Pakage rename (#1844)

* Rename package from fbprophet to prophet, and add shim

* Untrack files that should have been ignored

* Update github actions build commands

.deepsource.toml

@@ -1,6 +1,6 @@
 version = 1
 
-test_patterns = ["python/fbprophet/tests/**"]
+test_patterns = ["python/prophet/tests/**"]
 exclude_patterns = ["R/**", "notebooks/**", "docs/**", "examples/**"]
 
 [[analyzers]]

.github/workflows/build-and-test.yml

@@ -26,7 +26,7 @@ jobs:
         pip install -U -r python/requirements.txt dask[dataframe] distributed
         cd python && python setup.py develop test
         python setup.py clean
-        rm -rf fbprophet/stan_model
+        rm -rf prophet/stan_model
         wget https://github.com/stan-dev/cmdstan/releases/download/v2.26.1/cmdstan-2.26.1.tar.gz -O /tmp/cmdstan.tar.gz > /dev/null
         tar -xvf /tmp/cmdstan.tar.gz -C /tmp > /dev/null
         make -C /tmp/cmdstan-2.26.1/ build > /dev/null

.gitignore

@@ -6,16 +6,20 @@
 
 # Setuptools distribution folder.
 python/dist/
+python_shim/dist/
 
 # test cache
 .pytest_cache
+python/prophet/tests/dask-worker-space
 
 # Python cache
 __pycache__
 
 # Python egg metadata, regenerated from source files by setuptools.
 python/*.egg-info
-build/
+python/build/
+python_shim/*.egg-info
+python_shim/build/
 
 # Notebook checkpoints
 .ipynb_checkpoints

.travis.yml

@@ -17,7 +17,7 @@ jobs:
       script:
         - cd python && python setup.py develop test
         - python setup.py clean
-        - rm -rf fbprophet/stan_model
+        - rm -rf prophet/stan_model
         - wget https://github.com/stan-dev/cmdstan/releases/download/v2.22.1/cmdstan-2.22.1.tar.gz -O /tmp/cmdstan.tar.gz > /dev/null
         - tar -xvf /tmp/cmdstan.tar.gz -C /tmp > /dev/null
         - make -C /tmp/cmdstan-2.22.1/ build > /dev/null

notebooks/additional_topics.ipynb

@@ -6,29 +6,45 @@
    "metadata": {
     "block_hidden": true
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<fbprophet.forecaster.Prophet at 0x7f9eb843ca90>"
-      ]
-     },
-     "execution_count": 1,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "%load_ext rpy2.ipython\n",
     "%matplotlib inline\n",
     "import pandas as pd\n",
     "import numpy as np\n",
-    "from fbprophet import Prophet\n",
+    "from prophet import Prophet\n",
     "import logging\n",
-    "logging.getLogger('fbprophet').setLevel(logging.ERROR)\n",
+    "logging.getLogger('prophet').setLevel(logging.ERROR)\n",
     "import warnings\n",
-    "warnings.filterwarnings(\"ignore\")\n",
-    "\n",
+    "warnings.filterwarnings(\"ignore\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "block_hidden": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:numexpr.utils:NumExpr defaulting to 8 threads.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<prophet.forecaster.Prophet at 0x7f578ce95760>"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
     "df = pd.DataFrame({\n",
     "    'ds': pd.date_range(start='2020-01-01', periods=20),\n",
     "    'y': np.arange(20),\n",
@@ -48,15 +64,15 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "WARNING:rpy2.rinterface_lib.callbacks:R[write to console]: Loading required package: Rcpp\n",
+      "R[write to console]: Loading required package: Rcpp\n",
       "\n",
-      "WARNING:rpy2.rinterface_lib.callbacks:R[write to console]: Loading required package: rlang\n",
+      "R[write to console]: Loading required package: rlang\n",
       "\n",
-      "WARNING:rpy2.rinterface_lib.callbacks:R[write to console]: Disabling yearly seasonality. Run prophet with yearly.seasonality=TRUE to override this.\n",
+      "R[write to console]: Disabling yearly seasonality. Run prophet with yearly.seasonality=TRUE to override this.\n",
       "\n",
-      "WARNING:rpy2.rinterface_lib.callbacks:R[write to console]: Disabling daily seasonality. Run prophet with daily.seasonality=TRUE to override this.\n",
+      "R[write to console]: Disabling daily seasonality. Run prophet with daily.seasonality=TRUE to override this.\n",
       "\n",
-      "WARNING:rpy2.rinterface_lib.callbacks:R[write to console]: n.changepoints greater than number of observations. Using 15\n",
+      "R[write to console]: n.changepoints greater than number of observations. Using 15\n",
       "\n"
      ]
     }
@@ -102,12 +118,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
     "import json\n",
-    "from fbprophet.serialize import model_to_json, model_from_json\n",
+    "from prophet.serialize import model_to_json, model_from_json\n",
     "\n",
     "with open('serialized_model.json', 'w') as fout:\n",
     "    json.dump(model_to_json(m), fout)  # Save model\n",
@@ -120,7 +136,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The json file will be portable across systems, and deserialization is backwards compatible with older versions of fbprophet."
+    "The json file will be portable across systems, and deserialization is backwards compatible with older versions of prophet."
    ]
   },
   {
@@ -134,9 +150,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "R[write to console]: Disabling yearly seasonality. Run prophet with yearly.seasonality=TRUE to override this.\n",
+      "\n",
+      "R[write to console]: Disabling daily seasonality. Run prophet with daily.seasonality=TRUE to override this.\n",
+      "\n",
+      "R[write to console]: n.changepoints greater than number of observations. Using 15\n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "%%R\n",
     "m <- prophet(df, growth='flat')"
@@ -144,7 +173,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -171,15 +200,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "1.44 s ± 121 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
-      "860 ms ± 203 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
+      "1.33 s ± 55.9 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
+      "185 ms ± 4.46 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
      ]
     }
    ],
@@ -219,7 +248,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "As can be seen, the parameters from the previous model are passed in to the fitting for the next with the kwarg `init`. In this case, model fitting was almost 2x faster when using warm starting. The speedup will generally depend on how much the optimal model parameters have changed with the addition of the new data.\n",
+    "As can be seen, the parameters from the previous model are passed in to the fitting for the next with the kwarg `init`. In this case, model fitting was about 5x faster when using warm starting. The speedup will generally depend on how much the optimal model parameters have changed with the addition of the new data.\n",
     "\n",
     "There are few caveats that should be kept in mind when considering warm-starting. First, warm-starting may work well for small updates to the data (like the addition of one day in the example above) but can be worse than fitting from scratch if there are large changes to the data (i.e., a lot of days have been added). This is because when a large amount of history is added, the location of the changepoints will be very different between the two models, and so the parameters from the previous model may actually produce a bad trend initialization. Second, as a detail, the number of changepoints need to be consistent from one model to the next or else an error will be raised because the changepoint prior parameter `delta` will be the wrong size."
    ]

python/MANIFEST.in

@@ -4,8 +4,8 @@ include LICENSE
 include requirements.txt
 
 # Ensure in-place built models do not get included in the source dist.
-prune fbprophet/stan_model
+prune prophet/stan_model
 
 # Necessary for tests to run
-include fbprophet/tests/*.csv
-include fbprophet/tests/*.json
+include prophet/tests/*.csv
+include prophet/tests/*.json

python/README.md

@@ -21,7 +21,7 @@ Full documentation and examples available at the homepage: https://facebook.gith
 ## Installation
 
 ```shell
-pip install fbprophet
+pip install prophet
 ```
 Note:  Installation requires PyStan, which has its [own installation instructions](http://pystan.readthedocs.io/en/latest/installation_beginner.html).
 On Windows, PyStan requires a compiler so you'll need to [follow the instructions](http://pystan.readthedocs.io/en/latest/windows.html).
@@ -31,12 +31,12 @@ On Windows, PyStan requires a compiler so you'll need to [follow the instruction
 
 Simply type `make build` and if everything is fine you should be able to `make shell` or alternative jump directly to `make py-shell`. 
 
-To run the tests, inside the container `cd python/fbprophet` and then `python -m unittest`
+To run the tests, inside the container `cd python/prophet` and then `python -m unittest`
 
 ### Example usage
 
 ```python
-  >>> from fbprophet import Prophet
+  >>> from prophet import Prophet
   >>> m = Prophet()
   >>> m.fit(df)  # df is a pandas.DataFrame with 'y' and 'ds' columns
   >>> future = m.make_future_dataframe(periods=365)

python/prophet/__init__.py

@@ -5,6 +5,6 @@
 # LICENSE file in the root directory of this source tree. An additional grant 
 # of patent rights can be found in the PATENTS file in the same directory.
 
-from fbprophet.forecaster import Prophet
+from prophet.forecaster import Prophet
 
 __version__ = '1.0'

python/prophet/diagnostics.py

@@ -14,7 +14,7 @@ import concurrent.futures
 import numpy as np
 import pandas as pd
 
-logger = logging.getLogger('fbprophet')
+logger = logging.getLogger('prophet')
 
 
 def generate_cutoffs(df, horizon, initial, period):

python/prophet/forecaster.py

@@ -14,11 +14,11 @@ from datetime import timedelta, datetime
 import numpy as np
 import pandas as pd
 
-from fbprophet.make_holidays import get_holiday_names, make_holidays_df
-from fbprophet.models import StanBackendEnum
-from fbprophet.plot import (plot, plot_components)
+from prophet.make_holidays import get_holiday_names, make_holidays_df
+from prophet.models import StanBackendEnum
+from prophet.plot import (plot, plot_components)
 
-logger = logging.getLogger('fbprophet')
+logger = logging.getLogger('prophet')
 logger.setLevel(logging.INFO)
 
 

python/prophet/make_holidays.py

@@ -11,7 +11,7 @@ import warnings
 import numpy as np
 import pandas as pd
 
-import fbprophet.hdays as hdays_part2
+import prophet.hdays as hdays_part2
 import holidays as hdays_part1
 
 

python/prophet/models.py

@@ -15,7 +15,7 @@ import pkg_resources
 import os
 
 import logging
-logger = logging.getLogger('fbprophet.models')
+logger = logging.getLogger('prophet.models')
 
 
 class IStanBackend(ABC):
@@ -80,7 +80,7 @@ class CmdStanPyBackend(IStanBackend):
     def load_model(self):
         import cmdstanpy
         model_file = pkg_resources.resource_filename(
-            'fbprophet',
+            'prophet',
             'stan_model/prophet_model.bin',
         )
         return cmdstanpy.CmdStanModel(exe_file=model_file)
@@ -283,7 +283,7 @@ class PyStanBackend(IStanBackend):
     def load_model(self):
         """Load compiled Stan model"""
         model_file = pkg_resources.resource_filename(
-            'fbprophet',
+            'prophet',
             'stan_model/prophet_model.pkl',
         )
         with Path(model_file).open('rb') as f:

python/prophet/plot.py

@@ -11,9 +11,9 @@ import logging
 import numpy as np
 import pandas as pd
 
-from fbprophet.diagnostics import performance_metrics
+from prophet.diagnostics import performance_metrics
 
-logger = logging.getLogger('fbprophet.plot')
+logger = logging.getLogger('prophet.plot')
 
 
 
@@ -478,7 +478,7 @@ def plot_cross_validation_metric(
     (distance from the cutoff). This computes a specified performance metric
     for each prediction, and aggregated over a rolling window with horizon.
 
-    This uses fbprophet.diagnostics.performance_metrics to compute the metrics.
+    This uses prophet.diagnostics.performance_metrics to compute the metrics.
     Valid values of metric are 'mse', 'rmse', 'mae', 'mape', and 'coverage'.
 
     rolling_window is the proportion of data included in the rolling window of
@@ -491,7 +491,7 @@ def plot_cross_validation_metric(
 
     Parameters
     ----------
-    df_cv: The output from fbprophet.diagnostics.cross_validation.
+    df_cv: The output from prophet.diagnostics.cross_validation.
     metric: Metric name, one of ['mse', 'rmse', 'mae', 'mape', 'coverage'].
     rolling_window: Proportion of data to use for rolling average of metric.
         In [0, 1]. Defaults to 0.1.

python/prophet/serialize.py

@@ -13,8 +13,8 @@ import json
 import numpy as np
 import pandas as pd
 
-from fbprophet.forecaster import Prophet
-from fbprophet import __version__
+from prophet.forecaster import Prophet
+from prophet import __version__
 
 
 SIMPLE_ATTRIBUTES = [
@@ -100,7 +100,7 @@ def model_to_json(model):
     # Params (Dict[str, np.ndarray])
     model_json['params'] = {k: v.tolist() for k, v in model.params.items()}
     # Attributes that are skipped: stan_fit, stan_backend
-    model_json['__fbprophet_version'] = __version__
+    model_json['__prophet_version'] = __version__
     return json.dumps(model_json)
 
 

python/prophet/tests/test_diagnostics.py

@@ -17,8 +17,8 @@ import numpy as np
 import pandas as pd
 import datetime
 
-from fbprophet import Prophet
-from fbprophet import diagnostics
+from prophet import Prophet
+from prophet import diagnostics
 
 DATA_all = pd.read_csv(
     os.path.join(os.path.dirname(__file__), 'data.csv'), parse_dates=['ds']
@@ -99,7 +99,7 @@ class TestDiagnostics(TestCase):
         # cross validation  with 3 and 7 forecasts
         for args, forecasts in ((['4 days', '10 days', '115 days'], 3),
                             (['4 days', '4 days', '115 days'], 7)):
-            with patch('fbprophet.diagnostics.single_cutoff_forecast') as mock_func:
+            with patch('prophet.diagnostics.single_cutoff_forecast') as mock_func:
                 mock_func.return_value = mock_predict
                 df_cv = diagnostics.cross_validation(m, *args)
                 # check single forecast function called expected number of times

python/prophet/tests/test_prophet.py

@@ -14,7 +14,7 @@ from unittest import TestCase, skipUnless
 
 import numpy as np
 import pandas as pd
-from fbprophet import Prophet
+from prophet import Prophet
 
 
 DATA = pd.read_csv(

python/prophet/tests/test_serialize.py

@@ -15,8 +15,8 @@ from unittest import TestCase, skipUnless
 
 import numpy as np
 import pandas as pd
-from fbprophet import Prophet
-from fbprophet.serialize import model_to_json, model_from_json, PD_SERIES, PD_DATAFRAME
+from prophet import Prophet
+from prophet.serialize import model_to_json, model_from_json, PD_SERIES, PD_DATAFRAME
 
 
 DATA = pd.read_csv(
@@ -41,7 +41,7 @@ class TestSerialize(TestCase):
         # Make sure json doesn't get too large in the future
         self.assertTrue(len(model_str) < 200000)
         z = json.loads(model_str)
-        self.assertEqual(z['__fbprophet_version'], '1.0')
+        self.assertEqual(z['__prophet_version'], '1.0')
 
         m2 = model_from_json(model_str)
 
@@ -140,10 +140,10 @@ class TestSerialize(TestCase):
 
     def test_backwards_compatibility(self):
         old_versions = {
-            '0.6.1.dev0': 29.3669923968994,
-            '0.7.1': 29.282810844704414,
+            '0.6.1.dev0': (29.3669923968994, 'fb'),
+            '0.7.1': (29.282810844704414, 'fb'),
         }
-        for v, pred_val in old_versions.items():
+        for v, (pred_val, v_str) in old_versions.items():
             fname = os.path.join(
                 os.path.dirname(__file__),
                 'serialized_model_v{}.json'.format(v)
@@ -152,7 +152,7 @@ class TestSerialize(TestCase):
                 model_str = json.load(fin)
             # Check that deserializes
             m = model_from_json(model_str)
-            self.assertEqual(json.loads(model_str)['__fbprophet_version'], v)
+            self.assertEqual(json.loads(model_str)[f'__{v_str}prophet_version'], v)
             # Predict
             future = m.make_future_dataframe(10)
             fcst = m.predict(future)

python/prophet/tests/test_utilities.py

@@ -13,8 +13,8 @@ from unittest import TestCase
 
 import numpy as np
 import pandas as pd
-from fbprophet import Prophet
-from fbprophet.utilities import regressor_coefficients
+from prophet import Prophet
+from prophet.utilities import regressor_coefficients
 
 
 DATA = pd.read_csv(

python/scripts/generate_holidays_file.py

@@ -16,8 +16,8 @@ import pandas as pd
 import numpy as np
 
 import holidays as hdays_part1
-import fbprophet.hdays as hdays_part2
-from fbprophet.make_holidays import make_holidays_df
+import prophet.hdays as hdays_part2
+from prophet.make_holidays import make_holidays_df
 
 
 def utf8_to_ascii(text):

python/setup.py

@@ -24,16 +24,16 @@ if platform.platform().startswith('Win'):
     PLATFORM = 'win'
 
 MODEL_DIR = os.path.join('stan', PLATFORM)
-MODEL_TARGET_DIR = os.path.join('fbprophet', 'stan_model')
+MODEL_TARGET_DIR = os.path.join('prophet', 'stan_model')
 
 
 def get_backends_from_env() -> List[str]:
-    from fbprophet.models import StanBackendEnum
+    from prophet.models import StanBackendEnum
     return os.environ.get("STAN_BACKEND", StanBackendEnum.PYSTAN.name).split(",")
 
 
 def build_models(target_dir):
-    from fbprophet.models import StanBackendEnum
+    from prophet.models import StanBackendEnum
     for backend in get_backends_from_env():
         StanBackendEnum.get_backend_class(backend).build_model(target_dir, MODEL_DIR)
 
@@ -121,7 +121,7 @@ with open('requirements.txt', 'r') as f:
     install_requires = f.read().splitlines()
 
 setup(
-    name='fbprophet',
+    name='prophet',
     version='1.0',
     description='Automatic Forecasting Procedure',
     url='https://facebook.github.io/prophet/',
@@ -140,7 +140,7 @@ setup(
         'develop': DevelopCommand,
         'test': TestCommand,
     },
-    test_suite='fbprophet.tests',
+    test_suite='prophet.tests',
     classifiers=[
         'Programming Language :: Python',
         'Programming Language :: Python :: 3',

python_shim/LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) Facebook, Inc. and its affiliates.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

python_shim/MANIFEST.in

@@ -0,0 +1,4 @@
+include LICENSE
+include requirements.txt
+
+include fbprophet/tests/DATA.csv

python_shim/README.md

@@ -0,0 +1,5 @@
+# Prophet: Automatic Forecasting Procedure
+
+As of v1.0, Prophet has moved to use the name "[prophet](https://pypi.org/project/prophet/)" on PyPI and not the original name of "fbprophet". This package is now just a shim for using the prophet package. Please change references in your code to use "prophet" instead of "fbprophet".
+
+See https://facebook.github.io/prophet/ for full documentation.

python_shim/fbprophet/__init__.py

@@ -0,0 +1,15 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+
+# This source code is licensed under the MIT license found in the
+# LICENSE file in the root directory of this source tree.
+
+import logging
+
+from prophet.forecaster import Prophet
+
+logger = logging.getLogger('fbprophet')
+
+logger.warning(
+    'As of v1.0, the package name has changed from "fbprophet" to "prophet". '
+    'Please update references in your code accordingly.'
+)

python_shim/fbprophet/diagnostics.py

@@ -0,0 +1,6 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+
+# This source code is licensed under the MIT license found in the
+# LICENSE file in the root directory of this source tree.
+
+from prophet.diagnostics import *

python_shim/fbprophet/forecaster.py

@@ -0,0 +1,6 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+
+# This source code is licensed under the MIT license found in the
+# LICENSE file in the root directory of this source tree.
+
+from prophet.forecaster import *

python_shim/fbprophet/hdays.py

@@ -0,0 +1,6 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+
+# This source code is licensed under the MIT license found in the
+# LICENSE file in the root directory of this source tree.
+
+from prophet.hdays import *

python_shim/fbprophet/make_holidays.py

@@ -0,0 +1,6 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+
+# This source code is licensed under the MIT license found in the
+# LICENSE file in the root directory of this source tree.
+
+from prophet.make_holidays import *

python_shim/fbprophet/models.py

@@ -0,0 +1,6 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+
+# This source code is licensed under the MIT license found in the
+# LICENSE file in the root directory of this source tree.
+
+from prophet.models import *

python_shim/fbprophet/plot.py

@@ -0,0 +1,6 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+
+# This source code is licensed under the MIT license found in the
+# LICENSE file in the root directory of this source tree.
+
+from prophet.plot import *

python_shim/fbprophet/serialize.py

@@ -0,0 +1,6 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+
+# This source code is licensed under the MIT license found in the
+# LICENSE file in the root directory of this source tree.
+
+from prophet.serialize import *

python_shim/fbprophet/tests/data.csv

@@ -0,0 +1,102 @@
+ds,y
+2012-05-18,38.23
+2012-05-21,34.03
+2012-05-22,31.0
+2012-05-23,32.0
+2012-05-24,33.03
+2012-05-25,31.91
+2012-05-29,28.84
+2012-05-30,28.19
+2012-05-31,29.6
+2012-06-01,27.72
+2012-06-04,26.9
+2012-06-05,25.87
+2012-06-06,26.81
+2012-06-07,26.31
+2012-06-08,27.1
+2012-06-11,27.01
+2012-06-12,27.4
+2012-06-13,27.27
+2012-06-14,28.29
+2012-06-15,30.01
+2012-06-18,31.41
+2012-06-19,31.91
+2012-06-20,31.6
+2012-06-21,31.84
+2012-06-22,33.05
+2012-06-25,32.06
+2012-06-26,33.1
+2012-06-27,32.23
+2012-06-28,31.36
+2012-06-29,31.1
+2012-07-02,30.77
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python_shim/fbprophet/tests/test_package.py

@@ -0,0 +1,33 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+
+# This source code is licensed under the MIT license found in the
+# LICENSE file in the root directory of this source tree.
+
+import os
+from unittest import TestCase
+
+import pandas as pd
+from fbprophet import Prophet
+from fbprophet.diagnostics import cross_validation
+import fbprophet.plot as plot
+
+
+DATA = pd.read_csv(
+    os.path.join(os.path.dirname(__file__), 'data.csv'),
+    parse_dates=['ds'],
+)
+
+
+class TestFbprophet(TestCase):
+
+    def test_shim(self):
+        m = Prophet()
+        m.fit(DATA)
+        future = m.make_future_dataframe(10, include_history=False)
+        fcst = m.predict(future)
+ 
+        df_cv = cross_validation(
+            model=m, horizon='4 days', period='10 days', initial='115 days',
+        )
+
+        fig = plot.plot_forecast_component(m=m, fcst=fcst, name='weekly')

python_shim/requirements.txt

@@ -0,0 +1 @@
+prophet>=1.0

python_shim/setup.py

@@ -0,0 +1,37 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+
+# This source code is licensed under the MIT license found in the
+# LICENSE file in the root directory of this source tree.
+
+from setuptools import setup, find_packages
+
+
+with open('README.md', 'r', encoding='utf-8') as f:
+    long_description = f.read()
+
+with open('requirements.txt', 'r') as f:
+    install_requires = f.read().splitlines()
+
+setup(
+    name='fbprophet',
+    version='1.0',
+    description='Automatic Forecasting Procedure',
+    url='https://facebook.github.io/prophet/',
+    author='Sean J. Taylor <sjtz@pm.me>, Ben Letham <bletham@fb.com>',
+    author_email='sjtz@pm.me',
+    license='MIT',
+    packages=find_packages(),
+    setup_requires=[],
+    install_requires=install_requires,
+    python_requires='>=3',
+    zip_safe=False,
+    include_package_data=True,
+    test_suite='fbprophet.tests',
+    classifiers=[
+        'Programming Language :: Python',
+        'Programming Language :: Python :: 3',
+        'Programming Language :: Python :: 3.7',
+    ],
+    long_description=long_description,
+    long_description_content_type='text/markdown',
+)