bokeh.util¶

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:	attr (str) – an attribute name on this object callback (callable) – a callback function to register
Returns:	None

remove_on_change(attr, *callbacks)¶

Remove a callback from this object

trigger(attr, old, new)¶

Trigger callbacks for attr on this object.

Parameters:	attr (str) – old (object) – new (object) –
Returns:	None

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:	mod_name (str) – name of the required module to try to import error_msg (str) – error message to raise when the module is missing
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 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. (refer to klass arguments specification details) (**kws) –
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(result)¶

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