supplychainpy.reporting package¶
Subpackages¶
Submodules¶
supplychainpy.reporting.config module¶
supplychainpy.reporting.extensions module¶
supplychainpy.reporting.forms module¶
supplychainpy.reporting.load module¶
-
supplychainpy.reporting.load.
batch
(analysis, n)¶ Yield n-sized batches from analysis. :param analysis: :param n:
-
supplychainpy.reporting.load.
build_results_pickle
(ses_forecast_results: dict)¶
-
supplychainpy.reporting.load.
cleanup_pickled_files
()¶
-
supplychainpy.reporting.load.
currency_codes
() → dict¶ Retrives HTML Entity (decimal) for currency symbol.
Returns: Currency Symbols. Return type: dict
-
supplychainpy.reporting.load.
load
(file_path: str, location: str = None)¶ Loads analysis and forecast into local database for reporting suite.
Parameters: - file_path (str) – File path to source file containing data for analysis.
- location (str) – Location of database to populate.
-
supplychainpy.reporting.load.
load_currency
(fx_codes: {'AED': ('United Arab Emirates Dirham', '\u062f.'), 'ANG': ('Netherlands Antilles Guilder', 'ƒ'), 'GBP': ('United Kingdom Pound', '£'), 'USD': ('United States Dollar', '$'), 'EUR': ('Euro Member Countries', '€')}, ctx: <SQLAlchemy engine=None>)¶ Loads Currency Symbols
-
supplychainpy.reporting.load.
load_profile_recommendations
(analysed_order, forecast, transaction_log_id)¶
-
supplychainpy.reporting.load.
load_recommendations
(summary, forecast, analysed_order)¶
-
supplychainpy.reporting.load.
parallelise_htc
(batched_analysis: list, core_count: int)¶ Execute the Holts’ trend corrected smoothing forecast in parallel.
Parameters: - batched_analysis – Uncertain demand objects batched for appropriate number of cores available on the host machine
- core_count – Number of cores available on the host machine, minus one.
Returns: dict
-
supplychainpy.reporting.load.
parallelise_ses
(pickled_ses_batch_files: list, core_count: int) → dict¶ Execute the exponential smoothing forecast in parallel.
Parameters: - pickled_ses_batch_files – Uncertain demand objects batched for appropriate number of cores available on the host machine
- core_count – Number of cores available on the host machine, minus one.
Returns: dict
-
supplychainpy.reporting.load.
pickle_ses_forecast
(batched_analysis: list) → list¶
-
supplychainpy.reporting.load.
read_pickle
(batch_path: str)¶ Read pickled data from file
-
supplychainpy.reporting.load.
remove_pickle
(path: str)¶
-
supplychainpy.reporting.load.
retrieve_results_pickle
()¶
-
supplychainpy.reporting.load.
write_pickle
(**kwargs) → str¶ pickle data to file