NAME
blog.hoberg.ch - useless things for everybody
DESCRIPTION
blog.hoberg.ch is a text mode blog about BSD, Linux and typical DevOP content.
OPTIONS
- Ansible: java_cert module with trustcacerts option
When working with custom java key-/truststores you may find a new option to Ansibles java_cert module to trust an
imported certificate as trusted CAcert. This'll be needed when there's no chain of trust. With this PR there's no
workaround with keytool and command module nessesary.
Usage of task:
- name: Import trusted CA from SSL certificate
java_cert:
cert_path: /opt/certs/rootca.crt
keystore_path: /tmp/cacerts
keystore_pass: changeit
keystore_create: yes
state: present
cert_alias: LE_RootCA
trust_cacert: True
Github: #37708 Pullrequest
Download: java_cert.py
- postgresql-common 189 RPM for CentOS 7 with PGSQL10 support
Precompiled postgresql-common (build 189) RPM package for RHEL/CentOS 7 with PGSQL 10 support.
Changelog:
- New upstream release 189 (includes PGSQL 10 support)
- Fix systemd unit file for CentOS 7
Download: postgresql-common-189-1.el7.centos.noarch.rpm
- Stravlexa - An inofficial Alexa Skill for "Strava" Webservice
Sunday's morning while breakfasting - your mobile or tablet isn't in your kithen and you want to know your
last information from your sport activities? Ask Alexa! This Skill will provide basic information like your
weight your calories and your last activities like weightlifting, running biking and swimming with your last
30 activities on Strava. This Skill will need an API token which can be generated on Strava Settings.
Update: Version 1.1 supports all activity types of Strava.
#!/usr/bin/env python
"""
Name: stravlexa.py: An Alexa python skill to provide you your latest activities and your current weight on Strava.
Autor: Florian Paul Hoberg
Web: https://blog.hoberg.ch / https://github.com/florianpaulhoberg/stravlexa
Info: To run this Skill you will need an external webserver with valid SSL certificates, Amazon Developer and Strava account with API access.
Version: 1.1
"""
import urllib2, json
from flask import Flask
from flask_ask import Ask, statement
app = Flask(__name__)
ask = Ask(app, '/')
def get_stats_user(userid, token):
""" Get athletes own information """
url = "https://www.strava.com/api/v3/athletes/" + userid
req = urllib2.Request(url)
req.add_header('Authorization', 'Bearer ' + token)
response = urllib2.urlopen(req)
data = json.loads(response.read())
return data['weight'], data['firstname'], data['username'], data['country'], data['city'], data['friend_count'], data['sex']
def get_stats_activities(userid, token):
""" Get athletes last 30 activities """
url = "https://www.strava.com/api/v3/activities"
req = urllib2.Request(url)
req.add_header('Authorization', 'Bearer ' + token)
response = urllib2.urlopen(req)
data = json.loads(response.read())
return data
def split_activities(data, type_dict={}):
""" Check for all activity types and split them """
# Create an unique list in a dict of all
# activity types within the last 30 activities
for activity in data:
activity_type = activity['type']
if not activity_type in type_dict.keys():
type_dict[activity_type] = []
return type_dict
def generate_activities(data, type_dict):
""" Split metrics for all activity types """
# Copy created dict as template for every
# type of statistic to access the values
# more easy at a later time
time_dict = type_dict.copy()
avg_heartrate_dict = type_dict.copy()
avg_speed_dict = type_dict.copy()
distance_dict = type_dict.copy()
distance_dict = type_dict.copy()
all_activitiy_types = []
global_stats_time_dict = {}
global_stats_heartrate_dict = {}
global_stats_speed_dict = {}
global_stats_distance_dict = {}
global_count_dict = {}
# split every activity type to it's corresponding
# statistic dict
for activity in data:
activity_type = activity['type']
time_dict[activity_type] = time_dict[activity_type] + [ activity['elapsed_time'] ]
avg_heartrate_dict[activity_type] = avg_heartrate_dict[activity_type] + [ activity['average_heartrate'] ]
avg_speed_dict[activity_type] = avg_speed_dict[activity_type] + [ activity['average_speed'] ]
distance_dict[activity_type] = distance_dict[activity_type] + [ activity['distance'] ]
# Create an unique list of activity types
if not activity_type in all_activitiy_types:
all_activitiy_types.append(activity_type)
for single_activity in all_activitiy_types:
global_stats_time_dict[single_activity] = 0
global_stats_heartrate_dict[single_activity] = 0
# Speed value will be in meter per second
# define this as float to convert it later
# to kilometer per hour (European default)
global_stats_speed_dict[single_activity] = 0.0
global_stats_distance_dict[single_activity] = 0
for value in time_dict[single_activity]:
global_stats_time_dict[single_activity] = global_stats_time_dict[single_activity] + value
for value in avg_heartrate_dict[single_activity]:
global_stats_heartrate_dict[single_activity] = global_stats_heartrate_dict[single_activity] + value
for value in avg_speed_dict[single_activity]:
global_stats_speed_dict[single_activity] = global_stats_speed_dict[single_activity] + value
for value in distance_dict[single_activity]:
global_stats_distance_dict[single_activity] = global_stats_distance_dict[single_activity] + value
# Get average values for every activity and option
for single_activity in all_activitiy_types:
global_count_dict[single_activity] = len(time_dict[single_activity])
global_stats_time_dict[single_activity] = global_stats_time_dict[single_activity] / len(time_dict[single_activity])
global_stats_heartrate_dict[single_activity] = global_stats_heartrate_dict[single_activity] / len(avg_heartrate_dict[single_activity])
global_stats_speed_dict[single_activity] = global_stats_speed_dict[single_activity] / len(avg_speed_dict[single_activity])
global_stats_distance_dict[single_activity] = global_stats_distance_dict[single_activity] / len(distance_dict[single_activity])
# convert meter per second to kilometer per hour
global_stats_speed_dict[single_activity] = (float(global_stats_speed_dict[single_activity]) / 1000 * 3600)
return global_stats_time_dict, global_stats_heartrate_dict, global_stats_speed_dict, global_stats_distance_dict, all_activitiy_types, global_count_dict
def overall_stats(data):
""" Generate consolidated statistics over all activities """
overall_activity_time = 0
overall_activities = 0
for activity in data:
overall_activity_time = overall_activity_time + activity["elapsed_time"]
overall_activities = len(activity.values())
overall_activity_time = int(overall_activity_time) / 60 / 60
return overall_activities, overall_activity_time
def translate_german(t_german = {}):
""" Table of German translation of activities on Strava """
t_german["Ride"] = "Fahrrad fahren"
t_german["Run"] = "Laufen"
t_german["Swim"] = "Schwimmen"
t_german["WeightTraining"] = "Krafttraining"
t_german["Walk"] = "Spazieren"
t_german["Snowboard"] = "Snowboarden"
t_german["EBikeRide"] = "Faules Radfahren" # just kidding
t_german["Windsurf"] = "Surfen"
t_german["IceSkating"] = "Eislaufen"
t_german["InlineSkate"] = "Inline skaten"
t_german["Canoeing"] = "Kanu fahren"
t_german["Yoga"] = "Yoga"
t_german["VirtualRide"] = "virtuelle Aktivitaet"
return t_german
@ask.intent('AMAZON.HelpIntent')
def help():
speech_text = 'Du benoetigst fuer diesen Skill einen Strava Account und API Token.'
return question(speech_text).reprompt(speech_text).simple_card(speech_text)
@ask.intent('AMAZON.StopIntent')
def stop():
speech_text = 'Gehst du schon zum Sport? Viel Spass!'
return question(speech_text).reprompt(speech_text).simple_card(speech_text)
@ask.intent('AMAZON.CacnelIntent')
def cancel():
speech_text = 'Gehst du schon zum Sport? Viel Spass!'
return question(speech_text).reprompt(speech_text).simple_card(speech_text)
@ask.intent('GetEventsIntent')
def main(count_activities={}):
# Define your Strava userid and your API token
userid = ""
token = ""
user_weight, user_firstname, user_username, user_country, user_city, user_friend_count, user_sex = get_stats_user(userid, token)
data = get_stats_activities(userid, token)
type_dict = split_activities(data)
global_stats_time_dict, global_stats_heartrate_dict, global_stats_speed_dict, global_stats_distance_dict, all_activitiy_types, global_count_dict = generate_activities(data, type_dict)
overall_activities, overall_activity_time = overall_stats(data)
# Create German translateion
global_stats_time_dict_ger = global_stats_time_dict.copy()
global_stats_time_dict_ger = translate_german(global_stats_time_dict_ger)
# Create speech event
user_info = user_firstname + " du wiegst aktuell " + str(user_weight) + " Kilogramm "
user_stats = "und hast in den letzten 30 Tagen " + str(overall_activities) + " Aktivitaeten in " + str(overall_activity_time) + " Stunden absolviert"
# Create a list for every single activity for speech output
activity_speech = []
for single_activity in all_activitiy_types:
activity_speech.append(global_stats_time_dict_ger[single_activity] + ": " + str(global_count_dict[single_activity]) + " mal. Im Schnitt: " + str(int(global_stats_distance_dict[single_activity])/1000) + " Kilometer zurueckgelegt " + str(int(global_stats_time_dict[single_activity]/60)) + " Minuten verbracht! Herzfrequenz: " + str(int(global_stats_heartrate_dict[single_activity])) + " Geschwindigkeit: " + str(int(global_stats_speed_dict[single_activity])) + " kmh")
# Alexa speech output
speech_text = "\n"
speech_text += str(user_info)
speech_text += str(user_stats)
speech_text += str(activity_speech)
speech_text += ""
return statement(speech_text).simple_card(speech_text)
main()
if __name__ == '__main__':
app.run(host="0.0.0.0")
Download: stravlexa
Download: Github
- Flowexa - An inofficial Alexa Skill for "Polar Flow" Webservice
Sunday's morning while breakfasting - your mobile or tablet isn't in your kithen and you want to know your
last information from your sport activities? Ask Alexa! This Skill will provide basic information like your
weight (if you use "Polar Balance"), your calories and your last activities like weightlifting, running
biking and swimming within the last 30 days.
#!/usr/bin/env python
"""
name: flowexa.py
autor: Florian Paul Hoberg
description: This inofficial Alexa Skill will provide your last activities for weightlifting,
running, biking and swimming within the last 30 days. No API access is nessessary,
usual login credentials will be enough. To get additional information like user
weight a patched FlowClient library for Python will be needed and can be obtained:
https://github.com/florianpaulhoberg/flow-client/blob/patch-1/flow/client.py
note: ATM this is only available in German.
"""
import datetime
from flow import FlowClient
from flask import Flask
from flask_ask import Ask, statement
app = Flask(__name__)
ask = Ask(app, '/')
def sum_objects(object, sum_return=0.0):
""" Generate sum of inputs from list entries if they are set """
for float in object:
if float is not None:
sum_return = float + sum_return
return sum_return
def get_workouts(username, password, weightlifting_duration=[], weightlifting_calories=[], running_duration=[], running_calories=[], running_distance=[], biking_duration=[], biking_calories=[], biking_distance=[], swimming_duration=[], swimming_calories=[], swimming_distance=[]):
""" Get remote user and activities from Polar Flow service and group them """
client = FlowClient()
client.login(username, password)
activity = client.activities()
# Get global user information (will need patched FlowClient:
# https://github.com/florianpaulhoberg/flow-client/blob/patch-1/flow/client.py )
activity_count = len(activity)
userweight = activity[0].weight()
# Split activities and group them by kind of sport
for single_activity in activity:
# Weightlifting = d1ce94078aec226be28f6c602e6803e1-2015-10-20_13_45_19
if "d1ce94078aec226be28f6c602e6803e1-2015-10-20_13_45_19" in single_activity.iconUrl:
weightlifting_duration.append(single_activity.duration)
weightlifting_calories.append(single_activity.calories)
# Treadmile = d039f159dd0b62dc0a1ca72d82af2f0b-2015-10-20_13_46_28
# Running = 808d0882e97375e68844ec6c5417ea33-2015-10-20_13_46_22
if "d039f159dd0b62dc0a1ca72d82af2f0b-2015-10-20_13_46_28" or "808d0882e97375e68844ec6c5417ea33-2015-10-20_13_46_22" in single_activity.iconUrl:
running_duration.append(single_activity.duration)
running_calories.append(single_activity.calories)
running_distance.append(single_activity.distance)
# Biking = 561a80f6d7eef7cc328aa07fe992af8e-2015-10-20_13_46_03
if "561a80f6d7eef7cc328aa07fe992af8e-2015-10-20_13_46_03" in single_activity.iconUrl:
biking_duration.append(single_activity.duration)
biking_calories.append(single_activity.calories)
biking_distance.append(single_activity.distance)
# Swimming = f4197b0c1a4d65962b9e45226c77d4d5-2015-10-20_13_45_26
if "f4197b0c1a4d65962b9e45226c77d4d5-2015-10-20_13_45_26" in single_activity.iconUrl:
swimming_duration.append(single_activity.duration)
swimming_calories.append(single_activity.calories)
swimming_distance.append(single_activity.distance)
return weightlifting_duration, weightlifting_calories, running_duration, running_calories, running_distance, biking_duration, biking_calories, biking_distance, swimming_duration, swimming_calories, swimming_distance, activity_count, userweight
@ask.intent('AMAZON.HelpIntent')
def help():
speech_text = 'Du benoetigst fuer diesen Skill einen Polar Flow Account.'
return question(speech_text).reprompt(speech_text).simple_card(speech_text)
@ask.intent('AMAZON.StopIntent')
def stop():
speech_text = 'Gehst du schon zum Sport? Viel Spass!'
return question(speech_text).reprompt(speech_text).simple_card(speech_text)
@ask.intent('AMAZON.CacnelIntent')
def cancel():
speech_text = 'Gehst du schon zum Sport? Viel Spass!'
return question(speech_text).reprompt(speech_text).simple_card(speech_text)
@ask.intent('GetEventsIntent')
def main():
""" Run the whole magic """
# FlowLogin
firstname ="YOUR-FRISTNAME"
username = "YOUR-FLOW-EMAIL"
password = "YOUR-PASSWORD"
# Get global user information and workouts/activities
weightlifting_duration, weightlifting_calories, running_duration, running_calories, running_distance, biking_duration, biking_calories, biking_distance, swimming_duration, swimming_calories, swimming_distance, activity_count, userweight = get_workouts(username, password)
# Generate metrics for all groups
weightlifting_duration_overall = sum_objects(weightlifting_duration)
weightlifting_calories_overall = sum_objects(weightlifting_calories)
running_duration_overall = sum_objects(running_duration)
running_calories_overall = sum_objects(running_calories)
running_distance_overall = sum_objects(running_distance)
biking_duration_overall = sum_objects(biking_duration)
biking_calories_overall = sum_objects(biking_calories)
biking_distance_overall = sum_objects(biking_distance)
swimming_duration_overall = sum_objects(swimming_duration)
swimming_calories_overall = sum_objects(swimming_calories)
swimming_distance_overall = sum_objects(swimming_distance)
# To get time of hours we will need to / 1000 / 60 * 0.0166667
overall_time_min = (weightlifting_duration_overall + running_duration_overall + biking_duration_overall + swimming_duration_overall) / 1000 / 60
overall_time_hours = int(overall_time_min) * 0.0166667
overall_time_hours = int(overall_time_hours)
overall_calories = weightlifting_calories_overall + running_calories_overall + biking_calories_overall + swimming_calories_overall
# Rehashing output information for speech output
skill_output_info = "Gratulation " + firstname + " ! Du hast in den letzten 30 Tagen " + str(activity_count) + " Trainingseinheiten in insgesamt " + str(overall_time_hours) + " Stunden absolviert "
skill_output_weight = " Dein aktuelles Gewicht betraegt " + str(userweight) + " Kilogramm dabei hast du insgesamt " + str(int(overall_calories)) + " Kalorien verbrannt!"
skill_output_weightlifting = "Beim Kraftsport bist du " + str(len(weightlifting_duration)) + " mal gewesen! "
skill_output_running = " Laufen " + str(int(running_distance_overall)/1000) + " Kilometer! "
skill_output_biking = " Radfahren " + str(int(biking_distance_overall)/1000) + " Kilometer! "
skill_output_schwimming = " Schwimmen " + str(int(swimming_distance_overall)/1000) + " Kilometer! "
skill_output_overall = skill_output_info + skill_output_weight + skill_output_weightlifting + skill_output_running + skill_output_biking + skill_output_schwimming
# Speech output for your Echo via Skill
speech_text = "\n"
speech_text += str(skill_output_overall)
speech_text += ""
return statement(speech_text)
main()
if __name__ == '__main__':
app.run(host="0.0.0.0")
Download: flowexa
Download: Github
- Stravlexa - An inofficial Alexa Skill for "Strava" Webservice updated
Sunday's morning while breakfasting - your mobile or tablet isn't in your kithen and you want to know your
last information from your sport activities? Ask Alexa! This Skill will provide basic information like your
weight your calories and your last activities like weightlifting, running biking and swimming with your last
30 activities on Strava. This Skill will need an API token which can be generated on Strava Settings.
Update: This version will get all activity types dynamically.
#!/usr/bin/env python
"""
Name: stravlexa.py: An Alexa python skill to provide you your latest activities and your current weight on Strava.
Autor: Florian Paul Hoberg
Web: https://blog.hoberg.ch / https://github.com/florianpaulhoberg/stravlexa
Info: To run this Skill you will need an external webserver with valid SSL certificates, Amazon Developer and Strava account with API access.
"""
import urllib2, json
from flask import Flask
from flask_ask import Ask, statement
app = Flask(__name__)
ask = Ask(app, '/')
def get_stats_user(userid, token):
""" Get athletes own information """
url = "https://www.strava.com/api/v3/athletes/" + userid
req = urllib2.Request(url)
req.add_header('Authorization', 'Bearer ' + token)
response = urllib2.urlopen(req)
data = json.loads(response.read())
return data['weight'], data['firstname'], data['username'], data['country'], data['city'], data['friend_count'], data['sex']
def get_stats_activities(userid, token):
""" Get athletes last 30 activities """
url = "https://www.strava.com/api/v3/activities"
req = urllib2.Request(url)
req.add_header('Authorization', 'Bearer ' + token)
response = urllib2.urlopen(req)
data = json.loads(response.read())
return data
def split_activities(data, type_dict={}):
""" Check for all activity types and split them """
# Create an unique list in a dict of all
# activity types within the last 30 activities
for activity in data:
activity_type = activity['type']
if not activity_type in type_dict.keys():
type_dict[activity_type] = []
return type_dict
def generate_activities(data, type_dict):
""" Split metrics for all activity types """
# Copy created dict as template for every
# type of statistic to access the values
# more easy at a later time
time_dict = type_dict.copy()
avg_heartrate_dict = type_dict.copy()
avg_speed_dict = type_dict.copy()
distance_dict = type_dict.copy()
distance_dict = type_dict.copy()
all_activitiy_types = []
global_stats_time_dict = {}
global_stats_heartrate_dict = {}
global_stats_speed_dict = {}
global_stats_distance_dict = {}
global_count_dict = {}
# split every activity type to it's corresponding
# statistic dict
for activity in data:
activity_type = activity['type']
time_dict[activity_type] = time_dict[activity_type] + [ activity['elapsed_time'] ]
avg_heartrate_dict[activity_type] = avg_heartrate_dict[activity_type] + [ activity['average_heartrate'] ]
avg_speed_dict[activity_type] = avg_speed_dict[activity_type] + [ activity['average_speed'] ]
distance_dict[activity_type] = distance_dict[activity_type] + [ activity['distance'] ]
# Create an unique list of activity types
if not activity_type in all_activitiy_types:
all_activitiy_types.append(activity_type)
for single_activity in all_activitiy_types:
global_stats_time_dict[single_activity] = 0
global_stats_heartrate_dict[single_activity] = 0
# Speed value will be in meter per second
# define this as float to convert it later
# to kilometer per hour (European default)
global_stats_speed_dict[single_activity] = 0.0
global_stats_distance_dict[single_activity] = 0
for value in time_dict[single_activity]:
global_stats_time_dict[single_activity] = global_stats_time_dict[single_activity] + value
for value in avg_heartrate_dict[single_activity]:
global_stats_heartrate_dict[single_activity] = global_stats_heartrate_dict[single_activity] + value
for value in avg_speed_dict[single_activity]:
global_stats_speed_dict[single_activity] = global_stats_speed_dict[single_activity] + value
for value in distance_dict[single_activity]:
global_stats_distance_dict[single_activity] = global_stats_distance_dict[single_activity] + value
# Get average values for every activity and option
for single_activity in all_activitiy_types:
global_count_dict[single_activity] = len(time_dict[single_activity])
global_stats_time_dict[single_activity] = global_stats_time_dict[single_activity] / len(time_dict[single_activity])
global_stats_heartrate_dict[single_activity] = global_stats_heartrate_dict[single_activity] / len(avg_heartrate_dict[single_activity])
global_stats_speed_dict[single_activity] = global_stats_speed_dict[single_activity] / len(avg_speed_dict[single_activity])
global_stats_distance_dict[single_activity] = global_stats_distance_dict[single_activity] / len(distance_dict[single_activity])
# convert meter per second to kilometer per hour
global_stats_speed_dict[single_activity] = (float(global_stats_speed_dict[single_activity]) / 1000 * 3600)
return global_stats_time_dict, global_stats_heartrate_dict, global_stats_speed_dict, global_stats_distance_dict, all_activitiy_types, global_count_dict
def overall_stats(data):
""" Generate consolidated statistics over all activities """
overall_activity_time = 0
overall_activities = 0
for activity in data:
overall_activity_time = overall_activity_time + activity["elapsed_time"]
overall_activities = len(activity.values())
overall_activity_time = int(overall_activity_time) / 60 / 60
return overall_activities, overall_activity_time
def translate_german(t_german = {}):
""" Table of German translation of activities on Strava """
t_german["Ride"] = "Fahrrad fahren"
t_german["Run"] = "Laufen"
t_german["Swim"] = "Schwimmen"
t_german["WeightTraining"] = "Krafttraining"
t_german["Walk"] = "Spazieren"
t_german["Snowboard"] = "Snowboarden"
t_german["EBikeRide"] = "Faules Radfahren" # just kidding
t_german["Windsurf"] = "Surfen"
t_german["IceSkating"] = "Eislaufen"
t_german["InlineSkate"] = "Inline skaten"
t_german["Canoeing"] = "Kanu fahren"
t_german["Yoga"] = "Yoga"
t_german["VirtualRide"] = "virtuelle Aktivitaet"
return t_german
@ask.intent('AMAZON.HelpIntent')
def help():
speech_text = 'Du benoetigst fuer diesen Skill einen Strava Account und API Token.'
return question(speech_text).reprompt(speech_text).simple_card(speech_text)
@ask.intent('AMAZON.StopIntent')
def stop():
speech_text = 'Gehst du schon zum Sport? Viel Spass!'
return question(speech_text).reprompt(speech_text).simple_card(speech_text)
@ask.intent('AMAZON.CacnelIntent')
def cancel():
speech_text = 'Gehst du schon zum Sport? Viel Spass!'
return question(speech_text).reprompt(speech_text).simple_card(speech_text)
@ask.intent('GetEventsIntent')
def main(count_activities={}):
# Define your Strava userid and your API token
userid = ""
token = ""
user_weight, user_firstname, user_username, user_country, user_city, user_friend_count, user_sex = get_stats_user(userid, token)
data = get_stats_activities(userid, token)
type_dict = split_activities(data)
global_stats_time_dict, global_stats_heartrate_dict, global_stats_speed_dict, global_stats_distance_dict, all_activitiy_types, global_count_dict = generate_activities(data, type_dict)
overall_activities, overall_activity_time = overall_stats(data)
# Create German translateion
global_stats_time_dict_ger = global_stats_time_dict.copy()
global_stats_time_dict_ger = translate_german(global_stats_time_dict_ger)
# Create speech event
user_info = user_firstname + " du wiegst aktuell " + str(user_weight) + " Kilogramm "
user_stats = "und hast in den letzten 30 Tagen " + str(overall_activities) + " Aktivitaeten in " + str(overall_activity_time) + " Stunden absolviert"
# Create a list for every single activity for speech output
activity_speech = []
for single_activity in all_activitiy_types:
activity_speech.append(global_stats_time_dict_ger[single_activity] + ": " + str(global_count_dict[single_activity]) + " mal. Im Schnitt: " + str(int(global_stats_distance_dict[single_activity])/1000) + " Kilometer zurueckgelegt " + str(int(global_stats_time_dict[single_activity]/60)) + " Minuten verbracht! Herzfrequenz: " + str(int(global_stats_heartrate_dict[single_activity])) + " Geschwindigkeit: " + str(int(global_stats_speed_dict[single_activity])) + " kmh")
# Alexa speech output
speech_text = "\n"
speech_text += str(user_info)
speech_text += str(user_stats)
speech_text += str(activity_speech)
speech_text += ""
return statement(speech_text).simple_card(speech_text)
main()
if __name__ == '__main__':
app.run(host="0.0.0.0")
Download: stravlexa
Download: Github
- Ikea Tradfri Gateway firmware 1.2.42 broke coap connections with dynamic DTLS identities
After watching a movie this evening my final workflow didn't start as usual (shutdown TV
and enable overhead lights at 30%). After debugging without any success for the given
401 Unauthorized messages, I found out that my Ikea Tradfri gateway got silently updated to
version 1.2.42 with an interesting changelog to support DTLS sessions for CoAP.
Home Assistant got notified by Ikea and posted a hint on Twitter which made
it easy to fix my Homebridge (@NorthernMan54 Homebridge fork for Alexa support) and the
homebridge-tradfri plugin. As a quick fix you may generate your uniqe credentials
that'll stay for lifetime:
/usr/local/bin/coap-client -m post -u "Client_identity" -k "YOUR-TRADFRI-GW-PSK" -e '{"9090":"FOOBAR"}' "coaps://10.2.2.2:5684/15011/9063"
You will get something retunred like:
{"9091":"cKwtcUffs34gFfnhfJ","9029":"1.2.0042"} # cKwtcUffs34gFfnhfJ is our interesting part
Now, requests can be send by:
coap-client -m get -u "FOOBAR" -k "cKwtcUffs34gFfnhfJ" "coaps://10.2.2.2.51:5684/15011/9063"
When running any plugin based on coap, remember to replace your gw key and user with your new ones e.g. on homebrdige-tradfri:
--- tradfri/coap.js.bak 2017-11-01 02:27:50.141793626 +0100
+++ tradfri/coap.js 2017-11-01 02:45:17.659922013 +0100
@@ -26,7 +26,7 @@ var COAP;
return new Promise((resolve, reject) => {
const endpoint = util.format('coaps://%s:%s%s', this.hostname, this.port, uri);
this.log('GET:', endpoint);
- const cmd = child_process_1.spawn(this.binary, ['-u', 'Client_identity',
+ const cmd = child_process_1.spawn(this.binary, ['-u', 'FOOBAR',
'-k', 'cKwtcUffs34gFfnhfJ', endpoint
]);
let resp = "";
@@ -45,7 +45,7 @@ var COAP;
return new Promise((resolve, reject) => {
const endpoint = util.format('coaps://%s:%s%s', this.hostname, this.port, uri);
this.log('PUT:', endpoint);
- const cmd = child_process_1.spawn(this.binary, ['-f', '-', '-u', 'Client_identity',
+ const cmd = child_process_1.spawn(this.binary, ['-f', '-', '-u', 'FOOBAR',
'-k', 'cKwtcUffs34gFfnhfJ', '-m', 'put', endpoint
]);
cmd.stdin.write(JSON.stringify(payload));
After that I could control my tradfri lights again with Siri/HomeKit and Alexa.
- Elephant Shed - OpenSource PostgreSQL appliance released
Elephant Shed, an OpenSource PostgreSQL appliance for business got released by
credativ GmbH (PGConf, DebConf sponsor) today. Elephant Shed will be longtime
maintained by credativ's database specialists with optional support. This appliance
is fully OpenSource and can be be reviewed on GitHub. Even experienced PostgreSQL
administrators will only hardly find an area not covered by Elephant Shed like:
o Administration of PostgreSQL instances/cluster
o High-Level administration of databases and database users
o Performance monitoring that bundles all relevant system as well as PostgreSQL metrics
o Automated log file analysis and report generation
o Preconfigured backup to protect data
It can be installed in different ways. Beside the source code there's also a
package repository and upcoming images for Microsoft Azure, Amazon AWS, Goolge Cloud
Hasicorps' Vagrant and VMWare.
Find out more on elephant-shed.io and GitHub.
- Python JBoss / Wildfly JVM heap monitor for Icinga (Nagios)
Simple Python monitor for Icinga/Nagios to check JVM heap space of JBoss
& Wildfly via jboss-cli. Make sure to set path to your jboss-cli and
define your desired warn-/crit limits.
#!/usr/bin/env python
# check_jboss_jvm_heap.py
# monitor JBoss / Wildfly JVM heap space
# Florian Paul Hoberg
import subprocess
import os
import sys
import json
import tempfile
import argparse
from jbossply.jbossparser import JbossParser
# Change to your settings
JBOSS_CLI = "/opt/wildfly-10.1.0.Final/bin/jboss-cli.sh"
TMP_PATH = "/tmp/jboss_cli.tmp"
# Do not change anything below here
JBOSS_MEM = "-c \"/core-service=platform-mbean/type=memory:read-attribute(name=heap-memory-usage)\""
parser = JbossParser()
argparser = argparse.ArgumentParser(description='Following options are possible:')
def write_file():
""" write jboss content to file """
try:
with open(TMP_PATH, 'w') as file:
test = subprocess.Popen(JBOSS_CLI + " " + JBOSS_MEM, shell=True, stdout=file)
test.communicate()[0]
except IOError as e:
print "I/O error({0}): {1}".format(e.errno, e.strerror)
def open_file():
""" open file to buffer and convert jboss output to json """
try:
with open(TMP_PATH, 'r') as file:
buffer = file.read()
json = parser.parse(buffer)
heap_max = json['result']['max']
heap_used = json['result']['used']
return heap_max, heap_used
except IOError as e:
print "I/O error({0}): {1}".format(e.errno, e.strerror)
def main():
""" Check JBoss JVM heap space """
argparser.add_argument('-w', type=int, help='Define value in MB to raise warn state. (default: 150 MB)')
argparser.add_argument('-c', type=int, help='Define value in MB to raise critical state. (default: 80 MB)')
cliargs = argparser.parse_args()
if cliargs.w is None:
cliargs.w = 80
if cliargs.c is None:
cliargs.c = 150
HEAP_WARN = cliargs.w * 1024 * 1024
HEAP_CRIT = cliargs.c * 1024 * 1024
write_file()
heap_max, heap_used = open_file()
heap_free = int(heap_max) - int(heap_used)
heap_max_calc = heap_free + heap_used
if heap_free < HEAP_WARN and heap_free > HEAP_CRIT:
print("WARN: JVM heap is warn - SIZE:", heap_max_calc / 1024 / 1024, "MB | Free:", heap_free / 1024 / 1024, "MB | Used:", heap_used / 1024 / 1024, "MB")
exit(1)
if heap_free < HEAP_CRIT:
print("CRIT: JVM heap is critical - SIZE:", heap_max_calc / 1024 / 1024, "MB | Free:", heap_free / 1024 / 1024, "MB | Used:", heap_used / 1024 / 1024, "MB")
exit(2)
print("OK: JVM heap is ok - SIZE:", heap_max_calc / 1024 / 1024, "MB | Free:", heap_free / 1024 / 1024, "MB | Used:", heap_used / 1024 / 1024, "MB")
main()
Download: check_jboss_jvm_heap.py | GitHub
- Wildfly/JBoss 10/11: Serve multiple webapps on different ports with vhosts
There're many HowTos out in the web how to serve multiple Webapps on
different ports, but the most of them will tell you to duplicate your
systemd unit or init file (wt. -Djboss.socket.binding.port-offset=200)
and to copy your standalone directory. This will spawn an additional
process. If you want to serve your Webapp within one process and only
one config file you will need to work with VHosts. This will require
modifications on you .war or .ear file to bind it to the corresponding
VHost.
The following steps are requeired:
1. Add your new VHost in your standalone.xml:
<server name="mynextwebapp-server" default-host="mynextwebapp-host">
<http-listener name="mynextwebapp-listener" socket-binding="mynextwebapp-manager"/>
<host name="mynextwebapp-host" alias="localhost">
<location name="/" handler="welcome-content"/>
<filter-ref name="server-header"/>
<filter-ref name="x-powered-by-header"/>
</host>
</server>
2. Add a socket-binding group to your new VHost in your standalone.xml:
<socket-binding name="mynextwebapp-manager" port="8081"/>
3. Now, it's time to modify your webapp (.war / .ear file):
Extract your .war / .ear file:
jar -xvf $file
Within your WEB-INF file modify your "jboss-web.xml":
<jboss-web>
<context-root>/
<virtual-host>mynextwebapp-host
<server-instance>mynextwebapp-serve
</jboss-web>
Rebuild your .war / .ear file:
jar -cfv $filename $content
Move the new .war / .ear file to wildflys autodeploy directory and
it'll deploy it under http://$serverip:8081/
And yes, there's another possibility with setting the webapp to a
different context-root. This is possible but you should make sure
that the served webapp will never use absolute pathes that won't
match anymore outside of the expected context-root path.
Extract your .war / .ear file:
jar -xvf $file
Within your WEB-INF file modify your "jboss-web.xml":
<jboss-web>
<context-root>/mynewcontextpath/
</jboss-web>
Create an empty "bean.xml" file.
Rebuild your .war / .ear file:
jar -cfv $filename $content
Move the new .war / .ear file to wildflys autodeploy directory and
it'll deploy it under http://$serverip:8080/mynewcontextpath/
- A Python 32Bit App finder for MacOS / OSX
Because Apple is going to drop support for 32bit Apps on iOS and OSX
(macOS) in the near future you'll may have a look for your local
installed Apps on your system. With this small Python script you'll
get an overview:
#!/usr/bin/env python
# 2017-08-24 macos_osx_32bit_app_finder.py
# Florian Paul Hoberg
# This will find your 32bit apps
# on your local MacOS / OSX system
# usage: macos_osx_32bit_app_finder.py
import sys
import os
from subprocess import check_output
before=6
after=0
v_systemprofile = check_output(["system_profiler", "SPApplicationsDataType"])
f_systemprofile = "/tmp/systemprofile.tmp.txt"
def write_systemprofile():
""" Write systemprofile file """
with open(f_systemprofile, 'wb') as f_spfw:
f_spfw.write(v_systemprofile)
def append(size, data, x):
""" Append/pop buffer """
if len(data)>=size:
data.pop(0)
data.append(x)
def readconv_systemprofile():
""" Read/convert systemprofile file """
buffer = []
with open(f_systemprofile, 'r') as f_spfwr:
print "Installed 32bit Apps on your system:"
print "-"*40
for line in f_spfwr:
line=line.strip()
if "(Intel): No" in line:
if buffer:
print(buffer)
buffer=[]
after_count=after
while after_count < after:
after_count+=1
try:
line=f.next().strip()
except: pass
else:
print line
if "match" in line:
after_count=0
else:
append(before,buffer,line)
write_systemprofile()
readconv_systemprofile()
Download: macos_osx_32bit_app_finder.py
- certbot for letsencrypt in FreeBSD may conflict with acme version
Some versions of Letsencrypt's certbot client may fail on FreeBSD due
to a version conflict of acme's dependency which is easy to resolve.
Just to fix the folowwing content:
/usr/local/lib/python2.7/site-packages/certbot-0.15.0-py2.7.egg-info/requires.txt:
--- /usr/local/lib/python2.7/site-packages/letsencrypt-0.5.0-py2.7.egg-info/requires.txt 2017-08-24 07:23:40.331534000 -0200
+++ /usr/local/lib/python2.7/site-packages/letsencrypt-0.5.0-py2.7.egg-info/requires.txt.fix 2017-08-24 07:23:26.443221000 -0200
@@ -1,4 +1,4 @@
-acme==0.5.0
+acme>=0.5.0
ConfigArgParse>=0.9.3
configobj
cryptography>=0.7
Download: certbot-0.15.0_fbsd_acmeversionrequire.diff
- FreeBSD packet filter 'pf' config template
A small template for FeeBSD's packetfilter for firewalling in/out on IPv4 and IPv6
with default policy 'drop'. This includes different network interfaces, mgmt networks
(e.g. CIDR networks) and possible monitoring systems. Only tcp/80,443 are as state
established allowed in this template. Make sure to replace it with your values.
Download: pf.conf.template | GitHub
- nginx servername string replace with binary patcher in python3
As already in this blogpost described it's also possible to patch the nginx
binary instead of recompiling the whole package just to modify the servertoken
like "Server: nginx/1.13.3". In fact that it's just possible to hide the
server version you will need to recompile or patch to get rid of it.
For patching the binary on Linux or FreeBSD you may take a little
Python3 script called nginx-srvname-patcher.py. Short reminder that
you may only use up to 5 chars to replace. You'll find it here:
#!/usr/bin/env python3
# 2017-08-11 nginx-srvname-patcher.py
# Florian Paul Hoberg
# This will patch your nginx binary file
# from Server: nginx to Server: B00B
# You can change B00B to anything else
# but limited to max. 5 chars
#
# License: BSD 3-Clause License
# Python Version: 3
# usage: nginx-srvname-patcher.py nginx-bin-file
import sys
import re
SERVER_NAME_ORIG = "Server: nginx"
ENCODED_SERVER_NAME_ORIG = SERVER_NAME_ORIG.encode()
SERVER_NAME = "Server: B00B"
ENCODED_SERVER_NAME = SERVER_NAME.encode()
NGINX_BIN = "nginx_new"
def binary_nginx_patch(path):
""" Read binary to buffer"""
with open(path, 'rb') as f:
buffer = f.read()
return buffer
def check_nginx_string(data):
""" Check for original 'Server: nginx' content in raw data"""
if ENCODED_SERVER_NAME_ORIG in data:
print("OK: Found expected original string:\n", SERVER_NAME_ORIG)
patch_true = input("MSG: Proceed with patching? [y/N] ")
if patch_true == "y":
print("OK: Start patching nginx binary.", file=sys.stderr)
else:
print("WARN: Patching stopped.", file=sys.stderr)
exit(2)
def write_new_nginx_binary(data_out):
""" Write patched binary file """
with open(NGINX_BIN, 'wb') as new_nginx_binary:
data_out = data_out.replace(ENCODED_SERVER_NAME_ORIG, ENCODED_SERVER_NAME)
new_nginx_binary.write(data_out)
print("OK: Patching done. New binary:", NGINX_BIN)
def main():
if len(sys.argv) > 0:
data = binary_nginx_patch(sys.argv[1])
check_nginx_string(data)
write_new_nginx_binary(data)
try:
main()
except FileNotFoundError:
print("CRIT: Please define path to nginx binary.")
Download: nginx-srvname-patcher.py | GitHub
- A stay at the "Linux Hotel" Villa Vogel Sang in Essen for Python & DevOP
For the last five workdays I've been sent to the Linux Hotel in Essen (Germany) to push
up my Python skills. Unfortunately I decided to not stay in the hotel and travelled by
train these days. This should become uncomfortable. But first let me tell you
something about Linux Hotel.
Linux Hotel is a synonym for (training) congresses in opensource related topics like
programming in C, Perl, Python; IT specialist related topics like LPIC certification,
LDAP and other software and even DevOp content like Ansible, Puppet, Chef, Foreman...
As I already told I decided to travel instead of staying there over night which
resulted in a heavy travel time just to see my girl daily. It was my first stay
there and I didn't know that it should become that impressive.
On our first day we got told on our breakfast that almost everything is included
for free. You do not need to worry about breakfast, lunch or dinner. There's also
ice-cream, cookies, cakes and candies the whole day. You get water, softdrinks like
Coca-Cola, selfmade Cola, ClubMate, coffee, tea, alcoholics like different sorts of
beer and whine the whole day for free. Yes - this is also included. This are things
that made it really easy to cool down and chill in the evening after your course -
if you stay in the hotel! For further socializing there're additional social events
like driving GoCart, going out to Essen, flying in the fly simulator. You're not
interested? Maybe you'll take a look for the gym, go for a run or relax in the sauna.
There're so many possibilities to make your stay as comfortable as possible. Next
time I'll stay there defnetly over night. This is really a great concept and it's
money worth instead of regular conferencing centers.
- Replace nginx server header without modifying headers or recompile of nginx
If you're fine with patching a binary file there's a possible way to hide or replace
the server header from nginx. Unfortunately it's also shown with turned off servertokens.
o As root stop any running nginx process and backup your nginx binary
o Open your nginx binary with an editor (e.g. vi `which nginx`)
o Search for pattern "Server: nginx" (should look like "^@^@^@^@^@^@^@^@^@^@Server: nginx^M")
o Replace nginx with a string limited by max. 5 chars (e.G. B00Bs)
o Start nginx again
o check for your new string (curl -I $IP |grep -i server)
- Welcome to floblog a minimal text based blog enine
Welcome to floblog - an opensource minimal text based blog enine that does not need
any database, easy to backup and easy to use. There is no need for any CSS, JS or
images for layout - just focus the content!
COMPATIBILITY
This text mode blog is powered by floblog and compatible with any browser and can also be
shown on alternative browsers like links, lynx or just curl. No CSS, JS or images will make
it hard to read. Just focus the content. Written in Python3.
blog.hoberg.ch 2018-04-26 blog.hoberg.ch
[Impressum: hoberg.ch]