Use optional_imports instead of _*_imported.

Author: theengineear

plotly/figure_factory/_annotated_heatmap.py

@@ -1,12 +1,11 @@
 from __future__ import absolute_import
 
-from plotly import exceptions
+from plotly import exceptions, optional_imports
 from plotly.figure_factory import utils
 from plotly.graph_objs import graph_objs
-from plotly.tools import _numpy_imported
 
-if _numpy_imported:
-    import numpy as np
+# Optional imports, may be None for users that only use our core functionality.
+np = optional_imports.get_module('numpy')
 
 
 def validate_annotated_heatmap(z, x, y, annotation_text):
@@ -206,7 +205,7 @@ def get_z_mid(self):
 
         :rtype (float) z_avg: average val from z matrix
         """
-        if _numpy_imported and isinstance(self.z, np.ndarray):
+        if np and isinstance(self.z, np.ndarray):
             z_min = np.amin(self.z)
             z_max = np.amax(self.z)
         else:

plotly/figure_factory/_dendrogram.py

@@ -4,23 +4,14 @@
 
 from collections import OrderedDict
 
-from plotly import exceptions
+from plotly import exceptions, optional_imports
 from plotly.graph_objs import graph_objs
-from plotly.tools import (_numpy_imported, _scipy_imported,
-                          _scipy__cluster__hierarchy_imported,
-                          _scipy__spatial_imported)
 
-if _numpy_imported:
-    import numpy as np
-
-if _scipy_imported:
-    import scipy as scp
-
-if _scipy__cluster__hierarchy_imported:
-    import scipy.cluster.hierarchy as sch
-
-if _scipy__spatial_imported:
-    import scipy.spatial as scs
+# Optional imports, may be None for users that only use our core functionality.
+np = optional_imports.get_module('numpy')
+scp = optional_imports.get_module('scipy')
+sch = optional_imports.get_module('scipy.cluster.hierarchy')
+scs = optional_imports.get_module('scipy.spatial')
 
 
 def create_dendrogram(X, orientation="bottom", labels=None,
@@ -82,10 +73,7 @@ def create_dendrogram(X, orientation="bottom", labels=None,
     url = py.plot(fig, filename='pandas-dendrogram')
     ```
     """
-    dependencies = (_scipy_imported and _scipy__spatial_imported and
-                    _scipy__cluster__hierarchy_imported)
-
-    if dependencies is False:
+    if not scp or not scs or not sch:
         raise ImportError("FigureFactory.create_dendrogram requires scipy, \
                             scipy.spatial and scipy.hierarchy")
 

plotly/figure_factory/_distplot.py

@@ -1,19 +1,14 @@
 from __future__ import absolute_import
 
-from plotly import exceptions
+from plotly import exceptions, optional_imports
 from plotly.figure_factory import utils
 from plotly.graph_objs import graph_objs
-from plotly.tools import _numpy_imported, _pandas_imported, _scipy_imported
 
-if _numpy_imported:
-    import numpy as np
-
-if _pandas_imported:
-    import pandas as pd
-
-if _scipy_imported:
-    import scipy
-    import scipy.stats
+# Optional imports, may be None for users that only use our core functionality.
+np = optional_imports.get_module('numpy')
+pd = optional_imports.get_module('pandas')
+scipy = optional_imports.get_module('scipy')
+scipy_stats = optional_imports.get_module('scipy.stats')
 
 
 DEFAULT_HISTNORM = 'probability density'
@@ -29,9 +24,9 @@ def validate_distplot(hist_data, curve_type):
         'normal').
     """
     hist_data_types = (list,)
-    if _numpy_imported:
+    if np:
         hist_data_types += (np.ndarray,)
-    if _pandas_imported:
+    if pd:
         hist_data_types += (pd.core.series.Series,)
 
     if not isinstance(hist_data[0], hist_data_types):
@@ -47,7 +42,7 @@ def validate_distplot(hist_data, curve_type):
         raise exceptions.PlotlyError("curve_type must be defined as "
                                      "'kde' or 'normal'")
 
-    if _scipy_imported is False:
+    if not scipy:
         raise ImportError("FigureFactory.create_distplot requires scipy")
 
 
@@ -312,7 +307,7 @@ def make_kde(self):
             self.curve_x[index] = [self.start[index] +
                                    x * (self.end[index] - self.start[index])
                                    / 500 for x in range(500)]
-            self.curve_y[index] = (scipy.stats.gaussian_kde
+            self.curve_y[index] = (scipy_stats.gaussian_kde
                                    (self.hist_data[index])
                                    (self.curve_x[index]))
 
@@ -345,12 +340,12 @@ def make_normal(self):
         sd = [None] * self.trace_number
 
         for index in range(self.trace_number):
-            mean[index], sd[index] = (scipy.stats.norm.fit
+            mean[index], sd[index] = (scipy_stats.norm.fit
                                       (self.hist_data[index]))
             self.curve_x[index] = [self.start[index] +
                                    x * (self.end[index] - self.start[index])
                                    / 500 for x in range(500)]
-            self.curve_y[index] = scipy.stats.norm.pdf(
+            self.curve_y[index] = scipy_stats.norm.pdf(
                 self.curve_x[index], loc=mean[index], scale=sd[index])
 
             if self.histnorm == ALTERNATIVE_HISTNORM:

plotly/figure_factory/_gantt.py

@@ -2,12 +2,10 @@
 
 from numbers import Number
 
-from plotly import exceptions
+from plotly import exceptions, optional_imports
 from plotly.figure_factory import utils
-from plotly.tools import _pandas_imported
 
-if _pandas_imported:
-    import pandas as pd
+pd = optional_imports.get_module('pandas')
 
 REQUIRED_GANTT_KEYS = ['Task', 'Start', 'Finish']
 
@@ -16,7 +14,7 @@ def validate_gantt(df):
     """
     Validates the inputted dataframe or list
     """
-    if _pandas_imported and isinstance(df, pd.core.frame.DataFrame):
+    if pd and isinstance(df, pd.core.frame.DataFrame):
         # validate that df has all the required keys
         for key in REQUIRED_GANTT_KEYS:
             if key not in df:

plotly/figure_factory/_scatterplot.py

@@ -1,12 +1,11 @@
 from __future__ import absolute_import
 
-from plotly import exceptions
+from plotly import exceptions, optional_imports
 from plotly.figure_factory import utils
 from plotly.graph_objs import graph_objs
-from plotly.tools import _pandas_imported, make_subplots
+from plotly.tools import make_subplots
 
-if _pandas_imported:
-    import pandas as pd
+pd = optional_imports.get_module('pandas')
 
 DIAG_CHOICES = ['scatter', 'histogram', 'box']
 VALID_COLORMAP_TYPES = ['cat', 'seq']
@@ -88,7 +87,7 @@ def validate_scatterplotmatrix(df, index, diag, colormap_type, **kwargs):
     :raises: (PlotlyError) If kwargs contains 'size', 'color' or
         'colorscale'
     """
-    if _pandas_imported is False:
+    if not pd:
         raise ImportError("FigureFactory.scatterplotmatrix requires "
                           "a pandas DataFrame.")
 

plotly/figure_factory/_streamline.py

@@ -2,13 +2,11 @@
 
 import math
 
-from plotly import exceptions
+from plotly import exceptions, optional_imports
 from plotly.figure_factory import utils
 from plotly.graph_objs import graph_objs
-from plotly.tools import _numpy_imported
 
-if _numpy_imported:
-    import numpy as np
+np = optional_imports.get_module('numpy')
 
 
 def validate_streamline(x, y):
@@ -24,7 +22,7 @@ def validate_streamline(x, y):
     :raises: (PlotlyError) If x is not evenly spaced.
     :raises: (PlotlyError) If y is not evenly spaced.
     """
-    if _numpy_imported is False:
+    if np is False:
         raise ImportError("FigureFactory.create_streamline requires numpy")
     for index in range(len(x) - 1):
         if ((x[index + 1] - x[index]) - (x[1] - x[0])) > .0001:

plotly/figure_factory/_table.py

@@ -1,11 +1,9 @@
 from __future__ import absolute_import
 
-from plotly import exceptions
+from plotly import exceptions, optional_imports
 from plotly.graph_objs import graph_objs
-from plotly.tools import _pandas_imported
 
-if _pandas_imported:
-    import pandas as pd
+pd = optional_imports.get_module('pandas')
 
 
 def validate_table(table_text, font_colors):
@@ -138,7 +136,7 @@ class _Table(object):
     """
     def __init__(self, table_text, colorscale, font_colors, index,
                  index_title, annotation_offset, **kwargs):
-        if _pandas_imported and isinstance(table_text, pd.DataFrame):
+        if pd and isinstance(table_text, pd.DataFrame):
             headers = table_text.columns.tolist()
             table_text_index = table_text.index.tolist()
             table_text = table_text.values.tolist()

plotly/figure_factory/_trisurf.py

@@ -1,11 +1,9 @@
 from __future__ import absolute_import
 
-from plotly import colors, exceptions
+from plotly import colors, exceptions, optional_imports
 from plotly.graph_objs import graph_objs
-from plotly.tools import _numpy_imported
 
-if _numpy_imported:
-    import numpy as np
+np = optional_imports.get_module('numpy')
 
 
 def map_face2color(face, colormap, scale, vmin, vmax):
@@ -81,7 +79,7 @@ def trisurf(x, y, z, simplices, show_colorbar, edges_color, scale,
     Refer to FigureFactory.create_trisurf() for docstring
     """
     # numpy import check
-    if _numpy_imported is False:
+    if not np:
         raise ImportError("FigureFactory._trisurf() requires "
                           "numpy imported.")
     points3D = np.vstack((x, y, z)).T

plotly/figure_factory/_violin.py

@@ -2,20 +2,14 @@
 
 from numbers import Number
 
-from plotly import exceptions
+from plotly import exceptions, optional_imports
 from plotly.figure_factory import utils
 from plotly.graph_objs import graph_objs
-from plotly.tools import (_numpy_imported, _pandas_imported, _scipy_imported,
-                          make_subplots)
+from plotly.tools import make_subplots
 
-if _pandas_imported:
-    import pandas as pd
-
-if _numpy_imported:
-    import numpy as np
-
-if _scipy_imported:
-    from scipy import stats
+pd = optional_imports.get_module('pandas')
+np = optional_imports.get_module('numpy')
+scipy_stats = optional_imports.get_module('scipy.stats')
 
 
 def calc_stats(data):
@@ -178,7 +172,7 @@ def violinplot(vals, fillcolor='#1f77b4', rugplot=True):
     d2 = calc_stats(vals)['d2']
 
     # kernel density estimation of pdf
-    pdf = stats.gaussian_kde(vals)
+    pdf = scipy_stats.gaussian_kde(vals)
     # grid over the data interval
     xx = np.linspace(vals_min, vals_max, 100)
     # evaluate the pdf at the grid xx
@@ -554,7 +548,7 @@ def create_violin(data, data_header=None, group_header=None, colors=None,
                 raise exceptions.PlotlyError("If data is a list, it must "
                                              "contain only numbers.")
 
-        if _pandas_imported and isinstance(data, pd.core.frame.DataFrame):
+        if pd and isinstance(data, pd.core.frame.DataFrame):
             if data_header is None:
                 raise exceptions.PlotlyError("data_header must be the "
                                              "column name with the "

plotly/offline/offline.py

@@ -15,21 +15,12 @@
 from requests.compat import json as _json
 
 import plotly
-from plotly import tools, utils
+from plotly import optional_imports, tools, utils
 from plotly.exceptions import PlotlyError
 
-try:
-    import IPython
-    from IPython.display import HTML, display
-    _ipython_imported = True
-except ImportError:
-    _ipython_imported = False
-
-try:
-    import matplotlib
-    _matplotlib_imported = True
-except ImportError:
-    _matplotlib_imported = False
+ipython = optional_imports.get_module('IPython')
+ipython_display = optional_imports.get_module('IPython.display')
+matplotlib = optional_imports.get_module('matplotlib')
 
 __PLOTLY_OFFLINE_INITIALIZED = False
 
@@ -112,7 +103,7 @@ def init_notebook_mode(connected=False):
     your notebook, resulting in much larger notebook sizes compared to the case
     where `connected=True`.
     """
-    if not _ipython_imported:
+    if not ipython:
         raise ImportError('`iplot` can only run inside an IPython Notebook.')
 
     global __PLOTLY_OFFLINE_INITIALIZED
@@ -149,7 +140,7 @@ def init_notebook_mode(connected=False):
             '</script>'
             '').format(script=get_plotlyjs())
 
-    display(HTML(script_inject))
+    ipython_display.display(ipython_display.HTML(script_inject))
     __PLOTLY_OFFLINE_INITIALIZED = True
 
 
@@ -333,7 +324,7 @@ def iplot(figure_or_data, show_link=True, link_text='Export to plot.ly',
             'plotly.offline.init_notebook_mode() '
             '# run at the start of every ipython notebook',
         ]))
-    if not tools._ipython_imported:
+    if not ipython:
         raise ImportError('`iplot` can only run inside an IPython Notebook.')
 
     config = {}
@@ -344,7 +335,7 @@ def iplot(figure_or_data, show_link=True, link_text='Export to plot.ly',
         figure_or_data, config, validate, '100%', 525, True
     )
 
-    display(HTML(plot_html))
+    ipython_display.display(ipython_display.HTML(plot_html))
 
     if image:
         if image not in __IMAGE_FORMATS:
@@ -360,7 +351,7 @@ def iplot(figure_or_data, show_link=True, link_text='Export to plot.ly',
         # allow time for the plot to draw
         time.sleep(1)
         # inject code to download an image of the plot
-        display(HTML(script))
+        ipython_display.display(ipython_display.HTML(script))
 
 
 def plot(figure_or_data, show_link=True, link_text='Export to plot.ly',
@@ -690,7 +681,7 @@ def enable_mpl_offline(resize=False, strip_style=False,
     """
     init_notebook_mode()
 
-    ip = IPython.core.getipython.get_ipython()
+    ip = ipython.core.getipython.get_ipython()
     formatter = ip.display_formatter.formatters['text/html']
     formatter.for_type(matplotlib.figure.Figure,
                        lambda fig: iplot_mpl(fig, resize, strip_style, verbose,