest() if hex_digest else hashed.digest()
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Hash a given file with md5, or any other and return the hex digest. You can run `hashlib.algorithms_available` to see which are available on your system unless you have an archaic python version, you poor soul). This function is designed to be non memory intensive. .. code:: python reusables.file_hash(test_structure.zip") # '61e387de305201a2c915a4f4277d6663' :param path: location of the file to hash :param hash_type: string name of the hash to use :param block_size: amount of bytes to add to hasher at a time :param hex_digest: returned as hexdigest, false will return digest :return: file's hash
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L425-L450
cdgriffith/Reusables
reusables/file_operations.py
find_files
def find_files(directory=".", ext=None, name=None, match_case=False, disable_glob=False, depth=None, abspath=False, enable_scandir=False): """ Walk through a file directory and return an iterator of files that match requirements. Will autodetect if name has glob as magic characters. Note: For the example below, you can use find_files_list to return as a list, this is simply an easy way to show the output. .. code:: python list(reusables.find_files(name="ex", match_case=True)) # ['C:\\example.pdf', # 'C:\\My_exam_score.txt'] list(reusables.find_files(name="*free*")) # ['C:\\my_stuff\\Freedom_fight.pdf'] list(reusables.find_files(ext=".pdf")) # ['C:\\Example.pdf', # 'C:\\how_to_program.pdf', # 'C:\\Hunks_and_Chicks.pdf'] list(reusables.find_files(name="*chris*")) # ['C:\\Christmas_card.docx', # 'C:\\chris_stuff.zip'] :param directory: Top location to recursively search for matching files :param ext: Extensions of the file you are looking for :param name: Part of the file name :param match_case: If name or ext has to be a direct match or not :param disable_glob: Do not look for globable names or use glob magic check :param depth: How many directories down to search :param abspath: Return files with their absolute paths :param enable_scandir: on python < 3.5 enable external scandir package :return: generator of all files in the specified directory """ if ext or not name: disable_glob = True if not disable_glob: disable_glob = not glob.has_magic(name) if ext and isinstance(ext, str): ext = [ext] elif ext and not isinstance(ext, (list, tuple)): raise TypeError("extension must be either one extension or a list") if abspath: directory = os.path.abspath(directory) starting_depth = directory.count(os.sep) for root, dirs, files in _walk(directory, enable_scandir=enable_scandir): if depth and root.count(os.sep) - starting_depth >= depth: continue if not disable_glob: if match_case: raise ValueError("Cannot use glob and match case, please " "either disable glob or not set match_case") glob_generator = glob.iglob(os.path.join(root, name)) for item in glob_generator: yield item continue for file_name in files: if ext: for end in ext: if file_name.lower().endswith(end.lower() if not match_case else end): break else: continue if name: if match_case and name not in file_name: continue elif name.lower() not in file_name.lower(): continue yield os.path.join(root, file_name)
python
def find_files(directory=".", ext=None, name=None, match_case=False, disable_glob=False, depth=None, abspath=False, enable_scandir=False): """ Walk through a file directory and return an iterator of files that match requirements. Will autodetect if name has glob as magic characters. Note: For the example below, you can use find_files_list to return as a list, this is simply an easy way to show the output. .. code:: python list(reusables.find_files(name="ex", match_case=True)) # ['C:\\example.pdf', # 'C:\\My_exam_score.txt'] list(reusables.find_files(name="*free*")) # ['C:\\my_stuff\\Freedom_fight.pdf'] list(reusables.find_files(ext=".pdf")) # ['C:\\Example.pdf', # 'C:\\how_to_program.pdf', # 'C:\\Hunks_and_Chicks.pdf'] list(reusables.find_files(name="*chris*")) # ['C:\\Christmas_card.docx', # 'C:\\chris_stuff.zip'] :param directory: Top location to recursively search for matching files :param ext: Extensions of the file you are looking for :param name: Part of the file name :param match_case: If name or ext has to be a direct match or not :param disable_glob: Do not look for globable names or use glob magic check :param depth: How many directories down to search :param abspath: Return files with their absolute paths :param enable_scandir: on python < 3.5 enable external scandir package :return: generator of all files in the specified directory """ if ext or not name: disable_glob = True if not disable_glob: disable_glob = not glob.has_magic(name) if ext and isinstance(ext, str): ext = [ext] elif ext and not isinstance(ext, (list, tuple)): raise TypeError("extension must be either one extension or a list") if abspath: directory = os.path.abspath(directory) starting_depth = directory.count(os.sep) for root, dirs, files in _walk(directory, enable_scandir=enable_scandir): if depth and root.count(os.sep) - starting_depth >= depth: continue if not disable_glob: if match_case: raise ValueError("Cannot use glob and match case, please " "either disable glob or not set match_case") glob_generator = glob.iglob(os.path.join(root, name)) for item in glob_generator: yield item continue for file_name in files: if ext: for end in ext: if file_name.lower().endswith(end.lower() if not match_case else end): break else: continue if name: if match_case and name not in file_name: continue elif name.lower() not in file_name.lower(): continue yield os.path.join(root, file_name)
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Walk through a file directory and return an iterator of files that match requirements. Will autodetect if name has glob as magic characters. Note: For the example below, you can use find_files_list to return as a list, this is simply an easy way to show the output. .. code:: python list(reusables.find_files(name="ex", match_case=True)) # ['C:\\example.pdf', # 'C:\\My_exam_score.txt'] list(reusables.find_files(name="*free*")) # ['C:\\my_stuff\\Freedom_fight.pdf'] list(reusables.find_files(ext=".pdf")) # ['C:\\Example.pdf', # 'C:\\how_to_program.pdf', # 'C:\\Hunks_and_Chicks.pdf'] list(reusables.find_files(name="*chris*")) # ['C:\\Christmas_card.docx', # 'C:\\chris_stuff.zip'] :param directory: Top location to recursively search for matching files :param ext: Extensions of the file you are looking for :param name: Part of the file name :param match_case: If name or ext has to be a direct match or not :param disable_glob: Do not look for globable names or use glob magic check :param depth: How many directories down to search :param abspath: Return files with their absolute paths :param enable_scandir: on python < 3.5 enable external scandir package :return: generator of all files in the specified directory
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L463-L541
cdgriffith/Reusables
reusables/file_operations.py
remove_empty_directories
def remove_empty_directories(root_directory, dry_run=False, ignore_errors=True, enable_scandir=False): """ Remove all empty folders from a path. Returns list of empty directories. :param root_directory: base directory to start at :param dry_run: just return a list of what would be removed :param ignore_errors: Permissions are a pain, just ignore if you blocked :param enable_scandir: on python < 3.5 enable external scandir package :return: list of removed directories """ listdir = os.listdir if python_version < (3, 5) and enable_scandir: import scandir as _scandir def listdir(directory): return list(_scandir.scandir(directory)) directory_list = [] for root, directories, files in _walk(root_directory, enable_scandir=enable_scandir, topdown=False): if (not directories and not files and os.path.exists(root) and root != root_directory and os.path.isdir(root)): directory_list.append(root) if not dry_run: try: os.rmdir(root) except OSError as err: if ignore_errors: logger.info("{0} could not be deleted".format(root)) else: raise err elif directories and not files: for directory in directories: directory = join_paths(root, directory, strict=True) if (os.path.exists(directory) and os.path.isdir(directory) and not listdir(directory)): directory_list.append(directory) if not dry_run: try: os.rmdir(directory) except OSError as err: if ignore_errors: logger.info("{0} could not be deleted".format( directory)) else: raise err return directory_list
python
def remove_empty_directories(root_directory, dry_run=False, ignore_errors=True, enable_scandir=False): """ Remove all empty folders from a path. Returns list of empty directories. :param root_directory: base directory to start at :param dry_run: just return a list of what would be removed :param ignore_errors: Permissions are a pain, just ignore if you blocked :param enable_scandir: on python < 3.5 enable external scandir package :return: list of removed directories """ listdir = os.listdir if python_version < (3, 5) and enable_scandir: import scandir as _scandir def listdir(directory): return list(_scandir.scandir(directory)) directory_list = [] for root, directories, files in _walk(root_directory, enable_scandir=enable_scandir, topdown=False): if (not directories and not files and os.path.exists(root) and root != root_directory and os.path.isdir(root)): directory_list.append(root) if not dry_run: try: os.rmdir(root) except OSError as err: if ignore_errors: logger.info("{0} could not be deleted".format(root)) else: raise err elif directories and not files: for directory in directories: directory = join_paths(root, directory, strict=True) if (os.path.exists(directory) and os.path.isdir(directory) and not listdir(directory)): directory_list.append(directory) if not dry_run: try: os.rmdir(directory) except OSError as err: if ignore_errors: logger.info("{0} could not be deleted".format( directory)) else: raise err return directory_list
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Remove all empty folders from a path. Returns list of empty directories. :param root_directory: base directory to start at :param dry_run: just return a list of what would be removed :param ignore_errors: Permissions are a pain, just ignore if you blocked :param enable_scandir: on python < 3.5 enable external scandir package :return: list of removed directories
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L544-L592
cdgriffith/Reusables
reusables/file_operations.py
remove_empty_files
def remove_empty_files(root_directory, dry_run=False, ignore_errors=True, enable_scandir=False): """ Remove all empty files from a path. Returns list of the empty files removed. :param root_directory: base directory to start at :param dry_run: just return a list of what would be removed :param ignore_errors: Permissions are a pain, just ignore if you blocked :param enable_scandir: on python < 3.5 enable external scandir package :return: list of removed files """ file_list = [] for root, directories, files in _walk(root_directory, enable_scandir=enable_scandir): for file_name in files: file_path = join_paths(root, file_name, strict=True) if os.path.isfile(file_path) and not os.path.getsize(file_path): if file_hash(file_path) == variables.hashes.empty_file.md5: file_list.append(file_path) file_list = sorted(set(file_list)) if not dry_run: for afile in file_list: try: os.unlink(afile) except OSError as err: if ignore_errors: logger.info("File {0} could not be deleted".format(afile)) else: raise err return file_list
python
def remove_empty_files(root_directory, dry_run=False, ignore_errors=True, enable_scandir=False): """ Remove all empty files from a path. Returns list of the empty files removed. :param root_directory: base directory to start at :param dry_run: just return a list of what would be removed :param ignore_errors: Permissions are a pain, just ignore if you blocked :param enable_scandir: on python < 3.5 enable external scandir package :return: list of removed files """ file_list = [] for root, directories, files in _walk(root_directory, enable_scandir=enable_scandir): for file_name in files: file_path = join_paths(root, file_name, strict=True) if os.path.isfile(file_path) and not os.path.getsize(file_path): if file_hash(file_path) == variables.hashes.empty_file.md5: file_list.append(file_path) file_list = sorted(set(file_list)) if not dry_run: for afile in file_list: try: os.unlink(afile) except OSError as err: if ignore_errors: logger.info("File {0} could not be deleted".format(afile)) else: raise err return file_list
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Remove all empty files from a path. Returns list of the empty files removed. :param root_directory: base directory to start at :param dry_run: just return a list of what would be removed :param ignore_errors: Permissions are a pain, just ignore if you blocked :param enable_scandir: on python < 3.5 enable external scandir package :return: list of removed files
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L595-L627
cdgriffith/Reusables
reusables/file_operations.py
dup_finder
def dup_finder(file_path, directory=".", enable_scandir=False): """ Check a directory for duplicates of the specified file. This is meant for a single file only, for checking a directory for dups, use directory_duplicates. This is designed to be as fast as possible by doing lighter checks before progressing to more extensive ones, in order they are: 1. File size 2. First twenty bytes 3. Full SHA256 compare .. code:: python list(reusables.dup_finder( "test_structure\\files_2\\empty_file")) # ['C:\\Reusables\\test\\data\\fake_dir', # 'C:\\Reusables\\test\\data\\test_structure\\Files\\empty_file_1', # 'C:\\Reusables\\test\\data\\test_structure\\Files\\empty_file_2', # 'C:\\Reusables\\test\\data\\test_structure\\files_2\\empty_file'] :param file_path: Path to file to check for duplicates of :param directory: Directory to dig recursively into to look for duplicates :param enable_scandir: on python < 3.5 enable external scandir package :return: generators """ size = os.path.getsize(file_path) if size == 0: for empty_file in remove_empty_files(directory, dry_run=True): yield empty_file else: with open(file_path, 'rb') as f: first_twenty = f.read(20) file_sha256 = file_hash(file_path, "sha256") for root, directories, files in _walk(directory, enable_scandir=enable_scandir): for each_file in files: test_file = os.path.join(root, each_file) if os.path.getsize(test_file) == size: try: with open(test_file, 'rb') as f: test_first_twenty = f.read(20) except OSError: logger.warning("Could not open file to compare - " "{0}".format(test_file)) else: if first_twenty == test_first_twenty: if file_hash(test_file, "sha256") == file_sha256: yield os.path.abspath(test_file)
python
def dup_finder(file_path, directory=".", enable_scandir=False): """ Check a directory for duplicates of the specified file. This is meant for a single file only, for checking a directory for dups, use directory_duplicates. This is designed to be as fast as possible by doing lighter checks before progressing to more extensive ones, in order they are: 1. File size 2. First twenty bytes 3. Full SHA256 compare .. code:: python list(reusables.dup_finder( "test_structure\\files_2\\empty_file")) # ['C:\\Reusables\\test\\data\\fake_dir', # 'C:\\Reusables\\test\\data\\test_structure\\Files\\empty_file_1', # 'C:\\Reusables\\test\\data\\test_structure\\Files\\empty_file_2', # 'C:\\Reusables\\test\\data\\test_structure\\files_2\\empty_file'] :param file_path: Path to file to check for duplicates of :param directory: Directory to dig recursively into to look for duplicates :param enable_scandir: on python < 3.5 enable external scandir package :return: generators """ size = os.path.getsize(file_path) if size == 0: for empty_file in remove_empty_files(directory, dry_run=True): yield empty_file else: with open(file_path, 'rb') as f: first_twenty = f.read(20) file_sha256 = file_hash(file_path, "sha256") for root, directories, files in _walk(directory, enable_scandir=enable_scandir): for each_file in files: test_file = os.path.join(root, each_file) if os.path.getsize(test_file) == size: try: with open(test_file, 'rb') as f: test_first_twenty = f.read(20) except OSError: logger.warning("Could not open file to compare - " "{0}".format(test_file)) else: if first_twenty == test_first_twenty: if file_hash(test_file, "sha256") == file_sha256: yield os.path.abspath(test_file)
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Check a directory for duplicates of the specified file. This is meant for a single file only, for checking a directory for dups, use directory_duplicates. This is designed to be as fast as possible by doing lighter checks before progressing to more extensive ones, in order they are: 1. File size 2. First twenty bytes 3. Full SHA256 compare .. code:: python list(reusables.dup_finder( "test_structure\\files_2\\empty_file")) # ['C:\\Reusables\\test\\data\\fake_dir', # 'C:\\Reusables\\test\\data\\test_structure\\Files\\empty_file_1', # 'C:\\Reusables\\test\\data\\test_structure\\Files\\empty_file_2', # 'C:\\Reusables\\test\\data\\test_structure\\files_2\\empty_file'] :param file_path: Path to file to check for duplicates of :param directory: Directory to dig recursively into to look for duplicates :param enable_scandir: on python < 3.5 enable external scandir package :return: generators
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L630-L681
cdgriffith/Reusables
reusables/file_operations.py
directory_duplicates
def directory_duplicates(directory, hash_type='md5', **kwargs): """ Find all duplicates in a directory. Will return a list, in that list are lists of duplicate files. .. code: python dups = reusables.directory_duplicates('C:\\Users\\Me\\Pictures') print(len(dups)) # 56 print(dups) # [['C:\\Users\\Me\\Pictures\\IMG_20161127.jpg', # 'C:\\Users\\Me\\Pictures\\Phone\\IMG_20161127.jpg'], ... :param directory: Directory to search :param hash_type: Type of hash to perform :param kwargs: Arguments to pass to find_files to narrow file types :return: list of lists of dups""" size_map, hash_map = defaultdict(list), defaultdict(list) for item in find_files(directory, **kwargs): file_size = os.path.getsize(item) size_map[file_size].append(item) for possible_dups in (v for v in size_map.values() if len(v) > 1): for each_item in possible_dups: item_hash = file_hash(each_item, hash_type=hash_type) hash_map[item_hash].append(each_item) return [v for v in hash_map.values() if len(v) > 1]
python
def directory_duplicates(directory, hash_type='md5', **kwargs): """ Find all duplicates in a directory. Will return a list, in that list are lists of duplicate files. .. code: python dups = reusables.directory_duplicates('C:\\Users\\Me\\Pictures') print(len(dups)) # 56 print(dups) # [['C:\\Users\\Me\\Pictures\\IMG_20161127.jpg', # 'C:\\Users\\Me\\Pictures\\Phone\\IMG_20161127.jpg'], ... :param directory: Directory to search :param hash_type: Type of hash to perform :param kwargs: Arguments to pass to find_files to narrow file types :return: list of lists of dups""" size_map, hash_map = defaultdict(list), defaultdict(list) for item in find_files(directory, **kwargs): file_size = os.path.getsize(item) size_map[file_size].append(item) for possible_dups in (v for v in size_map.values() if len(v) > 1): for each_item in possible_dups: item_hash = file_hash(each_item, hash_type=hash_type) hash_map[item_hash].append(each_item) return [v for v in hash_map.values() if len(v) > 1]
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Find all duplicates in a directory. Will return a list, in that list are lists of duplicate files. .. code: python dups = reusables.directory_duplicates('C:\\Users\\Me\\Pictures') print(len(dups)) # 56 print(dups) # [['C:\\Users\\Me\\Pictures\\IMG_20161127.jpg', # 'C:\\Users\\Me\\Pictures\\Phone\\IMG_20161127.jpg'], ... :param directory: Directory to search :param hash_type: Type of hash to perform :param kwargs: Arguments to pass to find_files to narrow file types :return: list of lists of dups
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L684-L715
cdgriffith/Reusables
reusables/file_operations.py
join_paths
def join_paths(*paths, **kwargs): """ Join multiple paths together and return the absolute path of them. If 'safe' is specified, this function will 'clean' the path with the 'safe_path' function. This will clean root decelerations from the path after the first item. Would like to do 'safe=False' instead of '**kwargs' but stupider versions of python *cough 2.6* don't like that after '*paths'. .. code: python reusables.join_paths("var", "\\log", "/test") 'C:\\Users\\Me\\var\\log\\test' os.path.join("var", "\\log", "/test") '/test' :param paths: paths to join together :param kwargs: 'safe', make them into a safe path it True :return: abspath as string """ path = os.path.abspath(paths[0]) for next_path in paths[1:]: path = os.path.join(path, next_path.lstrip("\\").lstrip("/").strip()) path.rstrip(os.sep) return path if not kwargs.get('safe') else safe_path(path)
python
def join_paths(*paths, **kwargs): """ Join multiple paths together and return the absolute path of them. If 'safe' is specified, this function will 'clean' the path with the 'safe_path' function. This will clean root decelerations from the path after the first item. Would like to do 'safe=False' instead of '**kwargs' but stupider versions of python *cough 2.6* don't like that after '*paths'. .. code: python reusables.join_paths("var", "\\log", "/test") 'C:\\Users\\Me\\var\\log\\test' os.path.join("var", "\\log", "/test") '/test' :param paths: paths to join together :param kwargs: 'safe', make them into a safe path it True :return: abspath as string """ path = os.path.abspath(paths[0]) for next_path in paths[1:]: path = os.path.join(path, next_path.lstrip("\\").lstrip("/").strip()) path.rstrip(os.sep) return path if not kwargs.get('safe') else safe_path(path)
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L728-L755
cdgriffith/Reusables
reusables/file_operations.py
join_here
def join_here(*paths, **kwargs): """ Join any path or paths as a sub directory of the current file's directory. .. code:: python reusables.join_here("Makefile") # 'C:\\Reusables\\Makefile' :param paths: paths to join together :param kwargs: 'strict', do not strip os.sep :param kwargs: 'safe', make them into a safe path it True :return: abspath as string """ path = os.path.abspath(".") for next_path in paths: next_path = next_path.lstrip("\\").lstrip("/").strip() if not \ kwargs.get('strict') else next_path path = os.path.abspath(os.path.join(path, next_path)) return path if not kwargs.get('safe') else safe_path(path)
python
def join_here(*paths, **kwargs): """ Join any path or paths as a sub directory of the current file's directory. .. code:: python reusables.join_here("Makefile") # 'C:\\Reusables\\Makefile' :param paths: paths to join together :param kwargs: 'strict', do not strip os.sep :param kwargs: 'safe', make them into a safe path it True :return: abspath as string """ path = os.path.abspath(".") for next_path in paths: next_path = next_path.lstrip("\\").lstrip("/").strip() if not \ kwargs.get('strict') else next_path path = os.path.abspath(os.path.join(path, next_path)) return path if not kwargs.get('safe') else safe_path(path)
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Join any path or paths as a sub directory of the current file's directory. .. code:: python reusables.join_here("Makefile") # 'C:\\Reusables\\Makefile' :param paths: paths to join together :param kwargs: 'strict', do not strip os.sep :param kwargs: 'safe', make them into a safe path it True :return: abspath as string
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L758-L777
cdgriffith/Reusables
reusables/file_operations.py
check_filename
def check_filename(filename): """ Returns a boolean stating if the filename is safe to use or not. Note that this does not test for "legal" names accepted, but a more restricted set of: Letters, numbers, spaces, hyphens, underscores and periods. :param filename: name of a file as a string :return: boolean if it is a safe file name """ if not isinstance(filename, str): raise TypeError("filename must be a string") if regex.path.linux.filename.search(filename): return True return False
python
def check_filename(filename): """ Returns a boolean stating if the filename is safe to use or not. Note that this does not test for "legal" names accepted, but a more restricted set of: Letters, numbers, spaces, hyphens, underscores and periods. :param filename: name of a file as a string :return: boolean if it is a safe file name """ if not isinstance(filename, str): raise TypeError("filename must be a string") if regex.path.linux.filename.search(filename): return True return False
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Returns a boolean stating if the filename is safe to use or not. Note that this does not test for "legal" names accepted, but a more restricted set of: Letters, numbers, spaces, hyphens, underscores and periods. :param filename: name of a file as a string :return: boolean if it is a safe file name
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L780-L793
cdgriffith/Reusables
reusables/file_operations.py
safe_filename
def safe_filename(filename, replacement="_"): """ Replace unsafe filename characters with underscores. Note that this does not test for "legal" names accepted, but a more restricted set of: Letters, numbers, spaces, hyphens, underscores and periods. :param filename: name of a file as a string :param replacement: character to use as a replacement of bad characters :return: safe filename string """ if not isinstance(filename, str): raise TypeError("filename must be a string") if regex.path.linux.filename.search(filename): return filename safe_name = "" for char in filename: safe_name += char if regex.path.linux.filename.search(char) \ else replacement return safe_name
python
def safe_filename(filename, replacement="_"): """ Replace unsafe filename characters with underscores. Note that this does not test for "legal" names accepted, but a more restricted set of: Letters, numbers, spaces, hyphens, underscores and periods. :param filename: name of a file as a string :param replacement: character to use as a replacement of bad characters :return: safe filename string """ if not isinstance(filename, str): raise TypeError("filename must be a string") if regex.path.linux.filename.search(filename): return filename safe_name = "" for char in filename: safe_name += char if regex.path.linux.filename.search(char) \ else replacement return safe_name
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Replace unsafe filename characters with underscores. Note that this does not test for "legal" names accepted, but a more restricted set of: Letters, numbers, spaces, hyphens, underscores and periods. :param filename: name of a file as a string :param replacement: character to use as a replacement of bad characters :return: safe filename string
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L796-L814
cdgriffith/Reusables
reusables/file_operations.py
safe_path
def safe_path(path, replacement="_"): """ Replace unsafe path characters with underscores. Do NOT use this with existing paths that cannot be modified, this to to help generate new, clean paths. Supports windows and *nix systems. :param path: path as a string :param replacement: character to use in place of bad characters :return: a safer path """ if not isinstance(path, str): raise TypeError("path must be a string") if os.sep not in path: return safe_filename(path, replacement=replacement) filename = safe_filename(os.path.basename(path)) dirname = os.path.dirname(path) safe_dirname = "" regexp = regex.path.windows.safe if win_based else regex.path.linux.safe if win_based and dirname.find(":\\") == 1 and dirname[0].isalpha(): safe_dirname = dirname[0:3] dirname = dirname[3:] if regexp.search(dirname) and check_filename(filename): return path else: for char in dirname: safe_dirname += char if regexp.search(char) else replacement sanitized_path = os.path.normpath("{path}{sep}{filename}".format( path=safe_dirname, sep=os.sep if not safe_dirname.endswith(os.sep) else "", filename=filename)) if (not filename and path.endswith(os.sep) and not sanitized_path.endswith(os.sep)): sanitized_path += os.sep return sanitized_path
python
def safe_path(path, replacement="_"): """ Replace unsafe path characters with underscores. Do NOT use this with existing paths that cannot be modified, this to to help generate new, clean paths. Supports windows and *nix systems. :param path: path as a string :param replacement: character to use in place of bad characters :return: a safer path """ if not isinstance(path, str): raise TypeError("path must be a string") if os.sep not in path: return safe_filename(path, replacement=replacement) filename = safe_filename(os.path.basename(path)) dirname = os.path.dirname(path) safe_dirname = "" regexp = regex.path.windows.safe if win_based else regex.path.linux.safe if win_based and dirname.find(":\\") == 1 and dirname[0].isalpha(): safe_dirname = dirname[0:3] dirname = dirname[3:] if regexp.search(dirname) and check_filename(filename): return path else: for char in dirname: safe_dirname += char if regexp.search(char) else replacement sanitized_path = os.path.normpath("{path}{sep}{filename}".format( path=safe_dirname, sep=os.sep if not safe_dirname.endswith(os.sep) else "", filename=filename)) if (not filename and path.endswith(os.sep) and not sanitized_path.endswith(os.sep)): sanitized_path += os.sep return sanitized_path
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Replace unsafe path characters with underscores. Do NOT use this with existing paths that cannot be modified, this to to help generate new, clean paths. Supports windows and *nix systems. :param path: path as a string :param replacement: character to use in place of bad characters :return: a safer path
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/file_operations.py#L817-L853
cdgriffith/Reusables
reusables/tasker.py
Tasker.change_task_size
def change_task_size(self, size): """Blocking request to change number of running tasks""" self._pause.value = True self.log.debug("About to change task size to {0}".format(size)) try: size = int(size) except ValueError: self.log.error("Cannot change task size, non integer size provided") return False if size < 0: self.log.error("Cannot change task size, less than 0 size provided") return False self.max_tasks = size if size < self.max_tasks: diff = self.max_tasks - size self.log.debug("Reducing size offset by {0}".format(diff)) while True: self._update_tasks() if len(self.free_tasks) >= diff: for i in range(diff): task_id = self.free_tasks.pop(0) del self.current_tasks[task_id] break time.sleep(0.5) if not size: self._reset_and_pause() return True elif size > self.max_tasks: diff = size - self.max_tasks for i in range(diff): task_id = str(uuid.uuid4()) self.current_tasks[task_id] = {} self.free_tasks.append(task_id) self._pause.value = False self.log.debug("Task size changed to {0}".format(size)) return True
python
def change_task_size(self, size): """Blocking request to change number of running tasks""" self._pause.value = True self.log.debug("About to change task size to {0}".format(size)) try: size = int(size) except ValueError: self.log.error("Cannot change task size, non integer size provided") return False if size < 0: self.log.error("Cannot change task size, less than 0 size provided") return False self.max_tasks = size if size < self.max_tasks: diff = self.max_tasks - size self.log.debug("Reducing size offset by {0}".format(diff)) while True: self._update_tasks() if len(self.free_tasks) >= diff: for i in range(diff): task_id = self.free_tasks.pop(0) del self.current_tasks[task_id] break time.sleep(0.5) if not size: self._reset_and_pause() return True elif size > self.max_tasks: diff = size - self.max_tasks for i in range(diff): task_id = str(uuid.uuid4()) self.current_tasks[task_id] = {} self.free_tasks.append(task_id) self._pause.value = False self.log.debug("Task size changed to {0}".format(size)) return True
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Blocking request to change number of running tasks
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/tasker.py#L128-L163
cdgriffith/Reusables
reusables/tasker.py
Tasker.stop
def stop(self): """Hard stop the server and sub process""" self._end.value = True if self.background_process: try: self.background_process.terminate() except Exception: pass for task_id, values in self.current_tasks.items(): try: values['proc'].terminate() except Exception: pass
python
def stop(self): """Hard stop the server and sub process""" self._end.value = True if self.background_process: try: self.background_process.terminate() except Exception: pass for task_id, values in self.current_tasks.items(): try: values['proc'].terminate() except Exception: pass
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Hard stop the server and sub process
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/tasker.py#L165-L177
cdgriffith/Reusables
reusables/tasker.py
Tasker.get_state
def get_state(self): """Get general information about the state of the class""" return {"started": (True if self.background_process and self.background_process.is_alive() else False), "paused": self._pause.value, "stopped": self._end.value, "tasks": len(self.current_tasks), "busy_tasks": len(self.busy_tasks), "free_tasks": len(self.free_tasks)}
python
def get_state(self): """Get general information about the state of the class""" return {"started": (True if self.background_process and self.background_process.is_alive() else False), "paused": self._pause.value, "stopped": self._end.value, "tasks": len(self.current_tasks), "busy_tasks": len(self.busy_tasks), "free_tasks": len(self.free_tasks)}
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Get general information about the state of the class
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/tasker.py#L187-L195
cdgriffith/Reusables
reusables/tasker.py
Tasker.main_loop
def main_loop(self, stop_at_empty=False): """Blocking function that can be run directly, if so would probably want to specify 'stop_at_empty' to true, or have a separate process adding items to the queue. """ try: while True: self.hook_pre_command() self._check_command_queue() if self.run_until and self.run_until < datetime.datetime.now(): self.log.info("Time limit reached") break if self._end.value: break if self._pause.value: time.sleep(.5) continue self.hook_post_command() self._update_tasks() task_id = self._free_task() if task_id: try: task = self.task_queue.get(timeout=.1) except queue.Empty: if stop_at_empty: break self._return_task(task_id) else: self.hook_pre_task() self.log.debug("Starting task on {0}".format(task_id)) try: self._start_task(task_id, task) except Exception as err: self.log.exception("Could not start task {0} -" " {1}".format(task_id, err)) else: self.hook_post_task() finally: self.log.info("Ending main loop")
python
def main_loop(self, stop_at_empty=False): """Blocking function that can be run directly, if so would probably want to specify 'stop_at_empty' to true, or have a separate process adding items to the queue. """ try: while True: self.hook_pre_command() self._check_command_queue() if self.run_until and self.run_until < datetime.datetime.now(): self.log.info("Time limit reached") break if self._end.value: break if self._pause.value: time.sleep(.5) continue self.hook_post_command() self._update_tasks() task_id = self._free_task() if task_id: try: task = self.task_queue.get(timeout=.1) except queue.Empty: if stop_at_empty: break self._return_task(task_id) else: self.hook_pre_task() self.log.debug("Starting task on {0}".format(task_id)) try: self._start_task(task_id, task) except Exception as err: self.log.exception("Could not start task {0} -" " {1}".format(task_id, err)) else: self.hook_post_task() finally: self.log.info("Ending main loop")
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Blocking function that can be run directly, if so would probably want to specify 'stop_at_empty' to true, or have a separate process adding items to the queue.
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/tasker.py#L232-L269
cdgriffith/Reusables
reusables/tasker.py
Tasker.run
def run(self): """Start the main loop as a background process. *nix only""" if win_based: raise NotImplementedError("Please run main_loop, " "backgrounding not supported on Windows") self.background_process = mp.Process(target=self.main_loop) self.background_process.start()
python
def run(self): """Start the main loop as a background process. *nix only""" if win_based: raise NotImplementedError("Please run main_loop, " "backgrounding not supported on Windows") self.background_process = mp.Process(target=self.main_loop) self.background_process.start()
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Start the main loop as a background process. *nix only
[ "Start", "the", "main", "loop", "as", "a", "background", "process", ".", "*", "nix", "only" ]
train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/tasker.py#L271-L277
cdgriffith/Reusables
reusables/cli.py
cmd
def cmd(command, ignore_stderr=False, raise_on_return=False, timeout=None, encoding="utf-8"): """ Run a shell command and have it automatically decoded and printed :param command: Command to run as str :param ignore_stderr: To not print stderr :param raise_on_return: Run CompletedProcess.check_returncode() :param timeout: timeout to pass to communicate if python 3 :param encoding: How the output should be decoded """ result = run(command, timeout=timeout, shell=True) if raise_on_return: result.check_returncode() print(result.stdout.decode(encoding)) if not ignore_stderr and result.stderr: print(result.stderr.decode(encoding))
python
def cmd(command, ignore_stderr=False, raise_on_return=False, timeout=None, encoding="utf-8"): """ Run a shell command and have it automatically decoded and printed :param command: Command to run as str :param ignore_stderr: To not print stderr :param raise_on_return: Run CompletedProcess.check_returncode() :param timeout: timeout to pass to communicate if python 3 :param encoding: How the output should be decoded """ result = run(command, timeout=timeout, shell=True) if raise_on_return: result.check_returncode() print(result.stdout.decode(encoding)) if not ignore_stderr and result.stderr: print(result.stderr.decode(encoding))
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Run a shell command and have it automatically decoded and printed :param command: Command to run as str :param ignore_stderr: To not print stderr :param raise_on_return: Run CompletedProcess.check_returncode() :param timeout: timeout to pass to communicate if python 3 :param encoding: How the output should be decoded
[ "Run", "a", "shell", "command", "and", "have", "it", "automatically", "decoded", "and", "printed" ]
train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/cli.py#L29-L44
cdgriffith/Reusables
reusables/cli.py
pushd
def pushd(directory): """Change working directories in style and stay organized! :param directory: Where do you want to go and remember? :return: saved directory stack """ directory = os.path.expanduser(directory) _saved_paths.insert(0, os.path.abspath(os.getcwd())) os.chdir(directory) return [directory] + _saved_paths
python
def pushd(directory): """Change working directories in style and stay organized! :param directory: Where do you want to go and remember? :return: saved directory stack """ directory = os.path.expanduser(directory) _saved_paths.insert(0, os.path.abspath(os.getcwd())) os.chdir(directory) return [directory] + _saved_paths
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Change working directories in style and stay organized! :param directory: Where do you want to go and remember? :return: saved directory stack
[ "Change", "working", "directories", "in", "style", "and", "stay", "organized!" ]
train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/cli.py#L47-L56
cdgriffith/Reusables
reusables/cli.py
popd
def popd(): """Go back to where you once were. :return: saved directory stack """ try: directory = _saved_paths.pop(0) except IndexError: return [os.getcwd()] os.chdir(directory) return [directory] + _saved_paths
python
def popd(): """Go back to where you once were. :return: saved directory stack """ try: directory = _saved_paths.pop(0) except IndexError: return [os.getcwd()] os.chdir(directory) return [directory] + _saved_paths
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Go back to where you once were. :return: saved directory stack
[ "Go", "back", "to", "where", "you", "once", "were", "." ]
train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/cli.py#L59-L69
cdgriffith/Reusables
reusables/cli.py
ls
def ls(params="", directory=".", printed=True): """Know the best python implantation of ls? It's just to subprocess ls... (uses dir on windows). :param params: options to pass to ls or dir :param directory: if not this directory :param printed: If you're using this, you probably wanted it just printed :return: if not printed, you can parse it yourself """ command = "{0} {1} {2}".format("ls" if not win_based else "dir", params, directory) response = run(command, shell=True) # Shell required for windows response.check_returncode() if printed: print(response.stdout.decode("utf-8")) else: return response.stdout
python
def ls(params="", directory=".", printed=True): """Know the best python implantation of ls? It's just to subprocess ls... (uses dir on windows). :param params: options to pass to ls or dir :param directory: if not this directory :param printed: If you're using this, you probably wanted it just printed :return: if not printed, you can parse it yourself """ command = "{0} {1} {2}".format("ls" if not win_based else "dir", params, directory) response = run(command, shell=True) # Shell required for windows response.check_returncode() if printed: print(response.stdout.decode("utf-8")) else: return response.stdout
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Know the best python implantation of ls? It's just to subprocess ls... (uses dir on windows). :param params: options to pass to ls or dir :param directory: if not this directory :param printed: If you're using this, you probably wanted it just printed :return: if not printed, you can parse it yourself
[ "Know", "the", "best", "python", "implantation", "of", "ls?", "It", "s", "just", "to", "subprocess", "ls", "...", "(", "uses", "dir", "on", "windows", ")", "." ]
train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/cli.py#L85-L101
cdgriffith/Reusables
reusables/cli.py
find
def find(name=None, ext=None, directory=".", match_case=False, disable_glob=False, depth=None): """ Designed for the interactive interpreter by making default order of find_files faster. :param name: Part of the file name :param ext: Extensions of the file you are looking for :param directory: Top location to recursively search for matching files :param match_case: If name has to be a direct match or not :param disable_glob: Do not look for globable names or use glob magic check :param depth: How many directories down to search :return: list of all files in the specified directory """ return find_files_list(directory=directory, ext=ext, name=name, match_case=match_case, disable_glob=disable_glob, depth=depth)
python
def find(name=None, ext=None, directory=".", match_case=False, disable_glob=False, depth=None): """ Designed for the interactive interpreter by making default order of find_files faster. :param name: Part of the file name :param ext: Extensions of the file you are looking for :param directory: Top location to recursively search for matching files :param match_case: If name has to be a direct match or not :param disable_glob: Do not look for globable names or use glob magic check :param depth: How many directories down to search :return: list of all files in the specified directory """ return find_files_list(directory=directory, ext=ext, name=name, match_case=match_case, disable_glob=disable_glob, depth=depth)
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Designed for the interactive interpreter by making default order of find_files faster. :param name: Part of the file name :param ext: Extensions of the file you are looking for :param directory: Top location to recursively search for matching files :param match_case: If name has to be a direct match or not :param disable_glob: Do not look for globable names or use glob magic check :param depth: How many directories down to search :return: list of all files in the specified directory
[ "Designed", "for", "the", "interactive", "interpreter", "by", "making", "default", "order", "of", "find_files", "faster", "." ]
train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/cli.py#L104-L119
cdgriffith/Reusables
reusables/cli.py
head
def head(file_path, lines=10, encoding="utf-8", printed=True, errors='strict'): """ Read the first N lines of a file, defaults to 10 :param file_path: Path to file to read :param lines: Number of lines to read in :param encoding: defaults to utf-8 to decode as, will fail on binary :param printed: Automatically print the lines instead of returning it :param errors: Decoding errors: 'strict', 'ignore' or 'replace' :return: if printed is false, the lines are returned as a list """ data = [] with open(file_path, "rb") as f: for _ in range(lines): try: if python_version >= (2, 7): data.append(next(f).decode(encoding, errors=errors)) else: data.append(next(f).decode(encoding)) except StopIteration: break if printed: print("".join(data)) else: return data
python
def head(file_path, lines=10, encoding="utf-8", printed=True, errors='strict'): """ Read the first N lines of a file, defaults to 10 :param file_path: Path to file to read :param lines: Number of lines to read in :param encoding: defaults to utf-8 to decode as, will fail on binary :param printed: Automatically print the lines instead of returning it :param errors: Decoding errors: 'strict', 'ignore' or 'replace' :return: if printed is false, the lines are returned as a list """ data = [] with open(file_path, "rb") as f: for _ in range(lines): try: if python_version >= (2, 7): data.append(next(f).decode(encoding, errors=errors)) else: data.append(next(f).decode(encoding)) except StopIteration: break if printed: print("".join(data)) else: return data
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Read the first N lines of a file, defaults to 10 :param file_path: Path to file to read :param lines: Number of lines to read in :param encoding: defaults to utf-8 to decode as, will fail on binary :param printed: Automatically print the lines instead of returning it :param errors: Decoding errors: 'strict', 'ignore' or 'replace' :return: if printed is false, the lines are returned as a list
[ "Read", "the", "first", "N", "lines", "of", "a", "file", "defaults", "to", "10" ]
train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/cli.py#L122-L147
cdgriffith/Reusables
reusables/cli.py
tail
def tail(file_path, lines=10, encoding="utf-8", printed=True, errors='strict'): """ A really silly way to get the last N lines, defaults to 10. :param file_path: Path to file to read :param lines: Number of lines to read in :param encoding: defaults to utf-8 to decode as, will fail on binary :param printed: Automatically print the lines instead of returning it :param errors: Decoding errors: 'strict', 'ignore' or 'replace' :return: if printed is false, the lines are returned as a list """ data = deque() with open(file_path, "rb") as f: for line in f: if python_version >= (2, 7): data.append(line.decode(encoding, errors=errors)) else: data.append(line.decode(encoding)) if len(data) > lines: data.popleft() if printed: print("".join(data)) else: return data
python
def tail(file_path, lines=10, encoding="utf-8", printed=True, errors='strict'): """ A really silly way to get the last N lines, defaults to 10. :param file_path: Path to file to read :param lines: Number of lines to read in :param encoding: defaults to utf-8 to decode as, will fail on binary :param printed: Automatically print the lines instead of returning it :param errors: Decoding errors: 'strict', 'ignore' or 'replace' :return: if printed is false, the lines are returned as a list """ data = deque() with open(file_path, "rb") as f: for line in f: if python_version >= (2, 7): data.append(line.decode(encoding, errors=errors)) else: data.append(line.decode(encoding)) if len(data) > lines: data.popleft() if printed: print("".join(data)) else: return data
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A really silly way to get the last N lines, defaults to 10. :param file_path: Path to file to read :param lines: Number of lines to read in :param encoding: defaults to utf-8 to decode as, will fail on binary :param printed: Automatically print the lines instead of returning it :param errors: Decoding errors: 'strict', 'ignore' or 'replace' :return: if printed is false, the lines are returned as a list
[ "A", "really", "silly", "way", "to", "get", "the", "last", "N", "lines", "defaults", "to", "10", "." ]
train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/cli.py#L175-L201
cdgriffith/Reusables
reusables/cli.py
cp
def cp(src, dst, overwrite=False): """ Copy files to a new location. :param src: list (or string) of paths of files to copy :param dst: file or folder to copy item(s) to :param overwrite: IF the file already exists, should I overwrite it? """ if not isinstance(src, list): src = [src] dst = os.path.expanduser(dst) dst_folder = os.path.isdir(dst) if len(src) > 1 and not dst_folder: raise OSError("Cannot copy multiple item to same file") for item in src: source = os.path.expanduser(item) destination = (dst if not dst_folder else os.path.join(dst, os.path.basename(source))) if not overwrite and os.path.exists(destination): _logger.warning("Not replacing {0} with {1}, overwrite not enabled" "".format(destination, source)) continue shutil.copy(source, destination)
python
def cp(src, dst, overwrite=False): """ Copy files to a new location. :param src: list (or string) of paths of files to copy :param dst: file or folder to copy item(s) to :param overwrite: IF the file already exists, should I overwrite it? """ if not isinstance(src, list): src = [src] dst = os.path.expanduser(dst) dst_folder = os.path.isdir(dst) if len(src) > 1 and not dst_folder: raise OSError("Cannot copy multiple item to same file") for item in src: source = os.path.expanduser(item) destination = (dst if not dst_folder else os.path.join(dst, os.path.basename(source))) if not overwrite and os.path.exists(destination): _logger.warning("Not replacing {0} with {1}, overwrite not enabled" "".format(destination, source)) continue shutil.copy(source, destination)
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Copy files to a new location. :param src: list (or string) of paths of files to copy :param dst: file or folder to copy item(s) to :param overwrite: IF the file already exists, should I overwrite it?
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/cli.py#L204-L231
cdgriffith/Reusables
reusables/string_manipulation.py
cut
def cut(string, characters=2, trailing="normal"): """ Split a string into a list of N characters each. .. code:: python reusables.cut("abcdefghi") # ['ab', 'cd', 'ef', 'gh', 'i'] trailing gives you the following options: * normal: leaves remaining characters in their own last position * remove: return the list without the remainder characters * combine: add the remainder characters to the previous set * error: raise an IndexError if there are remaining characters .. code:: python reusables.cut("abcdefghi", 2, "error") # Traceback (most recent call last): # ... # IndexError: String of length 9 not divisible by 2 to splice reusables.cut("abcdefghi", 2, "remove") # ['ab', 'cd', 'ef', 'gh'] reusables.cut("abcdefghi", 2, "combine") # ['ab', 'cd', 'ef', 'ghi'] :param string: string to modify :param characters: how many characters to split it into :param trailing: "normal", "remove", "combine", or "error" :return: list of the cut string """ split_str = [string[i:i + characters] for i in range(0, len(string), characters)] if trailing != "normal" and len(split_str[-1]) != characters: if trailing.lower() == "remove": return split_str[:-1] if trailing.lower() == "combine" and len(split_str) >= 2: return split_str[:-2] + [split_str[-2] + split_str[-1]] if trailing.lower() == "error": raise IndexError("String of length {0} not divisible by {1} to" " cut".format(len(string), characters)) return split_str
python
def cut(string, characters=2, trailing="normal"): """ Split a string into a list of N characters each. .. code:: python reusables.cut("abcdefghi") # ['ab', 'cd', 'ef', 'gh', 'i'] trailing gives you the following options: * normal: leaves remaining characters in their own last position * remove: return the list without the remainder characters * combine: add the remainder characters to the previous set * error: raise an IndexError if there are remaining characters .. code:: python reusables.cut("abcdefghi", 2, "error") # Traceback (most recent call last): # ... # IndexError: String of length 9 not divisible by 2 to splice reusables.cut("abcdefghi", 2, "remove") # ['ab', 'cd', 'ef', 'gh'] reusables.cut("abcdefghi", 2, "combine") # ['ab', 'cd', 'ef', 'ghi'] :param string: string to modify :param characters: how many characters to split it into :param trailing: "normal", "remove", "combine", or "error" :return: list of the cut string """ split_str = [string[i:i + characters] for i in range(0, len(string), characters)] if trailing != "normal" and len(split_str[-1]) != characters: if trailing.lower() == "remove": return split_str[:-1] if trailing.lower() == "combine" and len(split_str) >= 2: return split_str[:-2] + [split_str[-2] + split_str[-1]] if trailing.lower() == "error": raise IndexError("String of length {0} not divisible by {1} to" " cut".format(len(string), characters)) return split_str
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Split a string into a list of N characters each. .. code:: python reusables.cut("abcdefghi") # ['ab', 'cd', 'ef', 'gh', 'i'] trailing gives you the following options: * normal: leaves remaining characters in their own last position * remove: return the list without the remainder characters * combine: add the remainder characters to the previous set * error: raise an IndexError if there are remaining characters .. code:: python reusables.cut("abcdefghi", 2, "error") # Traceback (most recent call last): # ... # IndexError: String of length 9 not divisible by 2 to splice reusables.cut("abcdefghi", 2, "remove") # ['ab', 'cd', 'ef', 'gh'] reusables.cut("abcdefghi", 2, "combine") # ['ab', 'cd', 'ef', 'ghi'] :param string: string to modify :param characters: how many characters to split it into :param trailing: "normal", "remove", "combine", or "error" :return: list of the cut string
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/string_manipulation.py#L24-L69
cdgriffith/Reusables
reusables/string_manipulation.py
int_to_roman
def int_to_roman(integer): """ Convert an integer into a string of roman numbers. .. code: python reusables.int_to_roman(445) # 'CDXLV' :param integer: :return: roman string """ if not isinstance(integer, int): raise ValueError("Input integer must be of type int") output = [] while integer > 0: for r, i in sorted(_roman_dict.items(), key=lambda x: x[1], reverse=True): while integer >= i: output.append(r) integer -= i return "".join(output)
python
def int_to_roman(integer): """ Convert an integer into a string of roman numbers. .. code: python reusables.int_to_roman(445) # 'CDXLV' :param integer: :return: roman string """ if not isinstance(integer, int): raise ValueError("Input integer must be of type int") output = [] while integer > 0: for r, i in sorted(_roman_dict.items(), key=lambda x: x[1], reverse=True): while integer >= i: output.append(r) integer -= i return "".join(output)
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Convert an integer into a string of roman numbers. .. code: python reusables.int_to_roman(445) # 'CDXLV' :param integer: :return: roman string
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/string_manipulation.py#L72-L94
cdgriffith/Reusables
reusables/string_manipulation.py
roman_to_int
def roman_to_int(roman_string): """ Converts a string of roman numbers into an integer. .. code: python reusables.roman_to_int("XXXVI") # 36 :param roman_string: XVI or similar :return: parsed integer """ roman_string = roman_string.upper().strip() if "IIII" in roman_string: raise ValueError("Malformed roman string") value = 0 skip_one = False last_number = None for i, letter in enumerate(roman_string): if letter not in _roman_dict: raise ValueError("Malformed roman string") if skip_one: skip_one = False continue if i < (len(roman_string) - 1): double_check = letter + roman_string[i + 1] if double_check in _roman_dict: if last_number and _roman_dict[double_check] > last_number: raise ValueError("Malformed roman string") last_number = _roman_dict[double_check] value += _roman_dict[double_check] skip_one = True continue if last_number and _roman_dict[letter] > last_number: raise ValueError("Malformed roman string") last_number = _roman_dict[letter] value += _roman_dict[letter] return value
python
def roman_to_int(roman_string): """ Converts a string of roman numbers into an integer. .. code: python reusables.roman_to_int("XXXVI") # 36 :param roman_string: XVI or similar :return: parsed integer """ roman_string = roman_string.upper().strip() if "IIII" in roman_string: raise ValueError("Malformed roman string") value = 0 skip_one = False last_number = None for i, letter in enumerate(roman_string): if letter not in _roman_dict: raise ValueError("Malformed roman string") if skip_one: skip_one = False continue if i < (len(roman_string) - 1): double_check = letter + roman_string[i + 1] if double_check in _roman_dict: if last_number and _roman_dict[double_check] > last_number: raise ValueError("Malformed roman string") last_number = _roman_dict[double_check] value += _roman_dict[double_check] skip_one = True continue if last_number and _roman_dict[letter] > last_number: raise ValueError("Malformed roman string") last_number = _roman_dict[letter] value += _roman_dict[letter] return value
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Converts a string of roman numbers into an integer. .. code: python reusables.roman_to_int("XXXVI") # 36 :param roman_string: XVI or similar :return: parsed integer
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/string_manipulation.py#L97-L135
cdgriffith/Reusables
reusables/string_manipulation.py
int_to_words
def int_to_words(number, european=False): """ Converts an integer or float to words. .. code: python reusables.int_to_number(445) # 'four hundred forty-five' reusables.int_to_number(1.45) # 'one and forty-five hundredths' :param number: String, integer, or float to convert to words. The decimal can only be up to three places long, and max number allowed is 999 decillion. :param european: If the string uses the european style formatting, i.e. decimal points instead of commas and commas instead of decimal points, set this parameter to True :return: The translated string """ def ones(n): return "" if n == 0 else _numbers[n] def tens(n): teen = int("{0}{1}".format(n[0], n[1])) if n[0] == 0: return ones(n[1]) if teen in _numbers: return _numbers[teen] else: ten = _numbers[int("{0}0".format(n[0]))] one = _numbers[n[1]] return "{0}-{1}".format(ten, one) def hundreds(n): if n[0] == 0: return tens(n[1:]) else: t = tens(n[1:]) return "{0} hundred {1}".format(_numbers[n[0]], "" if not t else t) def comma_separated(list_of_strings): if len(list_of_strings) > 1: return "{0} ".format("" if len(list_of_strings) == 2 else ",").join(list_of_strings) else: return list_of_strings[0] def while_loop(list_of_numbers, final_list): index = 0 group_set = int(len(list_of_numbers) / 3) while group_set != 0: value = hundreds(list_of_numbers[index:index + 3]) if value: final_list.append("{0} {1}".format(value, _places[group_set]) if _places[group_set] else value) group_set -= 1 index += 3 number_list = [] decimal_list = [] decimal = '' number = str(number) group_delimiter, point_delimiter = (",", ".") \ if not european else (".", ",") if point_delimiter in number: decimal = number.split(point_delimiter)[1] number = number.split(point_delimiter)[0].replace( group_delimiter, "") elif group_delimiter in number: number = number.replace(group_delimiter, "") if not number.isdigit(): raise ValueError("Number is not numeric") if decimal and not decimal.isdigit(): raise ValueError("Decimal is not numeric") if int(number) == 0: number_list.append("zero") r = len(number) % 3 d_r = len(decimal) % 3 number = number.zfill(len(number) + 3 - r if r else 0) f_decimal = decimal.zfill(len(decimal) + 3 - d_r if d_r else 0) d = [int(x) for x in f_decimal] n = [int(x) for x in number] while_loop(n, number_list) if decimal and int(decimal) != 0: while_loop(d, decimal_list) if decimal_list: name = '' if len(decimal) % 3 == 1: name = 'ten' elif len(decimal) % 3 == 2: name = 'hundred' place = int((str(len(decimal) / 3).split(".")[0])) number_list.append("and {0} {1}{2}{3}ths".format( comma_separated(decimal_list), name, "-" if name and _places[place+1] else "", _places[place+1])) return comma_separated(number_list)
python
def int_to_words(number, european=False): """ Converts an integer or float to words. .. code: python reusables.int_to_number(445) # 'four hundred forty-five' reusables.int_to_number(1.45) # 'one and forty-five hundredths' :param number: String, integer, or float to convert to words. The decimal can only be up to three places long, and max number allowed is 999 decillion. :param european: If the string uses the european style formatting, i.e. decimal points instead of commas and commas instead of decimal points, set this parameter to True :return: The translated string """ def ones(n): return "" if n == 0 else _numbers[n] def tens(n): teen = int("{0}{1}".format(n[0], n[1])) if n[0] == 0: return ones(n[1]) if teen in _numbers: return _numbers[teen] else: ten = _numbers[int("{0}0".format(n[0]))] one = _numbers[n[1]] return "{0}-{1}".format(ten, one) def hundreds(n): if n[0] == 0: return tens(n[1:]) else: t = tens(n[1:]) return "{0} hundred {1}".format(_numbers[n[0]], "" if not t else t) def comma_separated(list_of_strings): if len(list_of_strings) > 1: return "{0} ".format("" if len(list_of_strings) == 2 else ",").join(list_of_strings) else: return list_of_strings[0] def while_loop(list_of_numbers, final_list): index = 0 group_set = int(len(list_of_numbers) / 3) while group_set != 0: value = hundreds(list_of_numbers[index:index + 3]) if value: final_list.append("{0} {1}".format(value, _places[group_set]) if _places[group_set] else value) group_set -= 1 index += 3 number_list = [] decimal_list = [] decimal = '' number = str(number) group_delimiter, point_delimiter = (",", ".") \ if not european else (".", ",") if point_delimiter in number: decimal = number.split(point_delimiter)[1] number = number.split(point_delimiter)[0].replace( group_delimiter, "") elif group_delimiter in number: number = number.replace(group_delimiter, "") if not number.isdigit(): raise ValueError("Number is not numeric") if decimal and not decimal.isdigit(): raise ValueError("Decimal is not numeric") if int(number) == 0: number_list.append("zero") r = len(number) % 3 d_r = len(decimal) % 3 number = number.zfill(len(number) + 3 - r if r else 0) f_decimal = decimal.zfill(len(decimal) + 3 - d_r if d_r else 0) d = [int(x) for x in f_decimal] n = [int(x) for x in number] while_loop(n, number_list) if decimal and int(decimal) != 0: while_loop(d, decimal_list) if decimal_list: name = '' if len(decimal) % 3 == 1: name = 'ten' elif len(decimal) % 3 == 2: name = 'hundred' place = int((str(len(decimal) / 3).split(".")[0])) number_list.append("and {0} {1}{2}{3}ths".format( comma_separated(decimal_list), name, "-" if name and _places[place+1] else "", _places[place+1])) return comma_separated(number_list)
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Converts an integer or float to words. .. code: python reusables.int_to_number(445) # 'four hundred forty-five' reusables.int_to_number(1.45) # 'one and forty-five hundredths' :param number: String, integer, or float to convert to words. The decimal can only be up to three places long, and max number allowed is 999 decillion. :param european: If the string uses the european style formatting, i.e. decimal points instead of commas and commas instead of decimal points, set this parameter to True :return: The translated string
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train
https://github.com/cdgriffith/Reusables/blob/bc32f72e4baee7d76a6d58b88fcb23dd635155cd/reusables/string_manipulation.py#L138-L247
aicenter/roadmap-processing
roadmaptools/osmfilter.py
filter_osm_file
def filter_osm_file(): """ Downloads (and compiles) osmfilter tool from web and calls that osmfilter to only filter out only the road elements. """ print_info('Filtering OSM file...') start_time = time.time() if check_osmfilter(): # params = '--keep="highway=motorway =motorway_link =trunk =trunk_link =primary =primary_link =secondary' \ # ' =secondary_link =tertiary =tertiary_link =unclassified =unclassified_link =residential =residential_link' \ # ' =living_street" --drop="access=no"' params = config.osm_filter_params command = './osmfilter' if platform.system() == 'Linux' else 'osmfilter.exe' if platform.system() == 'Linux': filter_command = '%s "%s" %s | pv > "%s"' % (command, config.osm_map_filename, params, config.filtered_osm_filename) else: filter_command = '%s "%s" %s > "%s"' % ( command, config.osm_map_filename, params, config.filtered_osm_filename) os.system(filter_command) else: print_info('Osmfilter not available. Exiting.') exit(1) print_info('Filtering finished. (%.2f secs)' % (time.time() - start_time))
python
def filter_osm_file(): """ Downloads (and compiles) osmfilter tool from web and calls that osmfilter to only filter out only the road elements. """ print_info('Filtering OSM file...') start_time = time.time() if check_osmfilter(): # params = '--keep="highway=motorway =motorway_link =trunk =trunk_link =primary =primary_link =secondary' \ # ' =secondary_link =tertiary =tertiary_link =unclassified =unclassified_link =residential =residential_link' \ # ' =living_street" --drop="access=no"' params = config.osm_filter_params command = './osmfilter' if platform.system() == 'Linux' else 'osmfilter.exe' if platform.system() == 'Linux': filter_command = '%s "%s" %s | pv > "%s"' % (command, config.osm_map_filename, params, config.filtered_osm_filename) else: filter_command = '%s "%s" %s > "%s"' % ( command, config.osm_map_filename, params, config.filtered_osm_filename) os.system(filter_command) else: print_info('Osmfilter not available. Exiting.') exit(1) print_info('Filtering finished. (%.2f secs)' % (time.time() - start_time))
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Downloads (and compiles) osmfilter tool from web and calls that osmfilter to only filter out only the road elements.
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train
https://github.com/aicenter/roadmap-processing/blob/d9fb6e0b3bc1f11302a9e2ac62ee6db9484e2018/roadmaptools/osmfilter.py#L10-L37
Koed00/django-rq-jobs
django_rq_jobs/models.py
task_list
def task_list(): """ Scans the modules set in RQ_JOBS_MODULES for RQ jobs decorated with @task Compiles a readable list for Job model task choices """ try: jobs_module = settings.RQ_JOBS_MODULE except AttributeError: raise ImproperlyConfigured(_("You have to define RQ_JOBS_MODULE in settings.py")) if isinstance(jobs_module, string_types): jobs_modules = (jobs_module,) elif isinstance(jobs_module, (tuple, list)): jobs_modules = jobs_module else: raise ImproperlyConfigured(_("RQ_JOBS_MODULE must be a string or a tuple")) choices = [] for module in jobs_modules: try: tasks = importlib.import_module(module) except ImportError: raise ImproperlyConfigured(_("Can not find module {}").format(module)) module_choices = [('%s.%s' % (module, x), underscore_to_camelcase(x)) for x, y in list(tasks.__dict__.items()) if type(y) == FunctionType and hasattr(y, 'delay')] choices.extend(module_choices) choices.sort(key=lambda tup: tup[1]) return choices
python
def task_list(): """ Scans the modules set in RQ_JOBS_MODULES for RQ jobs decorated with @task Compiles a readable list for Job model task choices """ try: jobs_module = settings.RQ_JOBS_MODULE except AttributeError: raise ImproperlyConfigured(_("You have to define RQ_JOBS_MODULE in settings.py")) if isinstance(jobs_module, string_types): jobs_modules = (jobs_module,) elif isinstance(jobs_module, (tuple, list)): jobs_modules = jobs_module else: raise ImproperlyConfigured(_("RQ_JOBS_MODULE must be a string or a tuple")) choices = [] for module in jobs_modules: try: tasks = importlib.import_module(module) except ImportError: raise ImproperlyConfigured(_("Can not find module {}").format(module)) module_choices = [('%s.%s' % (module, x), underscore_to_camelcase(x)) for x, y in list(tasks.__dict__.items()) if type(y) == FunctionType and hasattr(y, 'delay')] choices.extend(module_choices) choices.sort(key=lambda tup: tup[1]) return choices
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Scans the modules set in RQ_JOBS_MODULES for RQ jobs decorated with @task Compiles a readable list for Job model task choices
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train
https://github.com/Koed00/django-rq-jobs/blob/b25ffd15c91858406494ae0c29babf00c268db18/django_rq_jobs/models.py#L33-L65
Koed00/django-rq-jobs
django_rq_jobs/models.py
Job.rq_job
def rq_job(self): """The last RQ Job this ran on""" if not self.rq_id or not self.rq_origin: return try: return RQJob.fetch(self.rq_id, connection=get_connection(self.rq_origin)) except NoSuchJobError: return
python
def rq_job(self): """The last RQ Job this ran on""" if not self.rq_id or not self.rq_origin: return try: return RQJob.fetch(self.rq_id, connection=get_connection(self.rq_origin)) except NoSuchJobError: return
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The last RQ Job this ran on
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train
https://github.com/Koed00/django-rq-jobs/blob/b25ffd15c91858406494ae0c29babf00c268db18/django_rq_jobs/models.py#L95-L102
Koed00/django-rq-jobs
django_rq_jobs/models.py
Job.rq_link
def rq_link(self): """Link to Django-RQ status page for this job""" if self.rq_job: url = reverse('rq_job_detail', kwargs={'job_id': self.rq_id, 'queue_index': queue_index_by_name(self.rq_origin)}) return '<a href="{}">{}</a>'.format(url, self.rq_id)
python
def rq_link(self): """Link to Django-RQ status page for this job""" if self.rq_job: url = reverse('rq_job_detail', kwargs={'job_id': self.rq_id, 'queue_index': queue_index_by_name(self.rq_origin)}) return '<a href="{}">{}</a>'.format(url, self.rq_id)
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Link to Django-RQ status page for this job
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train
https://github.com/Koed00/django-rq-jobs/blob/b25ffd15c91858406494ae0c29babf00c268db18/django_rq_jobs/models.py#L109-L114
Koed00/django-rq-jobs
django_rq_jobs/models.py
Job.rq_task
def rq_task(self): """ The function to call for this task. Config errors are caught by tasks_list() already. """ task_path = self.task.split('.') module_name = '.'.join(task_path[:-1]) task_name = task_path[-1] module = importlib.import_module(module_name) return getattr(module, task_name)
python
def rq_task(self): """ The function to call for this task. Config errors are caught by tasks_list() already. """ task_path = self.task.split('.') module_name = '.'.join(task_path[:-1]) task_name = task_path[-1] module = importlib.import_module(module_name) return getattr(module, task_name)
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The function to call for this task. Config errors are caught by tasks_list() already.
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train
https://github.com/Koed00/django-rq-jobs/blob/b25ffd15c91858406494ae0c29babf00c268db18/django_rq_jobs/models.py#L117-L127
Koed00/django-rq-jobs
django_rq_jobs/management/commands/rqjobs.py
fix_module
def fix_module(job): """ Fix for tasks without a module. Provides backwards compatibility with < 0.1.5 """ modules = settings.RQ_JOBS_MODULE if not type(modules) == tuple: modules = [modules] for module in modules: try: module_match = importlib.import_module(module) if hasattr(module_match, job.task): job.task = '{}.{}'.format(module, job.task) break except ImportError: continue return job
python
def fix_module(job): """ Fix for tasks without a module. Provides backwards compatibility with < 0.1.5 """ modules = settings.RQ_JOBS_MODULE if not type(modules) == tuple: modules = [modules] for module in modules: try: module_match = importlib.import_module(module) if hasattr(module_match, job.task): job.task = '{}.{}'.format(module, job.task) break except ImportError: continue return job
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Fix for tasks without a module. Provides backwards compatibility with < 0.1.5
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train
https://github.com/Koed00/django-rq-jobs/blob/b25ffd15c91858406494ae0c29babf00c268db18/django_rq_jobs/management/commands/rqjobs.py#L59-L74
Python-Tools/aioorm
aioorm/database.py
drop_model_tables
async def drop_model_tables(models, **drop_table_kwargs): """Drop tables for all given models (in the right order).""" for m in reversed(sort_models_topologically(models)): await m.drop_table(**drop_table_kwargs)
python
async def drop_model_tables(models, **drop_table_kwargs): """Drop tables for all given models (in the right order).""" for m in reversed(sort_models_topologically(models)): await m.drop_table(**drop_table_kwargs)
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Drop tables for all given models (in the right order).
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train
https://github.com/Python-Tools/aioorm/blob/f305e253ce748cda91b8bc9ec9c6b56e0e7681f7/aioorm/database.py#L244-L247
Python-Tools/aioorm
aioorm/shortcuts.py
model_to_dict
async def model_to_dict(model, recurse=True, backrefs=False, only=None, exclude=None, seen=None, extra_attrs=None, fields_from_query=None, max_depth=None): """ Convert a model instance (and any related objects) to a dictionary. :param bool recurse: Whether foreign-keys should be recursed. :param bool backrefs: Whether lists of related objects should be recursed. :param only: A list (or set) of field instances indicating which fields should be included. :param exclude: A list (or set) of field instances that should be excluded from the dictionary. :param list extra_attrs: Names of model instance attributes or methods that should be included. :param SelectQuery fields_from_query: Query that was source of model. Take fields explicitly selected by the query and serialize them. :param int max_depth: Maximum depth to recurse, value <= 0 means no max. """ max_depth = -1 if max_depth is None else max_depth if max_depth == 0: recurse = False only = _clone_set(only) extra_attrs = _clone_set(extra_attrs) if fields_from_query is not None: for item in fields_from_query._select: if isinstance(item, Field): only.add(item) elif isinstance(item, Node) and item._alias: extra_attrs.add(item._alias) data = {} exclude = _clone_set(exclude) seen = _clone_set(seen) exclude |= seen model_class = type(model) for field in model._meta.declared_fields: if field in exclude or (only and (field not in only)): continue field_data = model._data.get(field.name) if isinstance(field, ForeignKeyField) and recurse: if field_data: seen.add(field) rel_obj = getattr(model, field.name) if iscoroutine(rel_obj): rel_obj = await rel_obj field_data = await model_to_dict( rel_obj, recurse=recurse, backrefs=backrefs, only=only, exclude=exclude, seen=seen, max_depth=max_depth - 1) else: field_data = None data[field.name] = field_data if extra_attrs: for attr_name in extra_attrs: attr = getattr(model, attr_name) if callable(attr): data[attr_name] = attr() else: data[attr_name] = attr if backrefs and recurse: for related_name, foreign_key in model._meta.reverse_rel.items(): descriptor = getattr(model_class, related_name) if descriptor in exclude or foreign_key in exclude: continue if only and (descriptor not in only) and (foreign_key not in only): continue accum = [] exclude.add(foreign_key) related_query = getattr( model, related_name + '_prefetch', getattr(model, related_name)) async for rel_obj in related_query: accum.append(await model_to_dict( rel_obj, recurse=recurse, backrefs=backrefs, only=only, exclude=exclude, max_depth=max_depth - 1)) data[related_name] = accum return data
python
async def model_to_dict(model, recurse=True, backrefs=False, only=None, exclude=None, seen=None, extra_attrs=None, fields_from_query=None, max_depth=None): """ Convert a model instance (and any related objects) to a dictionary. :param bool recurse: Whether foreign-keys should be recursed. :param bool backrefs: Whether lists of related objects should be recursed. :param only: A list (or set) of field instances indicating which fields should be included. :param exclude: A list (or set) of field instances that should be excluded from the dictionary. :param list extra_attrs: Names of model instance attributes or methods that should be included. :param SelectQuery fields_from_query: Query that was source of model. Take fields explicitly selected by the query and serialize them. :param int max_depth: Maximum depth to recurse, value <= 0 means no max. """ max_depth = -1 if max_depth is None else max_depth if max_depth == 0: recurse = False only = _clone_set(only) extra_attrs = _clone_set(extra_attrs) if fields_from_query is not None: for item in fields_from_query._select: if isinstance(item, Field): only.add(item) elif isinstance(item, Node) and item._alias: extra_attrs.add(item._alias) data = {} exclude = _clone_set(exclude) seen = _clone_set(seen) exclude |= seen model_class = type(model) for field in model._meta.declared_fields: if field in exclude or (only and (field not in only)): continue field_data = model._data.get(field.name) if isinstance(field, ForeignKeyField) and recurse: if field_data: seen.add(field) rel_obj = getattr(model, field.name) if iscoroutine(rel_obj): rel_obj = await rel_obj field_data = await model_to_dict( rel_obj, recurse=recurse, backrefs=backrefs, only=only, exclude=exclude, seen=seen, max_depth=max_depth - 1) else: field_data = None data[field.name] = field_data if extra_attrs: for attr_name in extra_attrs: attr = getattr(model, attr_name) if callable(attr): data[attr_name] = attr() else: data[attr_name] = attr if backrefs and recurse: for related_name, foreign_key in model._meta.reverse_rel.items(): descriptor = getattr(model_class, related_name) if descriptor in exclude or foreign_key in exclude: continue if only and (descriptor not in only) and (foreign_key not in only): continue accum = [] exclude.add(foreign_key) related_query = getattr( model, related_name + '_prefetch', getattr(model, related_name)) async for rel_obj in related_query: accum.append(await model_to_dict( rel_obj, recurse=recurse, backrefs=backrefs, only=only, exclude=exclude, max_depth=max_depth - 1)) data[related_name] = accum return data
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train
https://github.com/Python-Tools/aioorm/blob/f305e253ce748cda91b8bc9ec9c6b56e0e7681f7/aioorm/shortcuts.py#L6-L101
Python-Tools/aioorm
aioorm/utils/csv_utils/csv_loader.py
RowConverter.extract_rows
async def extract_rows(self, file_or_name, **reader_kwargs): """ Extract `self.sample_size` rows from the CSV file and analyze their data-types. :param str file_or_name: A string filename or a file handle. :param reader_kwargs: Arbitrary parameters to pass to the CSV reader. :returns: A 2-tuple containing a list of headers and list of rows read from the CSV file. """ rows = [] rows_to_read = self.sample_size async with self.get_reader(file_or_name, **reader_kwargs) as reader: if self.has_header: rows_to_read += 1 for i in range(self.sample_size): try: row = await reader.__anext__() except AttributeError as te: row = next(reader) except: raise rows.append(row) if self.has_header: header, rows = rows[0], rows[1:] else: header = ['field_%d' % i for i in range(len(rows[0]))] return header, rows
python
async def extract_rows(self, file_or_name, **reader_kwargs): """ Extract `self.sample_size` rows from the CSV file and analyze their data-types. :param str file_or_name: A string filename or a file handle. :param reader_kwargs: Arbitrary parameters to pass to the CSV reader. :returns: A 2-tuple containing a list of headers and list of rows read from the CSV file. """ rows = [] rows_to_read = self.sample_size async with self.get_reader(file_or_name, **reader_kwargs) as reader: if self.has_header: rows_to_read += 1 for i in range(self.sample_size): try: row = await reader.__anext__() except AttributeError as te: row = next(reader) except: raise rows.append(row) if self.has_header: header, rows = rows[0], rows[1:] else: header = ['field_%d' % i for i in range(len(rows[0]))] return header, rows
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train
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Python-Tools/aioorm
aioorm/utils/csv_utils/csv_loader.py
RowConverter.get_checks
def get_checks(self): """Return a list of functions to use when testing values.""" return [ self.is_date, self.is_datetime, self.is_integer, self.is_float, self.default]
python
def get_checks(self): """Return a list of functions to use when testing values.""" return [ self.is_date, self.is_datetime, self.is_integer, self.is_float, self.default]
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Return a list of functions to use when testing values.
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train
https://github.com/Python-Tools/aioorm/blob/f305e253ce748cda91b8bc9ec9c6b56e0e7681f7/aioorm/utils/csv_utils/csv_loader.py#L152-L159
Python-Tools/aioorm
aioorm/utils/csv_utils/csv_loader.py
RowConverter.analyze
def analyze(self, rows): """ Analyze the given rows and try to determine the type of value stored. :param list rows: A list-of-lists containing one or more rows from a csv file. :returns: A list of peewee Field objects for each column in the CSV. """ transposed = zip(*rows) checks = self.get_checks() column_types = [] for i, column in enumerate(transposed): # Remove any empty values. col_vals = [val for val in column if val != ''] for check in checks: results = set(check(val) for val in col_vals) if all(results): column_types.append(check.field()) break return column_types
python
def analyze(self, rows): """ Analyze the given rows and try to determine the type of value stored. :param list rows: A list-of-lists containing one or more rows from a csv file. :returns: A list of peewee Field objects for each column in the CSV. """ transposed = zip(*rows) checks = self.get_checks() column_types = [] for i, column in enumerate(transposed): # Remove any empty values. col_vals = [val for val in column if val != ''] for check in checks: results = set(check(val) for val in col_vals) if all(results): column_types.append(check.field()) break return column_types
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Analyze the given rows and try to determine the type of value stored. :param list rows: A list-of-lists containing one or more rows from a csv file. :returns: A list of peewee Field objects for each column in the CSV.
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train
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BetterWorks/django-bleachfields
bleachfields/bleachfield.py
BleachField.clean_text
def clean_text(self, text): '''Clean text using bleach.''' if text is None: return '' text = re.sub(ILLEGAL_CHARACTERS_RE, '', text) if '<' in text or '&lt' in text: text = clean(text, tags=self.tags, strip=self.strip) return unescape(text)
python
def clean_text(self, text): '''Clean text using bleach.''' if text is None: return '' text = re.sub(ILLEGAL_CHARACTERS_RE, '', text) if '<' in text or '&lt' in text: text = clean(text, tags=self.tags, strip=self.strip) return unescape(text)
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Clean text using bleach.
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train
https://github.com/BetterWorks/django-bleachfields/blob/6b49aad6daa8c1357af31a2f7941352561d04cd6/bleachfields/bleachfield.py#L26-L34
nwilming/ocupy
ocupy/loader.py
LoadFromDisk.path
def path(self, category = None, image = None, feature = None): """ Constructs the path to categories, images and features. This path function assumes that the following storage scheme is used on the hard disk to access categories, images and features: - categories: /impath/category - images: /impath/category/category_image.png - features: /ftrpath/category/feature/category_image.mat The path function is called to query the location of categories, images and features before they are loaded. Thus, if your features are organized in a different way, you can simply replace this method such that it returns appropriate paths' and the LoadFromDisk loader will use your naming scheme. """ filename = None if not category is None: filename = join(self.impath, str(category)) if not image is None: assert not category is None, "The category has to be given if the image is given" filename = join(filename, '%s_%s.png' % (str(category), str(image))) if not feature is None: assert category != None and image != None, "If a feature name is given the category and image also have to be given." filename = join(self.ftrpath, str(category), feature, '%s_%s.mat' % (str(category), str(image))) return filename
python
def path(self, category = None, image = None, feature = None): """ Constructs the path to categories, images and features. This path function assumes that the following storage scheme is used on the hard disk to access categories, images and features: - categories: /impath/category - images: /impath/category/category_image.png - features: /ftrpath/category/feature/category_image.mat The path function is called to query the location of categories, images and features before they are loaded. Thus, if your features are organized in a different way, you can simply replace this method such that it returns appropriate paths' and the LoadFromDisk loader will use your naming scheme. """ filename = None if not category is None: filename = join(self.impath, str(category)) if not image is None: assert not category is None, "The category has to be given if the image is given" filename = join(filename, '%s_%s.png' % (str(category), str(image))) if not feature is None: assert category != None and image != None, "If a feature name is given the category and image also have to be given." filename = join(self.ftrpath, str(category), feature, '%s_%s.mat' % (str(category), str(image))) return filename
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/loader.py#L168-L195
nwilming/ocupy
ocupy/loader.py
LoadFromDisk.get_image
def get_image(self, cat, img): """ Loads an image from disk. """ filename = self.path(cat, img) data = [] if filename.endswith('mat'): data = loadmat(filename)['output'] else: data = imread(filename) if self.size is not None: return imresize(data, self.size) else: return data
python
def get_image(self, cat, img): """ Loads an image from disk. """ filename = self.path(cat, img) data = [] if filename.endswith('mat'): data = loadmat(filename)['output'] else: data = imread(filename) if self.size is not None: return imresize(data, self.size) else: return data
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train
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nwilming/ocupy
ocupy/loader.py
LoadFromDisk.get_feature
def get_feature(self, cat, img, feature): """ Load a feature from disk. """ filename = self.path(cat, img, feature) data = loadmat(filename) name = [k for k in list(data.keys()) if not k.startswith('__')] if self.size is not None: return imresize(data[name.pop()], self.size) return data[name.pop()]
python
def get_feature(self, cat, img, feature): """ Load a feature from disk. """ filename = self.path(cat, img, feature) data = loadmat(filename) name = [k for k in list(data.keys()) if not k.startswith('__')] if self.size is not None: return imresize(data[name.pop()], self.size) return data[name.pop()]
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train
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nwilming/ocupy
ocupy/loader.py
SaveToDisk.save_image
def save_image(self, cat, img, data): """Saves a new image.""" filename = self.path(cat, img) mkdir(filename) if type(data) == np.ndarray: data = Image.fromarray(data).convert('RGB') data.save(filename)
python
def save_image(self, cat, img, data): """Saves a new image.""" filename = self.path(cat, img) mkdir(filename) if type(data) == np.ndarray: data = Image.fromarray(data).convert('RGB') data.save(filename)
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train
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nwilming/ocupy
ocupy/loader.py
SaveToDisk.save_feature
def save_feature(self, cat, img, feature, data): """Saves a new feature.""" filename = self.path(cat, img, feature) mkdir(filename) savemat(filename, {'output':data})
python
def save_feature(self, cat, img, feature, data): """Saves a new feature.""" filename = self.path(cat, img, feature) mkdir(filename) savemat(filename, {'output':data})
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/loader.py#L251-L255
nwilming/ocupy
ocupy/datamat_tools.py
factorise_field
def factorise_field(dm, field_name, boundary_char = None, parameter_name=None): """This removes a common beginning from the data of the fields, placing the common element in a parameter and the different endings in the fields. if parameter_name is None, then it will be <field_name>_common. So far, it's probably only useful for the file_name. TODO: remove field entirely if no unique elements exist. """ old_data = dm.field(field_name) if isinstance(old_data[0], str) or isinstance(old_data[0], str): (new_data, common) = factorise_strings(old_data, boundary_char) new_data = array(new_data) else: raise NotImplementedError('factorising of fields not implemented for anything but string/unicode objects') if len(common) > 0: dm.__dict__[field_name] = new_data if parameter_name is None: parameter_name = field_name + '_common' dm.add_parameter(parameter_name, common)
python
def factorise_field(dm, field_name, boundary_char = None, parameter_name=None): """This removes a common beginning from the data of the fields, placing the common element in a parameter and the different endings in the fields. if parameter_name is None, then it will be <field_name>_common. So far, it's probably only useful for the file_name. TODO: remove field entirely if no unique elements exist. """ old_data = dm.field(field_name) if isinstance(old_data[0], str) or isinstance(old_data[0], str): (new_data, common) = factorise_strings(old_data, boundary_char) new_data = array(new_data) else: raise NotImplementedError('factorising of fields not implemented for anything but string/unicode objects') if len(common) > 0: dm.__dict__[field_name] = new_data if parameter_name is None: parameter_name = field_name + '_common' dm.add_parameter(parameter_name, common)
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This removes a common beginning from the data of the fields, placing the common element in a parameter and the different endings in the fields. if parameter_name is None, then it will be <field_name>_common. So far, it's probably only useful for the file_name. TODO: remove field entirely if no unique elements exist.
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat_tools.py#L11-L34
nwilming/ocupy
ocupy/utils.py
randsample
def randsample(vec, nr_samples, with_replacement = False): """ Draws nr_samples random samples from vec. """ if not with_replacement: return np.random.permutation(vec)[0:nr_samples] else: return np.asarray(vec)[np.random.randint(0, len(vec), nr_samples)]
python
def randsample(vec, nr_samples, with_replacement = False): """ Draws nr_samples random samples from vec. """ if not with_replacement: return np.random.permutation(vec)[0:nr_samples] else: return np.asarray(vec)[np.random.randint(0, len(vec), nr_samples)]
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Draws nr_samples random samples from vec.
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/utils.py#L63-L70
nwilming/ocupy
ocupy/utils.py
calc_resize_factor
def calc_resize_factor(prediction, image_size): """ Calculates how much prediction.shape and image_size differ. """ resize_factor_x = prediction.shape[1] / float(image_size[1]) resize_factor_y = prediction.shape[0] / float(image_size[0]) if abs(resize_factor_x - resize_factor_y) > 1.0/image_size[1] : raise RuntimeError("""The aspect ratio of the fixations does not match with the prediction: %f vs. %f""" %(resize_factor_y, resize_factor_x)) return (resize_factor_y, resize_factor_x)
python
def calc_resize_factor(prediction, image_size): """ Calculates how much prediction.shape and image_size differ. """ resize_factor_x = prediction.shape[1] / float(image_size[1]) resize_factor_y = prediction.shape[0] / float(image_size[0]) if abs(resize_factor_x - resize_factor_y) > 1.0/image_size[1] : raise RuntimeError("""The aspect ratio of the fixations does not match with the prediction: %f vs. %f""" %(resize_factor_y, resize_factor_x)) return (resize_factor_y, resize_factor_x)
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Calculates how much prediction.shape and image_size differ.
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/utils.py#L78-L88
nwilming/ocupy
ocupy/utils.py
dict_2_mat
def dict_2_mat(data, fill = True): """ Creates a NumPy array from a dictionary with only integers as keys and NumPy arrays as values. Dimension 0 of the resulting array is formed from data.keys(). Missing values in keys can be filled up with np.nan (default) or ignored. Parameters ---------- data : dict a dictionary with integers as keys and array-likes of the same shape as values fill : boolean flag specifying if the resulting matrix will keep a correspondence between dictionary keys and matrix indices by filling up missing keys with matrices of NaNs. Defaults to True Returns ------- numpy array with one more dimension than the values of the input dict """ if any([type(k) != int for k in list(data.keys())]): raise RuntimeError("Dictionary cannot be converted to matrix, " + "not all keys are ints") base_shape = np.array(list(data.values())[0]).shape result_shape = list(base_shape) if fill: result_shape.insert(0, max(data.keys()) + 1) else: result_shape.insert(0, len(list(data.keys()))) result = np.empty(result_shape) + np.nan for (i, (k, v)) in enumerate(data.items()): v = np.array(v) if v.shape != base_shape: raise RuntimeError("Dictionary cannot be converted to matrix, " + "not all values have same dimensions") result[fill and [k][0] or [i][0]] = v return result
python
def dict_2_mat(data, fill = True): """ Creates a NumPy array from a dictionary with only integers as keys and NumPy arrays as values. Dimension 0 of the resulting array is formed from data.keys(). Missing values in keys can be filled up with np.nan (default) or ignored. Parameters ---------- data : dict a dictionary with integers as keys and array-likes of the same shape as values fill : boolean flag specifying if the resulting matrix will keep a correspondence between dictionary keys and matrix indices by filling up missing keys with matrices of NaNs. Defaults to True Returns ------- numpy array with one more dimension than the values of the input dict """ if any([type(k) != int for k in list(data.keys())]): raise RuntimeError("Dictionary cannot be converted to matrix, " + "not all keys are ints") base_shape = np.array(list(data.values())[0]).shape result_shape = list(base_shape) if fill: result_shape.insert(0, max(data.keys()) + 1) else: result_shape.insert(0, len(list(data.keys()))) result = np.empty(result_shape) + np.nan for (i, (k, v)) in enumerate(data.items()): v = np.array(v) if v.shape != base_shape: raise RuntimeError("Dictionary cannot be converted to matrix, " + "not all values have same dimensions") result[fill and [k][0] or [i][0]] = v return result
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Creates a NumPy array from a dictionary with only integers as keys and NumPy arrays as values. Dimension 0 of the resulting array is formed from data.keys(). Missing values in keys can be filled up with np.nan (default) or ignored. Parameters ---------- data : dict a dictionary with integers as keys and array-likes of the same shape as values fill : boolean flag specifying if the resulting matrix will keep a correspondence between dictionary keys and matrix indices by filling up missing keys with matrices of NaNs. Defaults to True Returns ------- numpy array with one more dimension than the values of the input dict
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/utils.py#L90-L128
nwilming/ocupy
ocupy/utils.py
dict_fun
def dict_fun(data, function): """ Apply a function to all values in a dictionary, return a dictionary with results. Parameters ---------- data : dict a dictionary whose values are adequate input to the second argument of this function. function : function a function that takes one argument Returns ------- a dictionary with the same keys as data, such that result[key] = function(data[key]) """ return dict((k, function(v)) for k, v in list(data.items()))
python
def dict_fun(data, function): """ Apply a function to all values in a dictionary, return a dictionary with results. Parameters ---------- data : dict a dictionary whose values are adequate input to the second argument of this function. function : function a function that takes one argument Returns ------- a dictionary with the same keys as data, such that result[key] = function(data[key]) """ return dict((k, function(v)) for k, v in list(data.items()))
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Apply a function to all values in a dictionary, return a dictionary with results. Parameters ---------- data : dict a dictionary whose values are adequate input to the second argument of this function. function : function a function that takes one argument Returns ------- a dictionary with the same keys as data, such that result[key] = function(data[key])
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/utils.py#L130-L148
nwilming/ocupy
ocupy/utils.py
snip_string_middle
def snip_string_middle(string, max_len=20, snip_string='...'): """ >>> snip_string_middle('this is long', 8) 'th...ong' >>> snip_string_middle('this is long', 12) 'this is long' >>> snip_string_middle('this is long', 8, '~') 'thi~long' """ #warn('use snip_string() instead', DeprecationWarning) if len(string) <= max_len: new_string = string else: visible_len = (max_len - len(snip_string)) start_len = visible_len//2 end_len = visible_len-start_len new_string = string[0:start_len]+ snip_string + string[-end_len:] return new_string
python
def snip_string_middle(string, max_len=20, snip_string='...'): """ >>> snip_string_middle('this is long', 8) 'th...ong' >>> snip_string_middle('this is long', 12) 'this is long' >>> snip_string_middle('this is long', 8, '~') 'thi~long' """ #warn('use snip_string() instead', DeprecationWarning) if len(string) <= max_len: new_string = string else: visible_len = (max_len - len(snip_string)) start_len = visible_len//2 end_len = visible_len-start_len new_string = string[0:start_len]+ snip_string + string[-end_len:] return new_string
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>>> snip_string_middle('this is long', 8) 'th...ong' >>> snip_string_middle('this is long', 12) 'this is long' >>> snip_string_middle('this is long', 8, '~') 'thi~long'
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/utils.py#L150-L171
nwilming/ocupy
ocupy/utils.py
snip_string
def snip_string(string, max_len=20, snip_string='...', snip_point=0.5): """ Snips a string so that it is no longer than max_len, replacing deleted characters with the snip_string. The snip is done at snip_point, which is a fraction between 0 and 1, indicating relatively where along the string to snip. snip_point of 0.5 would be the middle. >>> snip_string('this is long', 8) 'this ...' >>> snip_string('this is long', 8, snip_point=0.5) 'th...ong' >>> snip_string('this is long', 12) 'this is long' >>> snip_string('this is long', 8, '~') 'this is~' >>> snip_string('this is long', 8, '~', 0.5) 'thi~long' """ if len(string) <= max_len: new_string = string else: visible_len = (max_len - len(snip_string)) start_len = int(visible_len*snip_point) end_len = visible_len-start_len new_string = string[0:start_len]+ snip_string if end_len > 0: new_string += string[-end_len:] return new_string
python
def snip_string(string, max_len=20, snip_string='...', snip_point=0.5): """ Snips a string so that it is no longer than max_len, replacing deleted characters with the snip_string. The snip is done at snip_point, which is a fraction between 0 and 1, indicating relatively where along the string to snip. snip_point of 0.5 would be the middle. >>> snip_string('this is long', 8) 'this ...' >>> snip_string('this is long', 8, snip_point=0.5) 'th...ong' >>> snip_string('this is long', 12) 'this is long' >>> snip_string('this is long', 8, '~') 'this is~' >>> snip_string('this is long', 8, '~', 0.5) 'thi~long' """ if len(string) <= max_len: new_string = string else: visible_len = (max_len - len(snip_string)) start_len = int(visible_len*snip_point) end_len = visible_len-start_len new_string = string[0:start_len]+ snip_string if end_len > 0: new_string += string[-end_len:] return new_string
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Snips a string so that it is no longer than max_len, replacing deleted characters with the snip_string. The snip is done at snip_point, which is a fraction between 0 and 1, indicating relatively where along the string to snip. snip_point of 0.5 would be the middle. >>> snip_string('this is long', 8) 'this ...' >>> snip_string('this is long', 8, snip_point=0.5) 'th...ong' >>> snip_string('this is long', 12) 'this is long' >>> snip_string('this is long', 8, '~') 'this is~' >>> snip_string('this is long', 8, '~', 0.5) 'thi~long'
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/utils.py#L173-L203
nwilming/ocupy
ocupy/utils.py
find_common_beginning
def find_common_beginning(string_list, boundary_char = None): """Given a list of strings, finds finds the longest string that is common to the *beginning* of all strings in the list. boundary_char defines a boundary that must be preserved, so that the common string removed must end with this char. """ common='' # by definition there is nothing common to 1 item... if len(string_list) > 1: shortestLen = min([len(el) for el in string_list]) for idx in range(shortestLen): chars = [s[idx] for s in string_list] if chars.count(chars[0]) != len(chars): # test if any chars differ break common+=chars[0] if boundary_char is not None: try: end_idx = common.rindex(boundary_char) common = common[0:end_idx+1] except ValueError: common = '' return common
python
def find_common_beginning(string_list, boundary_char = None): """Given a list of strings, finds finds the longest string that is common to the *beginning* of all strings in the list. boundary_char defines a boundary that must be preserved, so that the common string removed must end with this char. """ common='' # by definition there is nothing common to 1 item... if len(string_list) > 1: shortestLen = min([len(el) for el in string_list]) for idx in range(shortestLen): chars = [s[idx] for s in string_list] if chars.count(chars[0]) != len(chars): # test if any chars differ break common+=chars[0] if boundary_char is not None: try: end_idx = common.rindex(boundary_char) common = common[0:end_idx+1] except ValueError: common = '' return common
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Given a list of strings, finds finds the longest string that is common to the *beginning* of all strings in the list. boundary_char defines a boundary that must be preserved, so that the common string removed must end with this char.
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/utils.py#L205-L233
nwilming/ocupy
ocupy/utils.py
factorise_strings
def factorise_strings (string_list, boundary_char=None): """Given a list of strings, finds the longest string that is common to the *beginning* of all strings in the list and returns a new list whose elements lack this common beginning. boundary_char defines a boundary that must be preserved, so that the common string removed must end with this char. >>> cmn='something/to/begin with?' >>> blah=[cmn+'yes',cmn+'no',cmn+'?maybe'] >>> (blee, bleecmn) = factorise_strings(blah) >>> blee ['yes', 'no', '?maybe'] >>> bleecmn == cmn True >>> blah = ['de.uos.nbp.senhance', 'de.uos.nbp.heartFelt'] >>> (blee, bleecmn) = factorise_strings(blah, '.') >>> blee ['senhance', 'heartFelt'] >>> bleecmn 'de.uos.nbp.' >>> blah = ['/some/deep/dir/subdir', '/some/deep/other/dir', '/some/deep/other/dir2'] >>> (blee, bleecmn) = factorise_strings(blah, '/') >>> blee ['dir/subdir', 'other/dir', 'other/dir2'] >>> bleecmn '/some/deep/' >>> blah = ['/net/store/nbp/heartFelt/data/ecg/emotive_interoception/p20/2012-01-27T09.01.14-ecg.csv', '/net/store/nbp/heartFelt/data/ecg/emotive_interoception/p21/2012-01-27T11.03.08-ecg.csv', '/net/store/nbp/heartFelt/data/ecg/emotive_interoception/p23/2012-01-31T12.02.55-ecg.csv'] >>> (blee, bleecmn) = factorise_strings(blah, '/') >>> bleecmn '/net/store/nbp/heartFelt/data/ecg/emotive_interoception/' rmuil 2012/02/01 """ cmn = find_common_beginning(string_list, boundary_char) new_list = [el[len(cmn):] for el in string_list] return (new_list, cmn)
python
def factorise_strings (string_list, boundary_char=None): """Given a list of strings, finds the longest string that is common to the *beginning* of all strings in the list and returns a new list whose elements lack this common beginning. boundary_char defines a boundary that must be preserved, so that the common string removed must end with this char. >>> cmn='something/to/begin with?' >>> blah=[cmn+'yes',cmn+'no',cmn+'?maybe'] >>> (blee, bleecmn) = factorise_strings(blah) >>> blee ['yes', 'no', '?maybe'] >>> bleecmn == cmn True >>> blah = ['de.uos.nbp.senhance', 'de.uos.nbp.heartFelt'] >>> (blee, bleecmn) = factorise_strings(blah, '.') >>> blee ['senhance', 'heartFelt'] >>> bleecmn 'de.uos.nbp.' >>> blah = ['/some/deep/dir/subdir', '/some/deep/other/dir', '/some/deep/other/dir2'] >>> (blee, bleecmn) = factorise_strings(blah, '/') >>> blee ['dir/subdir', 'other/dir', 'other/dir2'] >>> bleecmn '/some/deep/' >>> blah = ['/net/store/nbp/heartFelt/data/ecg/emotive_interoception/p20/2012-01-27T09.01.14-ecg.csv', '/net/store/nbp/heartFelt/data/ecg/emotive_interoception/p21/2012-01-27T11.03.08-ecg.csv', '/net/store/nbp/heartFelt/data/ecg/emotive_interoception/p23/2012-01-31T12.02.55-ecg.csv'] >>> (blee, bleecmn) = factorise_strings(blah, '/') >>> bleecmn '/net/store/nbp/heartFelt/data/ecg/emotive_interoception/' rmuil 2012/02/01 """ cmn = find_common_beginning(string_list, boundary_char) new_list = [el[len(cmn):] for el in string_list] return (new_list, cmn)
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Given a list of strings, finds the longest string that is common to the *beginning* of all strings in the list and returns a new list whose elements lack this common beginning. boundary_char defines a boundary that must be preserved, so that the common string removed must end with this char. >>> cmn='something/to/begin with?' >>> blah=[cmn+'yes',cmn+'no',cmn+'?maybe'] >>> (blee, bleecmn) = factorise_strings(blah) >>> blee ['yes', 'no', '?maybe'] >>> bleecmn == cmn True >>> blah = ['de.uos.nbp.senhance', 'de.uos.nbp.heartFelt'] >>> (blee, bleecmn) = factorise_strings(blah, '.') >>> blee ['senhance', 'heartFelt'] >>> bleecmn 'de.uos.nbp.' >>> blah = ['/some/deep/dir/subdir', '/some/deep/other/dir', '/some/deep/other/dir2'] >>> (blee, bleecmn) = factorise_strings(blah, '/') >>> blee ['dir/subdir', 'other/dir', 'other/dir2'] >>> bleecmn '/some/deep/' >>> blah = ['/net/store/nbp/heartFelt/data/ecg/emotive_interoception/p20/2012-01-27T09.01.14-ecg.csv', '/net/store/nbp/heartFelt/data/ecg/emotive_interoception/p21/2012-01-27T11.03.08-ecg.csv', '/net/store/nbp/heartFelt/data/ecg/emotive_interoception/p23/2012-01-31T12.02.55-ecg.csv'] >>> (blee, bleecmn) = factorise_strings(blah, '/') >>> bleecmn '/net/store/nbp/heartFelt/data/ecg/emotive_interoception/' rmuil 2012/02/01
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https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/utils.py#L235-L277
nwilming/ocupy
ocupy/datamat.py
load
def load(path, variable='Datamat'): """ Load datamat at path. Parameters: path : string Absolute path of the file to load from. """ f = h5py.File(path,'r') try: dm = fromhdf5(f[variable]) finally: f.close() return dm
python
def load(path, variable='Datamat'): """ Load datamat at path. Parameters: path : string Absolute path of the file to load from. """ f = h5py.File(path,'r') try: dm = fromhdf5(f[variable]) finally: f.close() return dm
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https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat.py#L528-L541
nwilming/ocupy
ocupy/datamat.py
VectorFactory
def VectorFactory(fields, parameters, categories = None): ''' Creates a datamat from a dictionary that contains lists/arrays as values. Input: fields: Dictionary The values will be used as fields of the datamat and the keys as field names. parameters: Dictionary A dictionary whose values are added as parameters. Keys are used for parameter names. ''' fm = Datamat(categories = categories) fm._fields = list(fields.keys()) for (field, value) in list(fields.items()): try: fm.__dict__[field] = np.asarray(value) except ValueError: fm.__dict__[field] = np.asarray(value, dtype=np.object) fm._parameters = parameters for (field, value) in list(parameters.items()): fm.__dict__[field] = value fm._num_fix = len(fm.__dict__[list(fields.keys())[0]]) return fm
python
def VectorFactory(fields, parameters, categories = None): ''' Creates a datamat from a dictionary that contains lists/arrays as values. Input: fields: Dictionary The values will be used as fields of the datamat and the keys as field names. parameters: Dictionary A dictionary whose values are added as parameters. Keys are used for parameter names. ''' fm = Datamat(categories = categories) fm._fields = list(fields.keys()) for (field, value) in list(fields.items()): try: fm.__dict__[field] = np.asarray(value) except ValueError: fm.__dict__[field] = np.asarray(value, dtype=np.object) fm._parameters = parameters for (field, value) in list(parameters.items()): fm.__dict__[field] = value fm._num_fix = len(fm.__dict__[list(fields.keys())[0]]) return fm
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https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat.py#L560-L584
nwilming/ocupy
ocupy/datamat.py
Datamat.filter
def filter(self, index): #@ReservedAssignment """ Filters a datamat by different aspects. This function is a device to filter the datamat by certain logical conditions. It takes as input a logical array (contains only True or False for every datapoint) and kicks out all datapoints for which the array says False. The logical array can conveniently be created with numpy:: >>> print np.unique(fm.category) np.array([2,9]) >>> fm_filtered = fm[ fm.category == 9 ] >>> print np.unique(fm_filtered) np.array([9]) Parameters: index : array Array-like that contains True for every element that passes the filter; else contains False Returns: datamat : Datamat Instance """ return Datamat(categories=self._categories, datamat=self, index=index)
python
def filter(self, index): #@ReservedAssignment """ Filters a datamat by different aspects. This function is a device to filter the datamat by certain logical conditions. It takes as input a logical array (contains only True or False for every datapoint) and kicks out all datapoints for which the array says False. The logical array can conveniently be created with numpy:: >>> print np.unique(fm.category) np.array([2,9]) >>> fm_filtered = fm[ fm.category == 9 ] >>> print np.unique(fm_filtered) np.array([9]) Parameters: index : array Array-like that contains True for every element that passes the filter; else contains False Returns: datamat : Datamat Instance """ return Datamat(categories=self._categories, datamat=self, index=index)
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat.py#L140-L163
nwilming/ocupy
ocupy/datamat.py
Datamat.copy
def copy(self): """ Returns a copy of the datamat. """ return self.filter(np.ones(self._num_fix).astype(bool))
python
def copy(self): """ Returns a copy of the datamat. """ return self.filter(np.ones(self._num_fix).astype(bool))
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat.py#L165-L169
nwilming/ocupy
ocupy/datamat.py
Datamat.save
def save(self, path): """ Saves Datamat to path. Parameters: path : string Absolute path of the file to save to. """ f = h5py.File(path, 'w') try: fm_group = f.create_group('Datamat') for field in self.fieldnames(): try: fm_group.create_dataset(field, data = self.__dict__[field]) except (TypeError,) as e: # Assuming field is an object array that contains dicts which # contain numpy arrays as values sub_group = fm_group.create_group(field) for i, d in enumerate(self.__dict__[field]): index_group = sub_group.create_group(str(i)) print((field, d)) for key, value in list(d.items()): index_group.create_dataset(key, data=value) for param in self.parameters(): fm_group.attrs[param]=self.__dict__[param] finally: f.close()
python
def save(self, path): """ Saves Datamat to path. Parameters: path : string Absolute path of the file to save to. """ f = h5py.File(path, 'w') try: fm_group = f.create_group('Datamat') for field in self.fieldnames(): try: fm_group.create_dataset(field, data = self.__dict__[field]) except (TypeError,) as e: # Assuming field is an object array that contains dicts which # contain numpy arrays as values sub_group = fm_group.create_group(field) for i, d in enumerate(self.__dict__[field]): index_group = sub_group.create_group(str(i)) print((field, d)) for key, value in list(d.items()): index_group.create_dataset(key, data=value) for param in self.parameters(): fm_group.attrs[param]=self.__dict__[param] finally: f.close()
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat.py#L190-L217
nwilming/ocupy
ocupy/datamat.py
Datamat.set_param
def set_param(self, key, value): """ Set the value of a parameter. """ self.__dict__[key] = value self._parameters[key] = value
python
def set_param(self, key, value): """ Set the value of a parameter. """ self.__dict__[key] = value self._parameters[key] = value
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat.py#L234-L239
nwilming/ocupy
ocupy/datamat.py
Datamat.by_field
def by_field(self, field): """ Returns an iterator that iterates over unique values of field Parameters: field : string Filters the datamat for every unique value in field and yields the filtered datamat. Returns: datamat : Datamat that is filtered according to one of the unique values in 'field'. """ for value in np.unique(self.__dict__[field]): yield self.filter(self.__dict__[field] == value)
python
def by_field(self, field): """ Returns an iterator that iterates over unique values of field Parameters: field : string Filters the datamat for every unique value in field and yields the filtered datamat. Returns: datamat : Datamat that is filtered according to one of the unique values in 'field'. """ for value in np.unique(self.__dict__[field]): yield self.filter(self.__dict__[field] == value)
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Returns an iterator that iterates over unique values of field Parameters: field : string Filters the datamat for every unique value in field and yields the filtered datamat. Returns: datamat : Datamat that is filtered according to one of the unique values in 'field'.
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat.py#L241-L254
nwilming/ocupy
ocupy/datamat.py
Datamat.by_cat
def by_cat(self): """ Iterates over categories and returns a filtered datamat. If a categories object is attached, the images object for the given category is returned as well (else None is returned). Returns: (datamat, categories) : A tuple that contains first the filtered datamat (has only one category) and second the associated categories object (if it is available, None otherwise) """ for value in np.unique(self.category): cat_fm = self.filter(self.category == value) if self._categories: yield (cat_fm, self._categories[value]) else: yield (cat_fm, None)
python
def by_cat(self): """ Iterates over categories and returns a filtered datamat. If a categories object is attached, the images object for the given category is returned as well (else None is returned). Returns: (datamat, categories) : A tuple that contains first the filtered datamat (has only one category) and second the associated categories object (if it is available, None otherwise) """ for value in np.unique(self.category): cat_fm = self.filter(self.category == value) if self._categories: yield (cat_fm, self._categories[value]) else: yield (cat_fm, None)
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Iterates over categories and returns a filtered datamat. If a categories object is attached, the images object for the given category is returned as well (else None is returned). Returns: (datamat, categories) : A tuple that contains first the filtered datamat (has only one category) and second the associated categories object (if it is available, None otherwise)
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat.py#L256-L273
nwilming/ocupy
ocupy/datamat.py
Datamat.by_filenumber
def by_filenumber(self): """ Iterates over categories and returns a filtered datamat. If a categories object is attached, the images object for the given category is returned as well (else None is returned). Returns: (datamat, categories) : A tuple that contains first the filtered datamat (has only one category) and second the associated categories object (if it is available, None otherwise) """ for value in np.unique(self.filenumber): file_fm = self.filter(self.filenumber == value) if self._categories: yield (file_fm, self._categories[self.category[0]][value]) else: yield (file_fm, None)
python
def by_filenumber(self): """ Iterates over categories and returns a filtered datamat. If a categories object is attached, the images object for the given category is returned as well (else None is returned). Returns: (datamat, categories) : A tuple that contains first the filtered datamat (has only one category) and second the associated categories object (if it is available, None otherwise) """ for value in np.unique(self.filenumber): file_fm = self.filter(self.filenumber == value) if self._categories: yield (file_fm, self._categories[self.category[0]][value]) else: yield (file_fm, None)
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Iterates over categories and returns a filtered datamat. If a categories object is attached, the images object for the given category is returned as well (else None is returned). Returns: (datamat, categories) : A tuple that contains first the filtered datamat (has only one category) and second the associated categories object (if it is available, None otherwise)
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat.py#L275-L292
nwilming/ocupy
ocupy/datamat.py
Datamat.add_field
def add_field(self, name, data): """ Add a new field to the datamat. Parameters: name : string Name of the new field data : list Data for the new field, must be same length as all other fields. """ if name in self._fields: raise ValueError if not len(data) == self._num_fix: raise ValueError self._fields.append(name) self.__dict__[name] = data
python
def add_field(self, name, data): """ Add a new field to the datamat. Parameters: name : string Name of the new field data : list Data for the new field, must be same length as all other fields. """ if name in self._fields: raise ValueError if not len(data) == self._num_fix: raise ValueError self._fields.append(name) self.__dict__[name] = data
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Add a new field to the datamat. Parameters: name : string Name of the new field data : list Data for the new field, must be same length as all other fields.
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat.py#L294-L309
nwilming/ocupy
ocupy/datamat.py
Datamat.add_field_like
def add_field_like(self, name, like_array): """ Add a new field to the Datamat with the dtype of the like_array and the shape of the like_array except for the first dimension which will be instead the field-length of this Datamat. """ new_shape = list(like_array.shape) new_shape[0] = len(self) new_data = ma.empty(new_shape, like_array.dtype) new_data.mask = True self.add_field(name, new_data)
python
def add_field_like(self, name, like_array): """ Add a new field to the Datamat with the dtype of the like_array and the shape of the like_array except for the first dimension which will be instead the field-length of this Datamat. """ new_shape = list(like_array.shape) new_shape[0] = len(self) new_data = ma.empty(new_shape, like_array.dtype) new_data.mask = True self.add_field(name, new_data)
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Add a new field to the Datamat with the dtype of the like_array and the shape of the like_array except for the first dimension which will be instead the field-length of this Datamat.
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat.py#L311-L321
nwilming/ocupy
ocupy/datamat.py
Datamat.annotate
def annotate (self, src_dm, data_field, key_field, take_first=True): """ Adds a new field (data_field) to the Datamat with data from the corresponding field of another Datamat (src_dm). This is accomplished through the use of a key_field, which is used to determine how the data is copied. This operation corresponds loosely to an SQL join operation. The two Datamats are essentially aligned by the unique values of key_field so that each block element of the new field of the target Datamat will consist of those elements of src_dm's data_field where the corresponding element in key_field matches. If 'take_first' is not true, and there is not only a single corresponding element (typical usage case) then the target element value will be a sequence (array) of all the matching elements. The target Datamat (self) must not have a field name data_field already, and both Datamats must have key_field. The new field in the target Datamat will be a masked array to handle non-existent data. TODO: Make example more generic, remove interoceptive reference TODO: Make standalone test Examples: >>> dm_intero = load_interoception_files ('test-ecg.csv', silent=True) >>> dm_emotiv = load_emotivestimuli_files ('test-bpm.csv', silent=True) >>> length(dm_intero) 4 >>> unique(dm_intero.subject_id) ['p05', 'p06'] >>> length(dm_emotiv) 3 >>> unique(dm_emotiv.subject_id) ['p04', 'p05', 'p06'] >>> 'interospective_awareness' in dm_intero.fieldnames() True >>> unique(dm_intero.interospective_awareness) == [0.5555, 0.6666] True >>> 'interospective_awareness' in dm_emotiv.fieldnames() False >>> dm_emotiv.copy_field(dm_intero, 'interospective_awareness', 'subject_id') >>> 'interospective_awareness' in dm_emotiv.fieldnames() True >>> unique(dm_emotiv.interospective_awareness) == [NaN, 0.5555, 0.6666] False """ if key_field not in self._fields or key_field not in src_dm._fields: raise AttributeError('key field (%s) must exist in both Datamats'%(key_field)) if data_field not in src_dm._fields: raise AttributeError('data field (%s) must exist in source Datamat' % (data_field)) if data_field in self._fields: raise AttributeError('data field (%s) already exists in target Datamat' % (data_field)) #Create a mapping of key_field value to data value. data_to_copy = dict([(x.field(key_field)[0], x.field(data_field)) for x in src_dm.by_field(key_field)]) data_element = list(data_to_copy.values())[0] #Create the new data array of correct size. # We use a masked array because it is possible that for some elements # of the target Datamat, there exist simply no data in the source # Datamat. NaNs are fine as indication of this for floats, but if the # field happens to hold booleans or integers or something else, NaN # does not work. new_shape = [len(self)] + list(data_element.shape) new_data = ma.empty(new_shape, data_element.dtype) new_data.mask=True if np.issubdtype(new_data.dtype, np.float): new_data.fill(np.NaN) #For backwards compatibility, if mask not used #Now we copy the data. If the data to copy contains only a single value, # it is added to the target as a scalar (single value). # Otherwise, it is copied as is, i.e. as a sequence. for (key, val) in list(data_to_copy.items()): if take_first: new_data[self.field(key_field) == key] = val[0] else: new_data[self.field(key_field) == key] = val self.add_field(data_field, new_data)
python
def annotate (self, src_dm, data_field, key_field, take_first=True): """ Adds a new field (data_field) to the Datamat with data from the corresponding field of another Datamat (src_dm). This is accomplished through the use of a key_field, which is used to determine how the data is copied. This operation corresponds loosely to an SQL join operation. The two Datamats are essentially aligned by the unique values of key_field so that each block element of the new field of the target Datamat will consist of those elements of src_dm's data_field where the corresponding element in key_field matches. If 'take_first' is not true, and there is not only a single corresponding element (typical usage case) then the target element value will be a sequence (array) of all the matching elements. The target Datamat (self) must not have a field name data_field already, and both Datamats must have key_field. The new field in the target Datamat will be a masked array to handle non-existent data. TODO: Make example more generic, remove interoceptive reference TODO: Make standalone test Examples: >>> dm_intero = load_interoception_files ('test-ecg.csv', silent=True) >>> dm_emotiv = load_emotivestimuli_files ('test-bpm.csv', silent=True) >>> length(dm_intero) 4 >>> unique(dm_intero.subject_id) ['p05', 'p06'] >>> length(dm_emotiv) 3 >>> unique(dm_emotiv.subject_id) ['p04', 'p05', 'p06'] >>> 'interospective_awareness' in dm_intero.fieldnames() True >>> unique(dm_intero.interospective_awareness) == [0.5555, 0.6666] True >>> 'interospective_awareness' in dm_emotiv.fieldnames() False >>> dm_emotiv.copy_field(dm_intero, 'interospective_awareness', 'subject_id') >>> 'interospective_awareness' in dm_emotiv.fieldnames() True >>> unique(dm_emotiv.interospective_awareness) == [NaN, 0.5555, 0.6666] False """ if key_field not in self._fields or key_field not in src_dm._fields: raise AttributeError('key field (%s) must exist in both Datamats'%(key_field)) if data_field not in src_dm._fields: raise AttributeError('data field (%s) must exist in source Datamat' % (data_field)) if data_field in self._fields: raise AttributeError('data field (%s) already exists in target Datamat' % (data_field)) #Create a mapping of key_field value to data value. data_to_copy = dict([(x.field(key_field)[0], x.field(data_field)) for x in src_dm.by_field(key_field)]) data_element = list(data_to_copy.values())[0] #Create the new data array of correct size. # We use a masked array because it is possible that for some elements # of the target Datamat, there exist simply no data in the source # Datamat. NaNs are fine as indication of this for floats, but if the # field happens to hold booleans or integers or something else, NaN # does not work. new_shape = [len(self)] + list(data_element.shape) new_data = ma.empty(new_shape, data_element.dtype) new_data.mask=True if np.issubdtype(new_data.dtype, np.float): new_data.fill(np.NaN) #For backwards compatibility, if mask not used #Now we copy the data. If the data to copy contains only a single value, # it is added to the target as a scalar (single value). # Otherwise, it is copied as is, i.e. as a sequence. for (key, val) in list(data_to_copy.items()): if take_first: new_data[self.field(key_field) == key] = val[0] else: new_data[self.field(key_field) == key] = val self.add_field(data_field, new_data)
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Adds a new field (data_field) to the Datamat with data from the corresponding field of another Datamat (src_dm). This is accomplished through the use of a key_field, which is used to determine how the data is copied. This operation corresponds loosely to an SQL join operation. The two Datamats are essentially aligned by the unique values of key_field so that each block element of the new field of the target Datamat will consist of those elements of src_dm's data_field where the corresponding element in key_field matches. If 'take_first' is not true, and there is not only a single corresponding element (typical usage case) then the target element value will be a sequence (array) of all the matching elements. The target Datamat (self) must not have a field name data_field already, and both Datamats must have key_field. The new field in the target Datamat will be a masked array to handle non-existent data. TODO: Make example more generic, remove interoceptive reference TODO: Make standalone test Examples: >>> dm_intero = load_interoception_files ('test-ecg.csv', silent=True) >>> dm_emotiv = load_emotivestimuli_files ('test-bpm.csv', silent=True) >>> length(dm_intero) 4 >>> unique(dm_intero.subject_id) ['p05', 'p06'] >>> length(dm_emotiv) 3 >>> unique(dm_emotiv.subject_id) ['p04', 'p05', 'p06'] >>> 'interospective_awareness' in dm_intero.fieldnames() True >>> unique(dm_intero.interospective_awareness) == [0.5555, 0.6666] True >>> 'interospective_awareness' in dm_emotiv.fieldnames() False >>> dm_emotiv.copy_field(dm_intero, 'interospective_awareness', 'subject_id') >>> 'interospective_awareness' in dm_emotiv.fieldnames() True >>> unique(dm_emotiv.interospective_awareness) == [NaN, 0.5555, 0.6666] False
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat.py#L323-L408
nwilming/ocupy
ocupy/datamat.py
Datamat.rm_field
def rm_field(self, name): """ Remove a field from the datamat. Parameters: name : string Name of the field to be removed """ if not name in self._fields: raise ValueError self._fields.remove(name) del self.__dict__[name]
python
def rm_field(self, name): """ Remove a field from the datamat. Parameters: name : string Name of the field to be removed """ if not name in self._fields: raise ValueError self._fields.remove(name) del self.__dict__[name]
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Remove a field from the datamat. Parameters: name : string Name of the field to be removed
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat.py#L410-L421
nwilming/ocupy
ocupy/datamat.py
Datamat.add_parameter
def add_parameter(self, name, value): """ Adds a parameter to the existing Datamat. Fails if parameter with same name already exists or if name is otherwise in this objects ___dict__ dictionary. """ if name in self._parameters: raise ValueError("'%s' is already a parameter" % (name)) elif name in self.__dict__: raise ValueError("'%s' conflicts with the Datamat name-space" % (name)) self.__dict__[name] = value self._parameters[name] = self.__dict__[name]
python
def add_parameter(self, name, value): """ Adds a parameter to the existing Datamat. Fails if parameter with same name already exists or if name is otherwise in this objects ___dict__ dictionary. """ if name in self._parameters: raise ValueError("'%s' is already a parameter" % (name)) elif name in self.__dict__: raise ValueError("'%s' conflicts with the Datamat name-space" % (name)) self.__dict__[name] = value self._parameters[name] = self.__dict__[name]
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat.py#L423-L436
nwilming/ocupy
ocupy/datamat.py
Datamat.rm_parameter
def rm_parameter(self, name): """ Removes a parameter to the existing Datamat. Fails if parameter doesn't exist. """ if name not in self._parameters: raise ValueError("no '%s' parameter found" % (name)) del self._parameters[name] del self.__dict__[name]
python
def rm_parameter(self, name): """ Removes a parameter to the existing Datamat. Fails if parameter doesn't exist. """ if name not in self._parameters: raise ValueError("no '%s' parameter found" % (name)) del self._parameters[name] del self.__dict__[name]
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat.py#L438-L448
nwilming/ocupy
ocupy/datamat.py
Datamat.parameter_to_field
def parameter_to_field(self, name): """ Promotes a parameter to a field by creating a new array of same size as the other existing fields, filling it with the current value of the parameter, and then removing that parameter. """ if name not in self._parameters: raise ValueError("no '%s' parameter found" % (name)) if self._fields.count(name) > 0: raise ValueError("field with name '%s' already exists" % (name)) data = np.array([self._parameters[name]]*self._num_fix) self.rm_parameter(name) self.add_field(name, data)
python
def parameter_to_field(self, name): """ Promotes a parameter to a field by creating a new array of same size as the other existing fields, filling it with the current value of the parameter, and then removing that parameter. """ if name not in self._parameters: raise ValueError("no '%s' parameter found" % (name)) if self._fields.count(name) > 0: raise ValueError("field with name '%s' already exists" % (name)) data = np.array([self._parameters[name]]*self._num_fix) self.rm_parameter(name) self.add_field(name, data)
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Promotes a parameter to a field by creating a new array of same size as the other existing fields, filling it with the current value of the parameter, and then removing that parameter.
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat.py#L450-L464
nwilming/ocupy
ocupy/datamat.py
Datamat.join
def join(self, fm_new, minimal_subset=True): """ Adds content of a new Datamat to this Datamat. If a parameter of the Datamats is not equal or does not exist in one, it is promoted to a field. If the two Datamats have different fields then the elements for the Datamats that did not have the field will be NaN, unless 'minimal_subset' is true, in which case the mismatching fields will simply be deleted. Parameters fm_new : instance of Datamat This Datamat is added to the current one. minimal_subset : if true, remove fields which don't exist in both, instead of using NaNs for missing elements (defaults to False) Capacity to use superset of fields added by rmuil 2012/01/30 """ # Check if parameters are equal. If not, promote them to fields. ''' for (nm, val) in fm_new._parameters.items(): if self._parameters.has_key(nm): if (val != self._parameters[nm]): self.parameter_to_field(nm) fm_new.parameter_to_field(nm) else: fm_new.parameter_to_field(nm) ''' # Deal with mismatch in the fields # First those in self that do not exist in new... orig_fields = self._fields[:] for field in orig_fields: if not field in fm_new._fields: if minimal_subset: self.rm_field(field) else: warnings.warn("This option is deprecated. Clean and Filter your data before it is joined.", DeprecationWarning) fm_new.add_field_like(field, self.field(field)) # ... then those in the new that do not exist in self. orig_fields = fm_new._fields[:] for field in orig_fields: if not field in self._fields: if minimal_subset: fm_new.rm_field(field) else: warnings.warn("This option is deprecated. Clean and Filter your data before it is joined.", DeprecationWarning) self.add_field_like(field, fm_new.field(field)) if 'SUBJECTINDEX' in self._fields[:]: if fm_new.SUBJECTINDEX[0] in self.SUBJECTINDEX: fm_new.SUBJECTINDEX[:] = self.SUBJECTINDEX.max()+1 # Concatenate fields for field in self._fields: self.__dict__[field] = ma.hstack((self.__dict__[field], fm_new.__dict__[field])) # Update _num_fix self._num_fix += fm_new._num_fix
python
def join(self, fm_new, minimal_subset=True): """ Adds content of a new Datamat to this Datamat. If a parameter of the Datamats is not equal or does not exist in one, it is promoted to a field. If the two Datamats have different fields then the elements for the Datamats that did not have the field will be NaN, unless 'minimal_subset' is true, in which case the mismatching fields will simply be deleted. Parameters fm_new : instance of Datamat This Datamat is added to the current one. minimal_subset : if true, remove fields which don't exist in both, instead of using NaNs for missing elements (defaults to False) Capacity to use superset of fields added by rmuil 2012/01/30 """ # Check if parameters are equal. If not, promote them to fields. ''' for (nm, val) in fm_new._parameters.items(): if self._parameters.has_key(nm): if (val != self._parameters[nm]): self.parameter_to_field(nm) fm_new.parameter_to_field(nm) else: fm_new.parameter_to_field(nm) ''' # Deal with mismatch in the fields # First those in self that do not exist in new... orig_fields = self._fields[:] for field in orig_fields: if not field in fm_new._fields: if minimal_subset: self.rm_field(field) else: warnings.warn("This option is deprecated. Clean and Filter your data before it is joined.", DeprecationWarning) fm_new.add_field_like(field, self.field(field)) # ... then those in the new that do not exist in self. orig_fields = fm_new._fields[:] for field in orig_fields: if not field in self._fields: if minimal_subset: fm_new.rm_field(field) else: warnings.warn("This option is deprecated. Clean and Filter your data before it is joined.", DeprecationWarning) self.add_field_like(field, fm_new.field(field)) if 'SUBJECTINDEX' in self._fields[:]: if fm_new.SUBJECTINDEX[0] in self.SUBJECTINDEX: fm_new.SUBJECTINDEX[:] = self.SUBJECTINDEX.max()+1 # Concatenate fields for field in self._fields: self.__dict__[field] = ma.hstack((self.__dict__[field], fm_new.__dict__[field])) # Update _num_fix self._num_fix += fm_new._num_fix
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/datamat.py#L466-L526
nwilming/ocupy
ocupy/simulator.py
makeAngLenHist
def makeAngLenHist(ad, ld, fm = None, collapse=True, fit=spline_base.fit2d): """ Histograms and performs a spline fit on the given data, usually angle and length differences. Parameters: ad : array The data to be histogrammed along the x-axis. May range from -180 to 180. ld : array The data to be histogrammed along the y-axis. May range from -36 to 36. collapse : boolean If true, the histogrammed data will include negative values on the x-axis. Else, the histogram will be collapsed along x = 0, and thus contain only positive angle differences fit : function or None, optional The function to use in order to fit the data. If no fit should be applied, set to None fm : fixmat or None, optional If given, the angle and length differences are calculated from the fixmat and the previous parameters are overwritten. """ if fm: ad,ld = anglendiff(fm, roll=2) ad, ld = ad[0], ld[0] ld = ld[~np.isnan(ld)] ad = reshift(ad[~np.isnan(ad)]) if collapse: e_y = np.linspace(-36.5, 36.5, 74) e_x = np.linspace(0, 180, 181) H = makeHist(abs(ad), ld, fit=fit, bins=[e_y, e_x]) H = H/H.sum() return H else: e_x = np.linspace(-180, 180, 361) e_y = np.linspace(-36.5, 36.5, 74) return makeHist(ad, ld, fit=fit, bins=[e_y, e_x])
python
def makeAngLenHist(ad, ld, fm = None, collapse=True, fit=spline_base.fit2d): """ Histograms and performs a spline fit on the given data, usually angle and length differences. Parameters: ad : array The data to be histogrammed along the x-axis. May range from -180 to 180. ld : array The data to be histogrammed along the y-axis. May range from -36 to 36. collapse : boolean If true, the histogrammed data will include negative values on the x-axis. Else, the histogram will be collapsed along x = 0, and thus contain only positive angle differences fit : function or None, optional The function to use in order to fit the data. If no fit should be applied, set to None fm : fixmat or None, optional If given, the angle and length differences are calculated from the fixmat and the previous parameters are overwritten. """ if fm: ad,ld = anglendiff(fm, roll=2) ad, ld = ad[0], ld[0] ld = ld[~np.isnan(ld)] ad = reshift(ad[~np.isnan(ad)]) if collapse: e_y = np.linspace(-36.5, 36.5, 74) e_x = np.linspace(0, 180, 181) H = makeHist(abs(ad), ld, fit=fit, bins=[e_y, e_x]) H = H/H.sum() return H else: e_x = np.linspace(-180, 180, 361) e_y = np.linspace(-36.5, 36.5, 74) return makeHist(ad, ld, fit=fit, bins=[e_y, e_x])
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Histograms and performs a spline fit on the given data, usually angle and length differences. Parameters: ad : array The data to be histogrammed along the x-axis. May range from -180 to 180. ld : array The data to be histogrammed along the y-axis. May range from -36 to 36. collapse : boolean If true, the histogrammed data will include negative values on the x-axis. Else, the histogram will be collapsed along x = 0, and thus contain only positive angle differences fit : function or None, optional The function to use in order to fit the data. If no fit should be applied, set to None fm : fixmat or None, optional If given, the angle and length differences are calculated from the fixmat and the previous parameters are overwritten.
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train
https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/simulator.py#L329-L372