mirror of
https://github.com/saymrwulf/prophet.git
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ded98c493e
Clearly identify this project as supporting python 2 and 3. This is useful for utility programs like [caniusepython3](https://github.com/brettcannon/caniusepython3#how-do-you-tell-if-a-project-has-been-ported-to-python-3).
132 lines
4.2 KiB
Python
132 lines
4.2 KiB
Python
# Copyright (c) Facebook, Inc. and its affiliates.
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# This source code is licensed under the MIT license found in the
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# LICENSE file in the root directory of this source tree.
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import os.path
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import pickle
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import platform
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import sys
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from pkg_resources import (
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normalize_path,
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working_set,
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add_activation_listener,
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require,
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)
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from setuptools import setup, find_packages
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from setuptools.command.build_py import build_py
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from setuptools.command.develop import develop
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from setuptools.command.test import test as test_command
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PLATFORM = 'unix'
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if platform.platform().startswith('Win'):
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PLATFORM = 'win'
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MODEL_DIR = os.path.join('stan', PLATFORM)
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MODEL_TARGET_DIR = os.path.join('fbprophet', 'stan_model')
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def build_stan_model(target_dir, model_dir=MODEL_DIR):
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from pystan import StanModel
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model_name = 'prophet.stan'
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target_name = 'prophet_model.pkl'
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with open(os.path.join(model_dir, model_name)) as f:
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model_code = f.read()
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sm = StanModel(model_code=model_code)
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with open(os.path.join(target_dir, target_name), 'wb') as f:
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pickle.dump(sm, f, protocol=pickle.HIGHEST_PROTOCOL)
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class BuildPyCommand(build_py):
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"""Custom build command to pre-compile Stan models."""
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def run(self):
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if not self.dry_run:
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target_dir = os.path.join(self.build_lib, MODEL_TARGET_DIR)
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self.mkpath(target_dir)
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build_stan_model(target_dir)
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build_py.run(self)
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class DevelopCommand(develop):
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"""Custom develop command to pre-compile Stan models in-place."""
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def run(self):
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if not self.dry_run:
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target_dir = os.path.join(self.setup_path, MODEL_TARGET_DIR)
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self.mkpath(target_dir)
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build_stan_model(target_dir)
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develop.run(self)
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class TestCommand(test_command):
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"""We must run tests on the build directory, not source."""
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def with_project_on_sys_path(self, func):
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# Ensure metadata is up-to-date
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self.reinitialize_command('build_py', inplace=0)
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self.run_command('build_py')
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bpy_cmd = self.get_finalized_command("build_py")
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build_path = normalize_path(bpy_cmd.build_lib)
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# Build extensions
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self.reinitialize_command('egg_info', egg_base=build_path)
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self.run_command('egg_info')
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self.reinitialize_command('build_ext', inplace=0)
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self.run_command('build_ext')
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ei_cmd = self.get_finalized_command("egg_info")
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old_path = sys.path[:]
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old_modules = sys.modules.copy()
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try:
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sys.path.insert(0, normalize_path(ei_cmd.egg_base))
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working_set.__init__()
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add_activation_listener(lambda dist: dist.activate())
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require('%s==%s' % (ei_cmd.egg_name, ei_cmd.egg_version))
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func()
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finally:
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sys.path[:] = old_path
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sys.modules.clear()
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sys.modules.update(old_modules)
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working_set.__init__()
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with open('requirements.txt', 'r') as f:
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install_requires = f.read().splitlines()
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setup(
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name='fbprophet',
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version='0.5',
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description='Automatic Forecasting Procedure',
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url='https://facebook.github.io/prophet/',
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author='Sean J. Taylor <sjtz@pm.me>, Ben Letham <bletham@fb.com>',
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author_email='sjtz@pm.me',
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license='MIT',
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packages=find_packages(),
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setup_requires=[
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],
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install_requires=install_requires,
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zip_safe=False,
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include_package_data=True,
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cmdclass={
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'build_py': BuildPyCommand,
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'develop': DevelopCommand,
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'test': TestCommand,
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},
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test_suite='fbprophet.tests',
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classifiers=[
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'Programming Language :: Python',
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'Programming Language :: Python :: 2.7',
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'Programming Language :: Python :: 3',
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'Programming Language :: Python :: 3.7',
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],
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long_description="""
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Implements a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well.
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"""
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)
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