Hue service integration is generic and lets you integrate with other analytics systems. Here is a list of the main APIs:
REST APIs are not all public yet but this is work in progress in HUE-1450. Upcoming APIs: how to add new vizualizations, new SQL grammar and highlighting, workflow systems. In addition, whole new apps can also be created in order to provide end to end solutions.
They provide SQL integration with any database via several connectors (native, JDBC, SQL Alchemy...).
Other modes like MapReduce, Java, Shell, Sqoop are also available. Here is a list of the existing connectors.
Connectors are pluggable and can new engines can be supported. Feel free to comment on the Hue list of github about it.
The SQL Editor page also describes the configuration steps.
Close to 100% of Hive and Impala grammar is supported which makes the autocomplete extremly powerful. Other languages defaults to a generic SQL grammar.
Hive, Impala, SparkSQL
SQL Alchemy supports comes with HUE-8740.
MySQL, Oracle, PostgreSQL, Phoenix, Presto, Kylin, Redshift, BigQuery, Drill
Use the query editor with any JDBC or Django-compatible database. View the JDBC connector.
MapReduce, Pig, Java, Shell, Sqoop, DistCp Oozie connector
Based on the Livy REST API
Dashboards are generic and support Solr and any SQL:
The API was influenced by Solr but is now generic:
Implementations:
When HS2, RDBMS, and JDBC Are Not Enough
If the built-in HiveServer2 (Hive, Impala, Spark SQL), RDBMS (MySQL, PostgreSQL, Oracle, SQLite), and JDBC interfaces don’t meet your needs, you can implement your own connector to the notebook app: Notebook Connectors. Each connector API subclasses the Base API and must implement the methods defined within; refer to the JdbcApi or RdbmsApi for representative examples.
A similar backend to Solr would need to be developed: HUE-7828
Here is an example on how the Job Browser can list:
Here is an example on how the File Browser can list HDFS, S3 files and now ADLS.
This section goes into greater detail on useful features within the Hue environment.
Except for static content, request.user
is always populated. It is a
standard Django models.User
object. If you were to set a breakpoint at the
index()
function in our calculator app, you will find:
>>> request.user
<User: test>
request.user
gets populated. There's also a
middleware for Hue that makes sure that no pages are displayed unless the
user is authenticated.
Hue uses a typed configuration system that reads configuration files (in an
ini-style format). By default, Hue loads all *.ini
files in the build/desktop/conf
directory. The configuration files have the following format:
# This is a comment
[ app_name ] # Same as your app's name
app_property = "Pink Floyd"
[[ section_a ]] # The double brackets start a section under [ app_name ]
a_weight = 80 # that is useful for grouping
a_height = 180
[[ filesystems ]] # Sections are also useful for making a list
[[[ cluster_1 ]]] # All list members are sub-sections of the same type
namenode_host = localhost
# User may define more:
# [[[ cluster_2 ]]]
# namenode_host = 10.0.0.1
Your application's conf.py
is special. It provides access to the configuration file (and even
default configurations not specified in the file). Using the above example, your conf.py
should
define the following:
A desktop.lib.conf.Config
object for app_property
, such as:
MY_PROPERTY = Config(key='app_property', default='Beatles', help='blah')You can access its value by
MY_PROPERTY.get()
.
A desktop.lib.conf.ConfigSection
object for section_a
, such as:
SECTION_A = ConfigSection(key='section_a', help='blah', members=dict( AWEIGHT=Config(key='a_weight', type=int, default=0), AHEIGHT=Config(key='a_height', type=int, default=0)))You can access the values by
SECTION_A.AWEIGHT.get()
.
A desktop.lib.conf.UnspecifiedConfigSection
object for filesystems
, such as:
FS = UnspecifiedConfigSection( key='filesystems', each=ConfigSection(members=dict( nn_host=Config(key='namenode_host', required=True))An
UnspecifiedConfigSection
is useful when the children of the section are not known.
When Hue loads your application's configuration, it binds all sub-sections. You can
access the values by:
cluster1_val = FS['cluster_1'].nn_host.get() all_clusters = FS.keys() for cluster in all_clusters: val = FS[cluster].nn_host.get()
Your Hue application can automatically detect configuration problems and alert
the admin. To take advantage of this feature, create a config_validator
function in your conf.py
:
def config_validator(user): """ config_validator(user) -> [(config_variable, error_msg)] or None Called by core check_config() view. """ res = [ ] if not REQUIRED_PROPERTY.get(): res.append((REQUIRED_PROPERTY, "This variable must be set")) if MY_INT_PROPERTY.get() < 0: res.append((MY_INT_PROPERTY, "This must be a non-negative number")) return res
help="..."
argument to all configuration
related objects in your conf.py
. The examples omit some for the
sake of space. But you and your application's users can view all the
configuration variables by doing:
$ build/env/bin/hue config_help
Some Hue applications need to run separate daemon processes on the side.
Suppose your application needs a helper my_daemon.py
. You need to register it by:
In setup.py
, add to entry_points
:
entry_points = { 'desktop.sdk.application': 'my_app = my_app', 'desktop.supervisor.specs': [ 'my_daemon = my_app:SUPERVISOR_SPEC' ] }
In src/my_app/__init__.py
, tell Hue what to run by adding:
SUPERVISOR_SPEC = dict(django_command="my_daemon")
Then in src/my_app/management/commands
, create __init__.py
and my_daemon.py
. Your
daemon program has only one requirement: it must define a class called Command
that
extends django.core.management.base.BaseCommand
. Please see kt_renewer.py
for an example.
The next time Hue restarts, your my_daemon
will start automatically.
If your daemon program dies (exits with a non-zero exit code), Hue will
restart it.
"Under the covers:" Threading. Hue, by default, runs CherryPy web server. If Hue is configured (and it may be, in the future) to use mod_wsgi under Apache httpd, then there would be multiple python processes serving the backend. This means that your Django application code should avoid depending on shared process state. Instead, place the stored state in a database or run a separate server.
Django is an MVC framework, except that the controller is called a "view" and the "view" is called a "template". For an application developer, the essential flow to understand is how the "urls.py" file provides a mapping between URLs (expressed as a regular expression, optionally with captured parameters) and view functions. These view functions typically use their arguments (for example, the captured parameters) and their request object (which has, for example, the POST and GET parameters) to prepare dynamic content to be rendered using a template.
In Hue, the typical pattern for rendering data through a template is:
from desktop.lib.django_util import render
def view_function(request):
return render('view_function.mako', request, dict(greeting="hello"))
The render()
function chooses a template engine (either Django or Mako) based on the
extension of the template file (".html" or ".mako"). Mako templates are more powerful,
in that they allow you to run arbitrary code blocks quite easily, and are more strict (some
would say finicky); Django templates are simpler, but are less expressive.
Django Models are Django's Object-Relational Mapping framework. If your application needs to store data (history, for example), models are a good way to do it.
From an abstraction perspective, it's common to imagine external services as "models". For example, the Job Browser treats the Hadoop JobTracker as a "model", even though there's no database involved.
It is common for applications to need to access the underlying HDFS.
The request.fs
object is a "file system" object that exposes
operations that manipulate HDFS. It is pre-configured to access
HDFS as the user that's currently logged in. Operations available
on request.fs
are similar to the file operations typically
available in python. See webhdfs.py
for details; the list
of functions available is as follows:
chmod
,
chown
,
exists
,
isdir
,
isfile
,
listdir
(and listdir_stats
),
mkdir
,
open
(which exposes a file-like object with read()
, write()
, seek()
, and tell()
methods),
remove
,
rmdir
,
rmtree
, and
stats
.
Hue works in any WSGI-compliant container web server.
The current recommended deployment server is the built-in CherryPy server.
The CherryPy server, which is multi-threaded, is invoked by runcpserver
and is configured to start when Hue's supervisor
script is used.
Meanwhile, runserver
start a single-threaded
testing server.
Because multiple threads may be accessing your views
concurrently, your views should not use shared state.
An exception is that it is acceptable to initialize
some state when the module is first imported.
If you must use shared state, use Python's threading.Lock
.
Note that any module initialization may happen multiple times. Some WSGI containers (namely, Apache), will start multiple Unix processes, each with multiple threads. So, while you have to use locks to protect state within the process, there still may be multiple copies of this state.
For persistent global state, it is common to place the state in the database or on the Browser local storage.
Hue exposes a configuration flag ("auth") to configure a custom authentication backend. See See http://docs.djangoproject.com/en/dev/topics/auth/#writing-an-authentication-backend for writing such a backend.
In addition to that, backends may support a manages_passwords_externally()
method, returning
True or False, to tell the user manager application whether or not changing
passwords within Hue is possible.
Applications may define permission sets for different actions. Administrators
can assign permissions to user groups in the UserAdmin application. To define
custom permission sets, modify your app's settings.py
to create a list of
(identifier, description)
tuples:
PERMISSION_ACTIONS = [
("delete", "Delete really important data"),
("email", "Send email to the entire company"),
("identifier", "Description of the permission")
]
Then you can use this decorator on your view functions to enforce permission:
@desktop.decorators.hue_permission_required("delete", "my_app_name")
def delete_financial_report(request):
...
Right now, we check in the generated thrift code. To generate the code, you'll need the thrift binary version 0.9.0. Please download from http://thrift.apache.org/.
The modules using Thrift
have some helper scripts like regenerate_thrift.sh
for regenerating the code from the interfaces.
Hue has a profiling system built in, which can be used to analyze server-side performance of applications. To enable profiling::
build/env/bin/hue runprofileserver
Then, access the page that you want to profile. This will create files like
/tmp/useradmin.users.000072ms.2011-02-21T13:03:39.745851.prof. The format for
the file names is /tmp/
Hue uses the hotshot profiling library for instrumentation. The documentation for this library is located at: http://docs.python.org/library/hotshot.html.
You can use kcachegrind to view the profiled data graphically::
$ hotshot2calltree /tmp/xyz.prof > /tmp/xyz.trace
$ kcachegrind /tmp/xyz.trace
More generally, you can programmatically inspect a trace::
#!/usr/bin/python
import hotshot.stats
import sys
stats = hotshot.stats.load(sys.argv[1])
stats.sort_stats('cumulative', 'calls')
stats.print_stats(100)
This script takes in a .prof file, and orders function calls by the cumulative time spent in that function, followed by the number of times the function was called, and then prints out the top 100 time-wasters. For information on the other stats available, take a look at this website: http://docs.python.org/library/profile.html#pstats.Stats
Each app used to have its own model to store its data (e.g. a SQL query, a workflow). In Hue 3
a unification of all the models happened and any app now uses a single Document2 model:
desktop/core/src/desktop/models.py
. This enables to avoid simply re-use document
creation, sharing, saving etc...
Hue is Ajax based and has a REST API used by the browser to communicate (e.g. submit a query or workflow,
list some S3 files, export a document...). Currently this API is private and subject to change but
can be easily reused. You would need to GET /accounts/login
to get the CSRF token
and POST it back along username
and password
and reuse the sessionid
cookie in next
communication calls.
With Python Request
Hue is based on the Django Web Framework. Django comes with user authentication system. Django uses sessions and middleware to hook the authentication system into request object. HUE uses stock auth form which uses “username” and “password” and “csrftoken” form variables to authenticate.
In this code snippet, we will use well-known python “requests” library. we will first acquire “csrftoken” by GET “login_url”. We will create python dictionary of form data which contains “username”, “password” and “csrftoken” and the “next_url” and another python dictionary for header which contains the “Referer” url and empty python dictionary for the cookies. After POST request to “login_url” we will get status. Check the r.status_code. If r.status_code!=200 then you have problem in username and/or password.
Once the request is successful then capture headers and cookies for subsequent requests. Subsequent request.session calls can be made by providing cookies=session.cookies and headers=session.headers.
import requests def login_djangosite(): next_url = "/" login_url = "http://localhost:8888/accounts/login?next=/" session = requests.Session() r = session.get(login_url) form_data = dict(username="[your hue username]",password="[your hue password]", csrfmiddlewaretoken=session.cookies['csrftoken'],next=next_url) r = session.post(login_url, data=form_data, cookies=dict(), headers=dict(Referer=login_url)) # check if request executed successfully? print r.status_code cookies = session.cookies headers = session.headers r=session.get('http://localhost:8888/metastore/databases/default/metadata', cookies=session.cookies, headers=session.headers) print r.status_code # check metadata output print r.text
After upgrading the version of Hue, running these two commands will make sure the database has the correct tables and fields.
./build/env/bin/hue syncdb
./build/env/bin/hue migrate
Developing applications for Hue requires a minimal amount of CSS (and potentially JavaScript) to use existing functionality. As covered above, creating an application for the Hue is a matter of creating a standard HTML application.
In a nutshell, front-end development in Hue is using Bootstrap and Knockout js to layout your app and script the custom interactions.
Hue uses Bootstrap version 2.0 CSS styles and layouts. They are highly reusable and flexible. Your app doesn't have to use these styles, but if you do, it'll save you some time and make your app look at home in Hue.
On top of the standard Bootstrap styles, Hue defines a small set of custom styles in desktop/core/static/css/jhue.css.
When you create your application it will provision a CSS file for you in the static/css directory. For organization purposes, your styles should go here (and any images you have should go in static/art). Your app's name will be a class that is assigned to the root of your app in the DOM. So if you created an app called "calculator" then every window you create for your app will have the class "calculator". Every style you define should be prefixed with this to prevent you from accidentally colliding with the framework style. Examples:
/* the right way: */
.calculator p {
/* all my paragraphs should have a margin of 8px */
margin: 8px;
/* and a background from my art directory */
background: url(../art/paragraph.gif);
}
/* the wrong way: */
p {
/* woops; we're styling all the paragraphs on the page, affecting
the common header! */
margin: 8px;
background: url(../art/paragraph.gif);
}
You should create an icon for your application that is a transparent png sized
24px by 24px. Your settings.py
file should point to your icon via the ICON
variable. The create_desktop_app
command creates a default icon for you.
Hue ships with Twitter Bootstrap and Font Awesome 3 (http://fortawesome.github.io/Font-Awesome/) so you have plenty of scalable icons to choose from. You can style your elements to use them like this (in your mako template):
<!-- show a trash icon in a link -->
<a href="#something"><i class="icon-trash"></i> Trash</a>
For better performances, Hue uses the Django staticfiles app. If in production mode, if you edit
some static files, you would need to run this command or make apps
. No actions are needed in
development mode.
./build/env/bin/hue collectstatic
Hue by default loads these JavaScript components:
These are used by some Hue applications, but not loaded by default:
desktop/core/static/ext/js/knockout-min.js
)desktop/core/static/ext/js/jquery/plugins/jquery-ui-autocomplete-1.8.18.min.js
)These standard components have their own online documentation, which we will not repeat here. They let you write interactive behaviors with little or no JavaScript.
DESKTOP_DEBUG=1
as an environment variable if you want logs to go to stderr
as well as to the respective log files.__import__("ipdb").set_trace()
into your code.Building with
make docs
The javascript files are currently being migrated to webpack bundles, during this process some files will live under src/desktop/static/ and some will live under src/dekstop/js
First make sure all third-party dependencies defined in package.json are installed into node_modules/
npm install
Also run this after making changes to package.json, adding new third-party dependencies etc.
To generate the js bundles run:
npm run webpack
npm run webpack-workers
npm run webpack-login
During development the bundles can be autogenerated when it detects changes to the .js files, for this run:
npm run dev
Before sending a review with changes to the bundles run:
npm run lint-fix
and possibly fix any issues it might report.
After changing the CSS in a .less file, rebuilding with:
make css
Install a patched jison:
git clone https://github.com/JohanAhlen/jison
cd jison
npm install -g .
Then run:
make sql-all-parsers
After modifying files under tools/ace-editor run the following to build ace.js
npm install
make ace
How to update all the messages and compile them:
make locales
How to update and compile the messages of one app:
cd apps/beeswax
make compile-locale
How to create a new locale for an app:
cd $APP_ROOT/src/$APP_NAME/locale
$HUE_ROOT/build/env/bin/pybabel init -D django -i en_US.pot -d . -l fr
The metadata API is powering Search and Tagging here and the Query Assistant with Navigator Optimizer Integration.
The backends is pluggable by providing alternative client interfaces:
$.post("/metadata/api/catalog/search_entities_interactive/", {
query_s: ko.mapping.toJSON("*sample"),
sources: ko.mapping.toJSON(["sql", "hdfs", "s3"]),
field_facets: ko.mapping.toJSON([]),
limit: 10
}, function(data) {
console.log(ko.mapping.toJSON(data));
});
$.post("/metadata/api/catalog/search_entities_interactive/", {
query_s: ko.mapping.toJSON("*sample"),
interface: "dummy"
}, function(data) {
console.log(ko.mapping.toJSON(data));
});
$.get("/metadata/api/navigator/find_entity", {
type: "table",
database: "default",
name: "sample_07",
interface: "dummy"
}, function(data) {
console.log(ko.mapping.toJSON(data));
});
$.post("/metadata/api/catalog/update_properties/", {
id: "22",
properties: ko.mapping.toJSON({"description":"Adding a description"}),
interface: "dummy"
}, function(data) {
console.log(ko.mapping.toJSON(data));
});
$.post("/metadata/api/catalog/add_tags/", {
id: "22",
tags: ko.mapping.toJSON(["usage"]),
interface: "dummy"
}, function(data) {
console.log(ko.mapping.toJSON(data));
});
$.post("/metadata/api/catalog/delete_metadata_properties/", {
"id": "32",
"keys": ko.mapping.toJSON(["project", "steward"])
}, function(data) {
console.log(ko.mapping.toJSON(data));
});
$.post("/metadata/api/catalog/delete_metadata_properties/", {
"id": "32",
"keys": ko.mapping.toJSON(["project", "steward"])
}, function(data) {
console.log(ko.mapping.toJSON(data));
});
$.get("/metadata/api/catalog/models/properties/mappings/", function(data) {
console.log(ko.mapping.toJSON(data));
});
$.post("/metadata/api/catalog/namespace/", {
namespace: 'huecatalog'
}, function(data) {
console.log(ko.mapping.toJSON(data));
});
$.post("/metadata/api/catalog/namespace/create/", {
"namespace": "huecatalog",
"description": "my desc"
}, function(data) {
console.log(ko.mapping.toJSON(data));
});
$.post("/metadata/api/catalog/namespace/property/create/", {
"namespace": "huecatalog",
"properties": ko.mapping.toJSON({
"name" : "relatedEntities2",
"displayName" : "Related objects",
"description" : "My desc",
"multiValued" : true,
"maxLength" : 50,
"pattern" : ".*",
"enumValues" : null,
"type" : "TEXT"
})
}, function(data) {
console.log(ko.mapping.toJSON(data));
});
$.post("/metadata/api/catalog/namespace/property/map/", {
"class": "hv_view",
"properties": ko.mapping.toJSON([{
namespace: "huecatalog",
name: "relatedQueries"
}])
}, function(data) {
console.log(ko.mapping.toJSON(data));
});
Building a brand new application is more work but is ideal for creating a custom solution.
Hue leverages the browser to provide users with an environment for exploring and analyzing data.
Build on top of the Hue SDK to enable your application to interact efficiently with Hadoop and the other Hue services.
By building on top of Hue SDK, you get, out of the box:
This document will orient you with the general structure of Hue and will walk you through adding a new application using the SDK.
Hue, as a "container" web application, sits in between your Hadoop installation and the browser. It hosts all the Hue Apps, including the built-in ones, and ones that you may write yourself.
Hue is a web application built on the Django python web framework. Django, running on the WSGI container/web server (typically CherryPy), manages the url dispatch, executes application logic code, and puts together the views from their templates. Django uses a database (typically sqlite) to manage session data, and Hue applications can use it as well for their "models". (For example, the saved Editor stores saved queries in the database.)
In addition to the web server, some Hue applications run
daemon processes "on the side". Some examples are the Celery Task Server
, Celery Beat
.
Hue provides some APIs for interacting with Hadoop. Most noticeably, there are python file-object-like APIs for interacting with HDFS. These APIs work by making REST API or Thrift calls the Hadoop daemons. The Hadoop administrator must enable these interfaces from Hadoop.
Hue provides a front-end framework based on Bootstrap and Knockout js.
A Hue application may span three tiers: (1) the UI and user interaction in the client's browser, (2) the core application logic in the Hue web server, and (3) external services with which applications may interact.
The absolute minimum that you must implement (besides boilerplate), is a "Django view" function that processes the request and the associated template to render the response into HTML.
Many apps will evolve to have a bit of custom JavaScript and CSS styles. Apps that need to talk to an external service will pull in the code necessary to talk to that service.
The Hue "framework" is in desktop/core/
and contains the Web components.
desktop/libs/
is the API for talking to various Hadoop services.
The installable apps live in apps/
. Please place third-party dependencies in the app's ext-py/
directory.
The typical directory structure for inside an application includes: ``` src/ for Python/Django code models.py urls.py views.py forms.py settings.py
conf/
for configuration (.ini
) files to be installed
static/ for static HTML/js resources and help doc
templates/ for data to be put through a template engine
locales/ for localizations in multiple languages ```
For the URLs within your application, you should make your own urls.py
which will be automatically rooted at /yourappname/
in the global
namespace. See apps/about/src/about/urls.py
for an example.
The following are core technologies used inside of Hue.
Now that we have a high-level overview of what's going on, let's go ahead and create a new installation.
The Hue SDK is available from Github. Releases can be found on the download page. Releases are missing a few dependencies that could not be included because of licencing issues. So if you prefer to have an environment ready from scratch, it is preferable to checkout a particular release tag instead.
cd hue
## Build
make apps
## Run
build/env/bin/hue runserver
## Alternative run
build/env/bin/hue supervisor
## Visit http://localhost:8000/ with your web browser.
./build/env/bin/hue create_desktop_app calculator
find calculator -type f
calculator/setup.py # distutils setup file
calculator/src/calculator/__init__.py # main src module
calculator/src/calculator/forms.py
calculator/src/calculator/models.py
calculator/src/calculator/settings.py # app metadata setting
calculator/src/calculator/urls.py # url mapping
calculator/src/calculator/views.py # app business logic
calculator/src/calculator/templates/index.mako
calculator/src/calculator/templates/shared_components.mako
# Static resources
calculator/src/static/calculator/art/calculator.png # logo
calculator/src/static/calculator/css/calculator.css
calculator/src/static/calculator/js/calculator.js
As you'll discover if you look at calculator's setup.py, Hue uses a distutils entrypoint to register applications. By installing the calculator package into Hue's python virtual environment, you'll install a new app. The "app_reg.py" tool manages the applications that are installed. Note that in the following example, the value after the "--install" option is the path to the root directory of the application you want to install. In this example, it is a relative path to "/Users/philip/src/hue/calculator".
./build/env/bin/python tools/app_reg/app_reg.py --install calculator --relative-paths
=== Installing app at calculator
Updating registry with calculator (version 0.1)
--- Making egg-info for calculator
Congrats, you've added a new app!
You can now browse the new application.
# If you haven't killed the old process, do so now.
build/env/bin/hue runserver
And then visit http://localhost:8000/ to check it out! You should see the app in the left menu.
Now that your app has been installed, you'll want to customize it.
As you may have guessed, we're going to build a small calculator
application. Edit calculator/src/calculator/templates/index.mako
to include a simple form and a Knockout viewmodel:
<%!from desktop.views import commonheader, commonfooter %>
<%namespace name="shared" file="shared_components.mako" />
%if not is_embeddable:
${commonheader("Calculator", "calculator", user, "100px") | n,unicode}
%endif
## Main body
<div class="container-fluid calculator-components">
<div class="row">
<div class="span6 offset3 margin-top-30 text-center">
<form class="form-inline">
<input type="text" class="input-mini margin-right-10" placeholder="A" data-bind="value: a">
<!-- ko foreach: operations -->
<label class="radio margin-left-5">
<input type="radio" name="op" data-bind="checkedValue: $data, checked: $parent.chosenOperation" /><span data-bind="text: $data"></span>
</label>
<!-- /ko -->
<input type="text" class="input-mini margin-left-10" placeholder="B" data-bind="value: b">
<button class="btn" data-bind="click: calculate">Calculate</button>
</form>
<h2 data-bind="visible: result() !== null">The result is <strong data-bind="text: result"></strong></h2>
</div>
</div>
</div>
<script>
(function() {
var CalculatorViewModel = function () {
var self = this;
self.operations = ko.observableArray(['+', '-', '*', '/']);
self.a = ko.observable();
self.b = ko.observable();
self.chosenOperation = ko.observable('+');
self.result = ko.observable(null);
self.calculate = function () {
var a = parseFloat(self.a());
var b = parseFloat(self.b());
var result = null;
switch (self.chosenOperation()) {
case '+':
result = a + b;
break;
case '-':
result = a - b;
break;
case '*':
result = a * b;
break;
case '/':
result = a / b;
}
self.result(result);
}
};
$(document).ready(function () {
ko.applyBindings(new CalculatorViewModel(), $('.calculator-components')[0]);
});
})();
</script>
%if not is_embeddable:
${commonfooter(messages) | n,unicode}
%endif
The template language here is Mako,
which is flexible and powerful. If you use the ".html
" extension, Hue
will render your page using
Django templates
instead.
Note that we use Knockout.js to do the heavy lifting of this app.
Let's edit calculator/src/calculator/views.py
to simply render the page:
#!/usr/bin/env python
from desktop.lib.django_util import render
def index(request):
return render('index.mako', request, {
'is_embeddable': request.GET.get('is_embeddable', False),
})
You can now go and try the calculator.
Install the mini cluster (only once):
./tools/jenkins/jenkins.sh slow
Run all the tests:
build/env/bin/hue test all
Or just some parts of the tests, e.g.:
build/env/bin/hue test specific impala
build/env/bin/hue test specific impala.tests:TestMockedImpala
build/env/bin/hue test specific impala.tests:TestMockedImpala.test_basic_flow
Jasmine tests:
npm run test
The test
management command prepares the arguments (test app names)
and passes them to nose (django_nose.nose_runner). Nose will then magically
find all the tests to run.
Tests themselves should be named *_test.py. These will be found as long as they're in packages covered by django. You can use the unittest frameworks, or you can just name your method with the word "test" at a word boundary, and nose will find it. See apps/hello/src/hello/hello_test.py for an example.
To run tests that do not depend on Hadoop, use:
build/env/bin/hue test fast
To run all tests, use:
build/env/bin/hue test all
To run only tests of a particular app, use:
build/env/bin/hue test specific <app>
E.g. build/env/bin/hue test specific filebrowser
To run a specific test, use:
build/env/bin/hue test specific <test_func>
E.g. build/env/bin/hue test specific useradmin.tests:test_user_admin
Start up pdb on test failures:
build/env/bin/hue test <args> --pdb --pdb-failure -s
Point to an Impalad and trigger the Impala tests:
build/env/bin/hue test impala impalad-01.gethue.com
Add them in a "spec" subfolder relative to the file under test and the filename of the test has to end with "Spec.js".
someFile.js <- File under test
├── spec/
│ ├── someFileSpec.js <- File containing tests
Run all the tests once with:
npm run test
Optionally to use Karma and headless chrome for the tests you can run
npm run test-karma
See desktop/core/src/desktop/js/spec/karma.config.js
for various options
DESKTOP_LOGLEVEL=<level>
level can be DEBUG, INFO, WARN, ERROR, or CRITICAL
When specified, the console logger is set to the given log level. A console
logger is created if one is not defined.
DESKTOP_DEBUG
A shorthand for DESKTOP_LOG_LEVEL=DEBUG. Also turns on output HTML
validation.
DESKTOP_PROFILE
Turn on Python profiling. The profile data is saved in a file. See the
console output for the location of the file.
DESKTOP_LOG_DIR=$dir
Specify the HUE log directory. Defaults to ./log.
DESKTOP_DB_CONFIG=$db engine:db name:test db name:username:password:host:port
Specify alternate DB connection parameters for HUE to use. Useful for
testing your changes against, for example, MySQL instead of sqlite. String
is a colon-delimited list.
TEST_IMPALAD_HOST=impalad-01.gethue.com
Point to an Impalad and trigger the Impala tests.
Use pseudo_hdfs4.py! You should tag such tests with "requires_hadoop", as follows:
from nose.plugins.attrib import attr
@attr('requires_hadoop')
def your_test():
...
Because building Hadoop (for the tests that require it) is slow, we've separated the Jenkins builds into "fast" and "slow". Both are run via scripts/jenkins.sh, which should be kept updated with the latest and greatest in build technologies.