bokeh.util
¶
Provide a collection of general utilities usefil for implementing Bokeh functionality.
bokeh.util.browser
¶
-
view
(location, browser=None, new='same', autoraise=True)¶ Opens a browser to view the specified location.
Parameters: - location (str) – Location to open If location does not begin with “http:” it is assumed to be a file path on the local filesystem.
- browser (str) – what browser to use
- new (str) –
How to open the location. Valid values are:
"same"
- open in the current tab"tab"
- open a new tab in the current window"window"
- open in a new window - autoraise (bool) – Whether to raise the new location
Returns: None
bokeh.util.callback_manager
¶
Provides CallbackManager
mixin class for adding an on_change
callback interface to classes.
-
class
CallbackManager
(*args, **kw)¶ A mixin class to provide an interface for registering and triggering callbacks.
-
on_change
(attr, *callbacks)¶ Add a callback on this object to trigger when
attr
changes.Parameters: Returns: None
-
remove_on_change
(attr, *callbacks)¶ Remove a callback from this object
-
bokeh.util.dependencies
¶
Utilities for checking dependencies
-
import_optional
(mod_name)¶ Attempt to import an optional dependency.
Silently returns None if the requested module is not available.
Parameters: mod_name (str) – name of the optional module to try to import Returns: imported module or None, if import fails
-
import_required
(mod_name, error_msg)¶ Attempt to import a required dependency.
Raises a RuntimeError if the requested module is not available.
Parameters: Returns: imported module
Raises: RuntimeError
bokeh.util.deprecate
¶
Deprecation framework for Bokeh.
To mark a method or function as being deprecated do this:
from bokeh.util.deprecate import deprecated
@deprecated(("Bokeh 0.11.0", "other_thing")
def bad_thing(self, first, second):
''' Docstring for bad_thing.
'''
pass
The newly-decorated bad_thing
will issue a warning when called. It will
also have a deprecation notice appended to its docstring.
To mark an entire module as deprecated do this:
from bokeh.util.deprecate import deprecated_module
deprecated_module('foo.bar', '0.11', 'use baz.quux instead')
The module foo.bar
will issue a warning whenever it is imported.
-
class
BokehDeprecationWarning
¶ A specific
DeprecationWarning
subclass for Bokeh deprecations. Used to selectively filter Bokeh deprecations for unconditional display.
bokeh.util.functions
¶
utilities for working with functions
-
class
cached_property
(func)¶ A property that is only computed once per instance and then replaces itself with an ordinary attribute. Deleting the attribute resets the property.
Source: https://github.com/bottlepy/bottle/commit/fa7733e075da0d790d809aa3d2f53071897e6f76
bokeh.util.future
¶
Utilities for Py2/Py3 interop.
-
with_metaclass
(meta, *bases)¶ Add metaclasses in both Python 2 and Python 3.
Function from jinja2/_compat.py. License: BSD.
Use it like this:
class BaseForm(object): pass class FormType(type): pass class Form(with_metaclass(FormType, BaseForm)): pass
This requires a bit of explanation: the basic idea is to make a dummy metaclass for one level of class instantiation that replaces itself with the actual metaclass. Because of internal type checks we also need to make sure that we downgrade the custom metaclass for one level to something closer to type (that’s why __call__ and __init__ comes back from type etc.).
This has the advantage over six.with_metaclass of not introducing dummy classes into the final MRO.
bokeh.util.logconfig
¶
Configure the logging system for Bokeh.
By default, logging is not configured, to allow users of Bokeh to have full
control over logging policy. However, it is useful to be able to enable
logging arbitrarily during when developing Bokeh. This can be accomplished
by setting the environment variable BOKEH_PY_LOG_LEVEL
. Valid values are,
in order of increasing severity:
debug
info
warn
error
fatal
none
The default logging level is none
.
bokeh.util.notebook
¶
Functions useful for loading Bokeh code and data in IPython notebooks.
-
get_comms
(target_name)¶ Create a Jupyter comms object for a specific target, that can be used to update Bokeh documents in the notebook.
Parameters: target_name (str) – the target name the Comms object should connect to - Returns
- Jupyter Comms
-
load_notebook
(resources=None, verbose=False, hide_banner=False)¶ Prepare the IPython notebook for displaying Bokeh plots.
Parameters: - resources (Resource, optional) – how and where to load BokehJS from (default: CDN)
- verbose (bool, optional) – whether to report detailed settings (default: False)
- hide_banner (bool, optional) – whether to hide the Bokeh banner (default: False)
Warning
Clearing the output cell containing the published BokehJS resources HTML code may cause Bokeh CSS styling to be removed.
Returns: None
-
publish_display_data
(data, source='bokeh')¶ Compatibility wrapper for IPython
publish_display_data
Later versions of IPython remove the
source
(first) argument. This function insulates Bokeh library code from this change.Parameters: - source (str, optional) – the source arg for IPython (default: “bokeh”)
- data (dict) – the data dict to pass to
publish_display_data
Typically has the form{'text/html': html}
bokeh.util.paths
¶
-
bokehjsdir
(dev=False)¶ Get the location of the bokehjs source files. If dev is True, the files in bokehjs/build are preferred. Otherwise uses the files in bokeh/server/static.
-
serverdir
()¶ Get the location of the server subpackage
bokeh.util.platform
¶
Functions for testing what kind of Python or Python environment is in use.
-
is_notebook
()¶ Test whether we are inside an IPython notebook.
- Returns
- True if we are inside a notebook, otherwise False
-
is_py3
()¶ Test whether we are running Python 3.
- Returns
- True if we are running Python 3, otherwise False
-
is_pypy
()¶ Test whether we are running PyPy.
- Returns
- True if we are inside PyPy, otherwise False
bokeh.util.serialization
¶
Functions for helping with serialization and deserialization of Bokeh objects.
-
make_id
()¶ Return a new unique ID for a Bokeh object.
Normally this function will return UUIDs to use for identifying Bokeh objects. This is especally important for Bokeh objects stored on a Bokeh server. However, it is convenient to have more human-readable IDs during development, so this behavior can be overridden by setting the environment variable
BOKEH_SIMPLE_IDS=yes
.
-
transform_array
(obj)¶ Transform arrays into lists of json safe types also handles pandas series, and replacing nans and infs with strings
-
transform_column_source_data
(data)¶ iterate through the data of a ColumnSourceData object replacing non-JSON-compliant objects with compliant ones
-
transform_numerical_array
(obj)¶ handles nans/inf conversion
-
transform_series
(obj)¶ transforms pandas series into array of values
-
traverse_data
(datum, is_numpy=True, use_numpy=True)¶ recursively dig until a flat list is found if numpy is available convert the flat list to a numpy array and send off to transform_array() to handle nan, inf, -inf otherwise iterate through items in array converting non-json items
Parameters: - datum (list) – a list of values or lists
- is_numpy – True if numpy is present (see imports)
- use_numpy – toggle numpy as a dependency for testing purposes
bokeh.util.session_id
¶
Utilities for generating and manipulating session IDs.
A session ID would typically be associated with each browser tab viewing an application or plot. Each session has its own state separate from any other sessions hosted by the server.
-
check_session_id_signature
(session_id, secret_key=None, signed=False)¶ Check the signature of a session ID, returning True if it’s valid.
The server uses this function to check whether a session ID was generated with the correct secret key. If signed sessions are disabled, this function always returns True.
Parameters: - session_id (str) – The session ID to check
- secret_key (str, optional) – Secret key (default: value of ‘BOKEH_SECRET_KEY’ env var)
- signed (bool, optional) – Whether to check anything (default: value of ‘BOKEH_SIGN_SESSIONS’ env var)
-
generate_secret_key
()¶ Generate a new securely-generated secret key appropriate for SHA-256 HMAC signatures. This key could be used to sign Bokeh server session IDs for example.
-
generate_session_id
(secret_key=None, signed=False)¶ Generate a random session ID.
Typically, each browser tab connected to a Bokeh application has its own session ID. In production deployments of a Bokeh app, session IDs should be random and unguessable - otherwise users of the app could interfere with one another.
If session IDs are signed with a secret key, the server can verify that the generator of the session ID was “authorized” (the generator had to know the secret key). This can be used to have a separate process, such as another web application, which generates new sessions on a Bokeh server. This other process may require users to log in before redirecting them to the Bokeh server with a valid session ID, for example.
Parameters: - secret_key (str, optional) – Secret key (default: value of ‘BOKEH_SECRET_KEY’ env var)
- signed (bool, optional) – Whether to sign the session ID (default: value of ‘BOKEH_SIGN_SESSIONS’ env var)
bokeh.util.string
¶
Functions useful for string manipulations or encoding.
-
decode_utf8
(u)¶ Decode a sequence of bytes to a UTF-8 string
Parameters: u (str) – the bytes to decode Returns: UTF-8 string
-
encode_utf8
(u)¶ Encode a UTF-8 string to a sequence of bytes.
Parameters: u (str) – the string to encode Returns: bytes
-
nice_join
(seq, sep=', ')¶ Join together sequences of strings into English-friendly phrases using the conjunction
or
when appropriate.Parameters: - seq (seq[str]) – a sequence of strings to nicely join
- sep (str, optional) – a sequence delimiter to use (default: ”, ”)
Returns: a joined string
Examples
>>> nice_join(["a", "b", "c"]) 'a, b or c'
-
snakify
(name, sep='_')¶ Convert CamelCase to snake_case.
bokeh.util.testing
¶
Functions to help with testing Bokeh and reporting issues.
-
create_chart
(klass, values, compute_values=True, **kws)¶ Create a new chart class instance with values and the extra kws keyword parameters.
Parameters: - klass (class) – chart class to be created
- values (iterable) – chart data series
- compute_values (bool) – if == True underlying chart attributes (e.g., data, ranges, source, etc.) are computed by calling _setup_show, _prepare_show and _show_teardown methods.
- **kws (refer to klass arguments specification details) –
Returns: klass chart instance
Return type: _chart
-
print_versions
()¶ Print the versions for Bokeh and the current Python and OS.
Returns: None
-
runtests
(args=None)¶ Run the Bokeh tests under the bokeh python directory using pytest.
Does not run tests from bokehjs or examples.
Parameters: args (list, optional) – command line arguments accepted by py.test
e.g. args=[‘-s’, ‘-k charts’] prevents capture of standard out and only runs tests that match charts. For more py.test options see http://pytest.org/latest/usage.html#usage.
Returns: pytest exitcode Return type: int
-
skipIfPy3
(message)¶ unittest decorator to skip a test for Python 3
-
skipIfPyPy
(message)¶ unittest decorator to skip a test for PyPy
bokeh.util.tornado
¶
Internal utils related to Tornado
-
yield_for_all_futures
(*args, **kwargs)¶ Converts result into a Future by collapsing any futures inside result.
If result is a Future we yield until it’s done, then if the value inside the Future is another Future we yield until it’s done as well, and so on.
bokeh.util.version
¶
Provide a version for the Bokeh library.
This module uses versioneer to manage version strings. During development, versioneer will compute a version string from the current git revision. For packaged releases based off tags, the version string is hard coded in the files packaged for distribution.
-
__version__
¶ the version string for this installed Bokeh library
Note
It is also possible to override the normal version computation by creating
a special __conda_version__.py
file at the top level of the library,
that defines a conda_version
attribute. This facility is not normally
of interest to anyone except package maintainers.