Provide a collection of general utilities useful for implementing Bokeh functionality.
bokeh.util.browser
Utility functions for helping with operations involving browsers.
DummyWebBrowser
A “no-op” web-browser controller.
open
Receive standard arguments and take no action.
get_browser_controller
Return a browser controller.
browser (str or None) –
browser name, or None (default: None) If passed the string 'none', a dummy web browser controller is returned
None
'none'
Otherwise, use the value to select an appropriate controller using the webbrowser standard library module. In the value is None then a system default is used.
webbrowser
a web browser controller
controller
view
Open a browser to view the specified location.
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 or None) – what browser to use (default: None) If None, use the system default browser.
new (str) –
How to open the location. Valid values are:
'same' - open in the current tab
'same'
'tab' - open a new tab in the current window
'tab'
'window' - open in a new window
'window'
autoraise (bool) – Whether to automatically raise the location in a new browser window (default: True)
bokeh.util.callback_manager
Provides PropertyCallbackManager and EventCallbackManager mixin classes for adding on_change and on_event callback interfaces to classes.
PropertyCallbackManager
EventCallbackManager
on_change
on_event
A mixin class to provide an interface for registering and triggering event callbacks on the Python side.
A mixin class to provide an interface for registering and triggering callbacks.
Add a callback on this object to trigger when attr changes.
attr
attr (str) – an attribute name on this object
callback (callable) – a callback function to register
remove_on_change
Remove a callback from this object
trigger
Trigger callbacks for attr on this object.
attr (str) –
old (object) –
new (object) –
bokeh.util.compiler
Provide functions and classes to help with various JS and CSS compilation.
CompilationError
A RuntimeError subclass for reporting JS compilation errors.
RuntimeError
AttrDict
Provide a dict subclass that supports access by named attributes.
CustomModel
Represent a custom (user-defined) Bokeh model.
FromFile
A custom model implementation read from a separate source file.
path (str) – The path to the file containing the extension source code
Implementation
Base class for representing Bokeh custom model implementations.
Inline
Base class for representing Bokeh custom model implementations that may be given as inline code in some language.
code (str) – The source code for the implementation
file (str, optional) – A file path to a file containing the source text (default: None)
JavaScript
An implementation for a Bokeh custom model in JavaScript
Example
class MyExt(Model): __implementation__ = JavaScript(""" <JavaScript code> """)
Less
An implementation of a Less CSS style sheet.
TypeScript
An implementation for a Bokeh custom model in TypeScript
class MyExt(Model): __implementation__ = TypeScript(""" <TypeScript code> """)
bundle_all_models
Create a bundle of all models.
bundle_models
Create a bundle of selected models.
calc_cache_key
Generate a key to cache a custom extension implementation with.
There is no metadata other than the Model classes, so this is the only base to generate a cache key.
We build the model keys from the list of model.full_name. This is not ideal but possibly a better solution can be found found later.
model.full_name
get_cache_hook
Returns the current cache hook used to look up the compiled code given the CustomModel and Implementation
set_cache_hook
Sets a compiled model cache hook used to look up the compiled code given the CustomModel and Implementation
bokeh.util.dependencies
Utilities for checking dependencies
import_optional
Attempt to import an optional dependency.
Silently returns None if the requested module is not available.
mod_name (str) – name of the optional module to try to import
imported module or None, if import fails
import_required
Attempt to import a required dependency.
Raises a RuntimeError if the requested module is not available.
mod_name (str) – name of the required module to try to import
error_msg (str) – error message to raise when the module is missing
imported module
RuntimeError –
bokeh.util.deprecation
bokeh.util.functions
Utilities for function introspection.
get_param_info
Find parameters with defaults and return them.
sig (Signature) – a function signature
parameters with defaults
tuple(list, list)
bokeh.util.hex
Functions useful for dealing with hexagonal tilings.
For more information on the concepts employed here, see this informative page
https://www.redblobgames.com/grids/hexagons/
axial_to_cartesian
Map axial (q,r) coordinates to cartesian (x,y) coordinates of tiles centers.
This function can be useful for positioning other Bokeh glyphs with cartesian coordinates in relation to a hex tiling.
This function was adapted from:
https://www.redblobgames.com/grids/hexagons/#hex-to-pixel
q (array[float]) – A NumPy array of q-coordinates for binning
r (array[float]) – A NumPy array of r-coordinates for binning
size (float) –
The size of the hexagonal tiling.
The size is defined as the distance from the center of a hexagon to the top corner for “pointytop” orientation, or from the center to a side corner for “flattop” orientation.
orientation (str) – Whether the hex tile orientation should be “pointytop” or “flattop”.
aspect_scale (float, optional) –
Scale the hexagons in the “cross” dimension.
For “pointytop” orientations, hexagons are scaled in the horizontal direction. For “flattop”, they are scaled in vertical direction.
When working with a plot with aspect_scale != 1, it may be useful to set this value to match the plot.
aspect_scale != 1
(array[int], array[int])
cartesian_to_axial
Map Cartesion (x,y) points to axial (q,r) coordinates of enclosing tiles.
https://www.redblobgames.com/grids/hexagons/#pixel-to-hex
x (array[float]) – A NumPy array of x-coordinates to convert
y (array[float]) – A NumPy array of y-coordinates to convert
hexbin
Perform an equal-weight binning of data points into hexagonal tiles.
For more sophisticated use cases, e.g. weighted binning or scaling individual tiles proportional to some other quantity, consider using HoloViews.
x (array[float]) – A NumPy array of x-coordinates for binning
y (array[float]) – A NumPy array of y-coordinates for binning
orientation (str, optional) – Whether the hex tile orientation should be “pointytop” or “flattop”. (default: “pointytop”)
Match a plot’s aspect ratio scaling.
When working with a plot with aspect_scale != 1, this parameter can be set to match the plot, in order to draw regular hexagons (instead of “stretched” ones).
This is roughly equivalent to binning in “screen space”, and it may be better to use axis-aligned rectangular bins when plot aspect scales are not one.
DataFrame
The resulting DataFrame will have columns q and r that specify hexagon tile locations in axial coordinates, and a column counts that provides the count for each tile.
Warning
Hex binning only functions on linear scales, i.e. not on log plots.
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:
BOKEH_PY_LOG_LEVEL
debug info warn error fatal none
debug
info
warn
error
fatal
none
The default logging level is none.
basicConfig
A logging.basicConfig() wrapper that also undoes the default Bokeh-specific configuration.
bokeh.util.options
Utilities for specifying, validating, and documenting configuration options.
Options
Leverage the Bokeh properties type system for specifying and validating configuration options.
Subclasses of Options specify a set of configuration options using standard Bokeh properties:
class ConnectOpts(Options): host = String(default="127.0.0.1", help="a host value") port = Int(default=5590, help="a port value")
Then a ConnectOpts can be created by passing a dictionary containing keys and values corresponding to the configuration options, as well as any additional keys and values. The items corresponding to the properties on ConnectOpts will be *removed* from the dictionary. This can be useful for functions that accept their own set of config keyword arguments in addition to some set of Bokeh model properties.
ConnectOpts
bokeh.util.paths
bokehjsdir
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.serialization
Functions for helping with serialization and deserialization of Bokeh objects.
Certain NumPy array dtypes can be serialized to a binary format for performance and efficiency. The list of supported dtypes is:
np.uint32
np.int32
np.float64
np.uint16
np.int16
np.int8
np.uint8
np.float32
array_encoding_disabled
Determine whether an array may be binary encoded.
The NumPy array dtypes that can be encoded are:
array (np.ndarray) – the array to check
bool
convert_date_to_datetime
Convert a date object to a datetime
obj (date) – the object to convert
datetime
convert_datetime_array
Convert NumPy datetime arrays to arrays to milliseconds since epoch.
array –
(obj) A NumPy array of datetime to convert
If the value passed in is not a NumPy array, it will be returned as-is.
array
convert_datetime_type
Convert any recognized date, time, or datetime value to floating point milliseconds since epoch.
obj (object) : the object to convert
milliseconds
float
convert_timedelta_type
Convert any recognized timedelta value to floating point absolute milliseconds.
decode_base64_dict
Decode a base64 encoded array into a NumPy array.
data (dict) – encoded array data to decode
Data should have the format encoded by encode_base64_dict().
encode_base64_dict()
np.ndarray
encode_base64_dict
Encode a NumPy array using base64:
The encoded format is a dict with the following structure:
{ '__ndarray__' : << base64 encoded array data >>, 'shape' : << array shape >>, 'dtype' : << dtype name >>, }
array (np.ndarray) – an array to encode
dict
encode_binary_dict
Send a numpy array as an unencoded binary buffer
{ '__buffer__' : << an ID to locate the buffer >>, 'shape' : << array shape >>, 'dtype' : << dtype name >>, 'order' : << byte order at origin (little or big)>> }
buffers (set) –
Set to add buffers to
This is an “out” parameter. The values it contains will be modified in-place.
is_datetime_type
Whether an object is any date, time, or datetime type recognized by Bokeh.
obj (object) : the object to test
True if obj is a datetime type
obj
is_timedelta_type
Whether an object is any timedelta type recognized by Bokeh.
True if obj is a timedelta type
make_globally_unique_id
Return a globally unique UUID.
Some situations, e.g. id’ing dynamically created Divs in HTML documents, always require globally unique IDs.
str
make_id
Return a new unique ID for a Bokeh object.
Normally this function will return simple monotonically increasing integer IDs (as strings) for identifying Bokeh objects within a Document. However, if it is desirable to have globally unique for every object, this behavior can be overridden by setting the environment variable BOKEH_SIMPLE_IDS=no.
BOKEH_SIMPLE_IDS=no
serialize_array
Transforms a NumPy array into serialized form.
array (np.ndarray) – the NumPy array to transform
force_list (bool, optional) – whether to only output to standard lists This function can encode some dtypes using a binary encoding, but setting this argument to True will override that and cause only standard Python lists to be emitted. (default: False)
buffers (set, optional) –
If binary buffers are desired, the buffers parameter may be provided, and any columns that may be sent as binary buffers will be added to the set. If None, then only base64 encoding will be used (default: None)
If force_list is True, then this value will be ignored, and no buffers will be generated.
list or dict
transform_array
Transform a NumPy arrays into serialized format
Converts un-serializable dtypes and returns JSON serializable format
array (np.ndarray) – a NumPy array to be transformed
JSON
transform_array_to_list
Transforms a NumPy array into a list of values
array (np.nadarray) – the NumPy array series to transform
transform_column_source_data
Transform ColumnSourceData data to a serialized format
ColumnSourceData
data (dict) – the mapping of names to data columns to transform
cols (list[str], optional) – Optional list of subset of columns to transform. If None, all columns will be transformed (default: None)
JSON compatible dict
transform_series
Transforms a Pandas series into serialized form
series (pd.Series) – the Pandas series to transform
traverse_data
Recursively traverse an object until a flat list is found.
The flat list is converted to a numpy array and passed to transform_array() to handle nan, inf, and -inf.
nan
inf
-inf
obj (list) – a list of values or lists
bokeh.util.token
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
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.
check_token_signature
Check the signature of a token and the contained signature.
The server uses this function to check whether a token and the contained session id was generated with the correct secret key. If signed sessions are disabled, this function always returns True.
token (str) – The token to check
secret_key (str, optional) – Secret key (default: value of BOKEH_SECRET_KEY environment variable)
signed (bool, optional) – Whether to check anything (default: value of BOKEH_SIGN_SESSIONS environment variable)
generate_jwt_token
Generates a JWT token given a session_id and additional payload.
session_id (str) – The session id to add to the token
secret_key (str, optional) – Secret key (default: value of BOKEH_SECRET_KEY environment varariable)
signed (bool, optional) – Whether to sign the session ID (default: value of BOKEH_SIGN_SESSIONS envronment varariable)
extra_payload (dict, optional) – Extra key/value pairs to include in the Bokeh session token
expiration (int, optional) – Expiration time
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
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.
get_session_id
Extracts the session id from a JWT token.
token (str) – A JWT token containing the session_id and other data.
get_token_payload
Extract the payload from the token.
bokeh.util.string
Functions useful for string manipulations or encoding.
format_docstring
Safely format docstrings.
When Python is executed with the -OO option, doc strings are removed and replaced the value None. This function guards against applying the string formatting options in that case.
-OO
docstring (str or None) – The docstring to format, or None
args (tuple) – string formatting arguments for the docsring
kwargs (dict) – string formatting arguments for the docsring
str or None
indent
Indent all the lines in a given block of text by a specified amount.
text (str) – The text to indent
n (int, optional) – The amount to indent each line by (default: 2)
ch (char, optional) – What character to fill the indentation with (default: ” “)
nice_join
Join together sequences of strings into English-friendly phrases using the conjunction or when appropriate.
or
seq (seq[str]) – a sequence of strings to nicely join
sep (str, optional) – a sequence delimiter to use (default: “, “)
conjunction (str or None, optional) – a conjuction to use for the last two items, or None to reproduce basic join behaviour (default: “or”)
a joined string
Examples
>>> nice_join(["a", "b", "c"]) 'a, b or c'
snakify
Convert CamelCase to snake_case.
bokeh.util.tornado
Internal utils related to Tornado
bokeh.util.terminal
Provide utilities for formatting terminal output.
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 full version string for this installed Bokeh library
Return the base version string, without any “dev”, “rc” or local build information appended.
Return whether the current installed version is a full release.
bokeh.util.warnings
Provide Bokeh-specific warning subclasses.
The primary use of these subclasses to to force them to be unconditionally displayed to users by default.
BokehDeprecationWarning
A Bokeh-specific DeprecationWarning subclass.
DeprecationWarning
Used to selectively filter Bokeh deprecations for unconditional display.
BokehUserWarning
A Bokeh-specific UserWarning subclass.
UserWarning
Used to selectively filter Bokeh warnings for unconditional display.