How to get info from web?

Remember that Python usage in Pepper robots is limited to Python 2 and old versions of packages. It is possible to install some (small) Python packages via pip --user to /home/nao but the space is limited.

If you want to test without the real robot, you can run the Python 2 code (in or outside Choregraphe) using the virtual robot - see below.

Use website API

If API exists, you can usually use JSON data after send the right parameters. Example to get weather data.

import requests
url = "http://api.openweathermap.org/data/2.5/weather"

params = {'q': 'Brno',
          'units': 'metric',
          'lang': 'cz'}

r = requests.get(url=url, params=params)
data = r.json()

print(data['main']['temp'])

(Full example forecast.py )

Parse webpage data

If no API is provided, you can download and parse the webpage.

from bs4 import BeautifulSoup
import requests
page = requests.get(url).text
soup = BeautifulSoup(page, features="lxml")
results = soup.findAll('h3', attrs={'class':'article-title'})

(Full example news.py)

In virtual robot, if you get a runtime error: No module named bs4, you may need to install the package into the Choregraphe environtment via:

sudo pip2 install --target='/opt/Softbank Robotics/Choregraphe Suite 2.5/lib/python2.7/site-packages' \
    bs4

Use pip instead of pip2 in older linux systems. Beware that the version of just installed bs4 package may be different from the version on the real robot.

A safe option to include new packages is to install the package (e.g. yourmodule) in the application directory (e.g. lib) and import it like:

def __init__(self):
        GeneratedClass.__init__(self)
        self.folderName = os.path.join(self.behaviorAbsolutePath(), "../lib")

def onInput_onStart(self):
        if self.folderName not in sys.path:
            sys.path.append(self.folderName)
        import yourmodule
        # ... use yourmodule
        if self.folderName in sys.path:
            sys.path.remove(self.folderName)
        self.onStopped() #activate the output of the box

Load local data

The same approach may be used for accessing your own data (e.g. in csv or json format) stored within your application directory. You need to include the file within the app package description ....pml file as:

<Resources>
    <File name="data.csv" src="data" />
</Resources>

and load it in a Python box with correct path

import csv

class MyClass(GeneratedClass):
    def __init__(self):
        GeneratedClass.__init__(self)
        self.folderName = os.path.join(self.behaviorAbsolutePath(), "..")
        self.data = []
        with open(os.path.join(self.folderName, 'data.csv'), 'rb') as f:
            reader = csv.reader(f)
            for row in reader:
                self.data.append(row)
        self.logger.info("data: %d rows loaded" % len(self.data))

How to integrate info with robot?

There are 2 basic options:

use simple dialog variables as input and say the results directly in the Python script
use complex service (=a separate Python class/script) which fully integrates in the Pepper API

These options are detailed below.

Option 1 - Dialog variables

In the dialog topic file, set a value of a variable, use the variable in a Python script in the robot's behavior. See the example application below for details.

concept:(team) [sparta spartě slavie slavii]
u:(["Můj [oblíbený nejoblíbenější] tým je" "Fandím {týmu}"] _~team) $team=$1

First word after sentence is available in $1 and passed to the script as team variable.

def onInput_onStart(self, team):
    self.team_name = 'Slavia'
    if ((team.lower().startswith('spart')):
        self.team_name = 'Sparta'

Use TTS in script

# find out self.team_points for self.team_name from web
sentence = self.team_name + " má " + str(self.team_points) + " bodů"
self.tts.say(sentence)

Option 2 - Run script as service and parse service output

Specify service script in manifest.xml (here rozvrh = schedule):

<services>
    <service autorun="true" execStart="/usr/bin/python2 scripts/rozvrh.py" name="rozvrh" />
</services>

In dialog, detect variables, pass them to service, and parse the call result to say answer:

u:(rozvrh) Pro jakou místnost bys chtěl znát rozvrh?
    u1:({pro} {místnost učebnu} _~letter _~number) Podívám se na rozvrh pro $1 $2 ^call(Rozvrh.get_current_lesson($1, $2)) \pau=500\
    c1:(In _* teaches _* course _*) V místnosti $1 je právě $3 s vyučujícím, který se jmenuje $2.
    c1:(In _* currently _*) V místnosti $1 je právě $2

Note that in c1: we can use _* since this regular expression is matched against text from the service, not against human speech. The text can be in English (or even in non-language), the answer to humans is then specified in the concrete dialog topic, e.g. in Czech. Unfortunately, the documentation is not clear in what can and what cannot be matched by _* here, tests are needed with real data.

u1 detects letter and number (concepts defined earlier in dialog) and calls get_current_lesson(). This function return strings, that are parsed in dialog and answer is translated to each locale.

def get_current_lesson(self, letter, number):
    room = letter + str(number)
    lesson = self.rozvrh.find_current_lesson(room)
    if lesson:
        if lesson.teacher:
            teacher = lesson.teacher.split(' ')[-1]
            return "In %s teaches %s course %s" % (lesson.room, teacher, lesson.name)
         else:
            return "In %s currently %s" % (lesson.room, lesson.name)

Run script as service and use TTS in script

Detect variables in dialog, pass them to script and let script use TTS to say answer.

u:("[řekni ukaž zobraz najdi] {mi} [odjezdy spoje] ze zastávky _~station_name")
    ^call(DialogKordisbot.say_answer1($1))

Dialog detects word with station name and calls say_answer1(). No answer is passed back, answer is said directly in script.

def say_answer1(self, station):
    #get data finalDepartures
    answer_msg = "First line {} goes to {} at {}, second line {} goes to {} at {}, third line {} goes to {} at {}".format(finalDepartures[0][0], finalDepartures[0][1], finalDepartures[0][2], finalDepartures[1][0], finalDepartures[1][1], finalDepartures[1][2], finalDepartures[2][0], finalDepartures[2][1], finalDepartures[2][2])

    self.s.ALAnimatedSpeech.say(answer_msg)

Testing a service with virtual robot

A service can be tested in the virtual robot settings.

prepare an app with the service to test - you may start with the examples below or use the templater tool robot-jumpstarter (use a new name for your service):
```
ssh aurora
cd /nlp/projekty/pepper/web/robot-jumpstarter
python jumpstart.py python-service tweety-service TweetyService
cp -a output/tweety-service ~/pepper/
```
Here tweety-service is the directory name of the application (and the app name), TweetyService is the API name of your service as it will be called from Python.
copy the directory with the service app (e.g. ~/pepper/tweety-service) to your computer, where you run Choregraphe. All the following steps are done on this computer, not remotely via SSH.
start Choregraphe and run the virtual robot
find out the port number of your virtual robot: click
and remember the IP and port from the table:

Here the virtual robot's address is localhost:34121

connecting to the Choregraphe virtual robot seems not to work in Windows environment, only in Linux. For Windows, the virtual robot can be run via the NAOqi binary:

c:/Program\ Files/Softbank\ Robotics/Choregraphe\ Suite\ 2.5/bin/naoqi-bin

with the output saying

[I] 1650614881.924666 23993 qimessaging.servicedirectory: ServiceDirectory listener created on tcp://127.0.0.1:9559
[I] 1650614881.925642 23993 qimessaging.transportserver: TransportServer will listen on: tcp://127.0.0.1:9559
[I] 1650614881.927379 23993 qimessaging.servicedirectory: Registered Service "ServiceDirectory" (#1)
...

Here the robot's URL is 127.0.0.1:9559.

run your service in the virtual robot (Choregraphe must still be running, of course):

cd ~/pepper/tweety-service/app
python2 scripts/tweetyservice.py --qi-url localhost:34121

The output should look like:

[I] 1584373059.579170 4749 qimessaging.session: Session listener created on tcp://0.0.0.0:0
[I] 1584373059.579385 4749 qimessaging.transportserver: TransportServer will listen on: tcp://192.168.1.2:36873
[I] 1584373059.579394 4749 qimessaging.transportserver: TransportServer will listen on: tcp://127.0.0.1:36873

Keep this service running (in the background or foreground, i.e. use other shell/window for the qicli commands).

now you can communicate with your running service in the same way as with all other API services on the real robot:

use ^call(TweetyService.get()) in a dialog

direct call in a Python Box code:

def __init__(self):
   self.tweety = ALProxy('TweetyService')

def onInput_onStart(self):
    self.tts.say("číslo {}".format(self.tweety.get()))
    self.onStopped() #activate the output of the box

use the qicli command line tool:

alias qicli='"/opt/Softbank Robotics/Choregraphe Suite 2.5/bin/qicli" --qi-url localhost:34121'
qicli info TweetyService
qicli call TweetyService.get
qicli call TweetyService.set 2
qicli call TweetyService.get

with the output

099 [TweetyService]
  * Info:
   machine   f883b92e-3a87-44e5-aa70-4a3b78f4d937
   process   4749
   endpoints tcp://192.168.1.2:36873
             tcp://127.0.0.1:36873
  * Methods:
   100 get   Int8 ()
   101 reset Void ()
   102 set   Void (Int8)
   103 stop  Void ()
-------------------------------------------------------
0
null
2

if the service uses Python packages from the Softbank site-packages, the service needs before the first import:
```
import sys
sys.path.append('/opt/Softbank Robotics/Choregraphe Suite 2.5/lib/python2.7/site-packages')
```

Example app

This application implements the option 1 of the two integration solutions mentioned above, i.e. it does not use a service, just simple dialog variables with standard Choregraphe box flow.

Create new project in Choregraphe.
As usual, add Czech in project Properties.
Add Set Language box and select Czech. Warnings may appear when running this box on the virtual robot (ALSpeechRecognition is not available ...) but these are harmless now.
Right click the free area -> Create a new box -> Dialog...
in the Dialog -> Add Topic - choose Czech and Add to the package content as collaborative dialog (allows to start the dialog just by talking to the robot)
Connect onStart -> Set Language -> Dialog
Right click dialog box -> Edit box. Find Outputs and click on + button. Name: country, Type: string, Nature: punctual

In Project files double click on virustat_czc.top and enter

topic: ~virustat()
language: czc

u:(ahoj) ahoj, pro který stát tě zajímá statistika?
    u1:(Česko) dobrá, česko $country=Czechia
    u1:(Německo) dobrá, německo $country=Germany

Value of variable $country will be sent to the output named country.
Right click the free area -> Create a new box -> Python...
Find Inputs and click on the Edit icon next to onStart. set Type to String.
Find Outputs and click on + button. Name: returnStat, Type: string, Nature: punctual
Connect country output of the dialog with onStart input of the Python script.
Add Say Text box and connect returnStat output of the Python script with onStart input of Say Text box.
Connect onStopped output of Say Text box with onStopped.

Double-click the Python script to edit the script, and exchange autogenerated script with the following:

class MyClass(GeneratedClass):
    def __init__(self):
        GeneratedClass.__init__(self)

    def onLoad(self):
        #put initialization code here
        pass

    def onUnload(self):
        #put clean-up code here
        pass

    def onInput_onStart(self, country):
        #self.onStopped() #activate the output of the box
        self.logger.info("start")
        self.logger.info(self.getStat(country))
        self.returnStat(self.getStat(country))

    def onInput_onStop(self):
        self.onUnload() #it is recommended to reuse the clean-up as the box is stopped
        self.onStopped() #activate the output of the box

    def getStat(self, country):
        import urllib2
        url = 'https://opendata.arcgis.com/datasets/bbb2e4f589ba40d692fab712ae37b9ac_2.csv'
        response = urllib2.urlopen(url)
        csv = response.read()
        for line in csv.splitlines():
            data = line.split(',')
            if data[3] == country:
                return 'Počet nakažených je '+data[7]

Download the sample application (virustat.zip), unzip it and open in Choregraphe.

Other example applications

Explore example applications in /nlp/projekty/pepper/myapps:

kordisbot, Brno traffic dialog (runs own service DialogKordisbot, needs to install BeautifulSoup, reuqests and pyopenssl in the service environment)
sport_bot, dialog about Premiere League results
rozvrh, dialog about the faculty course schedule

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PV277 Programming Applications for Social Robots