def test_time_bucket(self):
now = datetime.now(pytz.timezone(app_config.PROJECT_TIMEZONE))
five_hours_ago = now - timedelta(hours=5)
ten_hours_ago = now - timedelta(hours=10)
bucket = TimeTools.time_bucket(five_hours_ago)
self.assertEqual(bucket, '4 hours')
bucket = TimeTools.time_bucket(ten_hours_ago)
self.assertEqual(bucket, '8 hours')
def test_time_bucket(self):
now = datetime.now(pytz.timezone(app_config.PROJECT_TIMEZONE))
five_hours_ago = now - timedelta(hours=5)
ten_hours_ago = now - timedelta(hours=10)
bucket = TimeTools.time_bucket(five_hours_ago)
self.assertEqual(bucket, '4 hours')
bucket = TimeTools.time_bucket(ten_hours_ago)
self.assertEqual(bucket, '8 hours')
def test_humanist_time_bucket(self):
bucket = TimeTools.humanist_time_bucket({'minutes': 5, 'seconds': 5})
self.assertEqual(bucket, '5 minutes 5 seconds')
bucket = TimeTools.humanist_time_bucket({'minutes': 0, 'seconds': 1})
self.assertEqual(bucket, '1 second')
bucket = TimeTools.humanist_time_bucket({'minutes': 5, 'seconds': 0})
self.assertEqual(bucket, '5 minutes')
bucket = TimeTools.humanist_time_bucket({'minutes': 1, 'seconds': 1})
self.assertEqual(bucket, '1 minute 1 second')
def handle_slug_inquiry(self, message):
"""
Respond to an inquiry about the slug with stats and charts
"""
match = re.search(self.SLUG_SEARCH_REGEX, message.body["text"])
slug = match.group(1)
if slug:
# Try to match the story to a slug to accurately get a team
# The Google Analytics property ID comes from the team config
# We use the default team if none is found
stories = Story.select().where(Story.slug.contains(slug))
team = self.config.get_team_for_stories(stories)
linger_rows = self.get_linger_data(team=team, slug=slug)
if not linger_rows:
return {"text": "Sorry, I wasn't able to find linger rate stats for %s" % slug}
median = NPRLingerRate.get_median(linger_rows)
print "Got median"
print median
people = "{:,}".format(median["total_people"])
time_text = TimeTools.humanist_time_bucket(median)
reply = u"*%s* people spent a median *%s* on `%s`." % (people, time_text, slug)
reply += "\n\nThis graphic appears in %s %s I am tracking:" % (
inflector.number_to_words(len(stories)),
inflector.plural("story", len(stories)),
)
for story in stories:
reply += "\n" + "*<%s|%s>*" % (story.url, story.name.strip())
# Get linger rate data for charting.
all_graphics_rows = self.get_linger_data(team=team)
all_graphics_median = NPRLingerRate.get_median(all_graphics_rows)
attachments = [
{
"fallback": slug + " update",
"color": "#eeeeee",
"title": slug,
"image_url": self.get_histogram_url(linger_rows, median),
},
{
"fallback": slug + " update",
"color": "#eeeeee",
"title": "How all graphics performed",
"image_url": self.get_histogram_url(all_graphics_rows, all_graphics_median),
},
]
return {"text": reply, "attachments": attachments}
def get_update_message(self, story):
"""
Handle periodic checks on the metric.
For each slug in the story, get the analytics we need, and craft
an relevant update message.
"""
story_slugs = story.slug_list()
team = self.config.get_team_for_story(story)
hours_since = TimeTools.hours_since(story.date)
messages = []
if len(story_slugs) > 1:
# Some stories have many slugs.
# We break out the stats into a nice little grid so they're
# easier to read.
message = (
"%s hours in and here's what I know about the graphics on _%s_:"
) % (hours_since, story.name)
fields = []
for slug in story_slugs:
stats = self.get_stats_for_slug(team=team, slug=slug)
if stats:
fields.append({
"title": slug,
"value": stats['time_text'],
"short": True
})
attachments = [{
"fallback": story.name + " update",
"color": "#eeeeee",
"title": story.name,
"title_link": story.url,
"fields": fields
}]
return {'text': message, 'attachments': attachments}
else:
# For stories with only one slug, we have a slightly different
# message:
stats = self.get_stats_for_slug(team=team, slug=story_slugs[0])
if stats:
message = "%s hours in, *%s users* have spent a median *%s* on _%s_ (`%s`)" % (
hours_since, stats['people'], stats['time_text'],
story.name, story_slugs[0])
return {'text': message}
def get_update_message(self, story):
"""
Handle periodic checks on the metric.
For each slug in the story, get the analytics we need, and craft
an relevant update message.
"""
story_slugs = story.slug_list()
team = self.config.get_team_for_story(story)
hours_since = TimeTools.hours_since(story.date)
messages = []
if len(story_slugs) > 1:
# Some stories have many slugs.
# We break out the stats into a nice little grid so they're
# easier to read.
message = ("%s hours in and here's what I know about the graphics on _%s_:") % (hours_since, story.name)
fields = []
for slug in story_slugs:
stats = self.get_stats_for_slug(team=team, slug=slug)
if stats:
fields.append({"title": slug, "value": stats["time_text"], "short": True})
attachments = [
{
"fallback": story.name + " update",
"color": "#eeeeee",
"title": story.name,
"title_link": story.url,
"fields": fields,
}
]
return {"text": message, "attachments": attachments}
else:
# For stories with only one slug, we have a slightly different
# message:
stats = self.get_stats_for_slug(team=team, slug=story_slugs[0])
if stats:
message = "%s hours in, *%s users* have spent a median *%s* on _%s_ (`%s`)" % (
hours_since,
stats["people"],
stats["time_text"],
story.name,
story_slugs[0],
)
return {"text": message}
def get_stats_for_slug(self, team, slug):
"""
Return clean stats about how long people looked at a slug
"""
linger_rows = self.get_linger_data(team=team, slug=slug)
if not linger_rows:
return False
median = NPRLingerRate.get_median(linger_rows)
return {
'median': median,
'people': "{:,}".format(median['total_people']),
'time_text': TimeTools.humanist_time_bucket(median)
}
def test_humanist_time_bucket(self):
bucket = TimeTools.humanist_time_bucket({
'minutes': 5,
'seconds': 5
})
self.assertEqual(bucket, '5 minutes 5 seconds')
bucket = TimeTools.humanist_time_bucket({
'minutes': 0,
'seconds': 1
})
self.assertEqual(bucket, '1 second')
bucket = TimeTools.humanist_time_bucket({
'minutes': 5,
'seconds': 0
})
self.assertEqual(bucket, '5 minutes')
bucket = TimeTools.humanist_time_bucket({
'minutes': 1,
'seconds': 1
})
self.assertEqual(bucket, '1 minute 1 second')
def get_stats_for_slug(self, team, slug):
"""
Return clean stats about how long people looked at a slug
"""
linger_rows = self.get_linger_data(team=team, slug=slug)
if not linger_rows:
return False
median = NPRLingerRate.get_median(linger_rows)
return {
"median": median,
"people": "{:,}".format(median["total_people"]),
"time_text": TimeTools.humanist_time_bucket(median),
}
def handle_linger_update(message):
if 'doing' not in message.body['text']:
return
m = GRUBER_URLINTEXT_PAT.findall(message.body['text'])
if not m[0]:
return
url = str(m[0][0])
url = url.replace('&', '&')
logger.info("Looking for url %s" % url)
try:
story = Story.select().where(Story.url == url).get()
except:
message.reply("Sorry, I don't have stats for %s" % url)
return
story_time_bucket = story.time_bucket()
stats_per_slug = analytics.get_linger_data_for_story(story)
if len(stats_per_slug) is not 0:
reply = ("Here's what I know about the graphics on _%s_:") % (
story.name.strip())
fields = []
for stat in stats_per_slug:
time = TimeTools.humanist_time_bucket(stat['stats'])
fields.append({
"title": stat['slug'],
"value": time,
"short": True
})
attachments = [{
"fallback": story.name + " update",
"color": "#eeeeee",
"title": story.name,
"title_link": story.url,
"fields": fields
}]
# Use send_message instead of message.reply, otherwise we lose
# the bot icon.
slackTools.send_message(message.body['channel'], reply, attachments)
def handle_slug_inquiry(self, message):
"""
Respond to an inquiry about the slug with stats and charts
"""
match = re.search(self.SLUG_SEARCH_REGEX, message.body['text'])
slug = match.group(1)
if slug:
# Try to match the story to a slug to accurately get a team
# The Google Analytics property ID comes from the team config
# We use the default team if none is found
stories = Story.select().where(Story.slug.contains(slug))
team = self.config.get_team_for_stories(stories)
linger_rows = self.get_linger_data(team=team, slug=slug)
if not linger_rows:
return {
'text':
"Sorry, I wasn't able to find linger rate stats for %s" %
slug
}
median = NPRLingerRate.get_median(linger_rows)
print "Got median"
print median
people = "{:,}".format(median['total_people'])
time_text = TimeTools.humanist_time_bucket(median)
reply = u"*%s* people spent a median *%s* on `%s`." % (
people, time_text, slug)
reply += '\n\nThis graphic appears in %s %s I am tracking:' % (
inflector.number_to_words(
len(stories)), inflector.plural('story', len(stories)))
for story in stories:
reply += '\n' + '*<%s|%s>*' % (story.url, story.name.strip())
# Get linger rate data for charting.
all_graphics_rows = self.get_linger_data(team=team)
all_graphics_median = NPRLingerRate.get_median(all_graphics_rows)
attachments = [{
"fallback":
slug + " update",
"color":
"#eeeeee",
"title":
slug,
"image_url":
self.get_histogram_url(linger_rows, median)
}, {
"fallback":
slug + " update",
"color":
"#eeeeee",
"title":
"How all graphics performed",
"image_url":
self.get_histogram_url(all_graphics_rows, all_graphics_median)
}]
return {'text': reply, 'attachments': attachments}
def time_bucket(self):
return TimeTools.time_bucket(self.date)
def handle_slug_question(message):
m = re.search(LINGER_RATE_REGEX, message.body['text'])
if not m:
return
slug = m.group(1)
if slug:
median = analytics.get_linger_rate(slug)
stories = Story.select().where(Story.slug.contains(slug))
message.reply("Ok! I'm looking up %s. This may take a second." % slug)
if median:
people = "{:,}".format(median['total_people'])
time_text = TimeTools.humanist_time_bucket(median)
reply = u"*%s* people spent a median *%s* on `%s`." % (
people, time_text, slug)
# List the stories this slug appears on
reply += '\n\nThis graphic appears in %s %s:' % (
inflector.number_to_words(
len(stories)), inflector.plural('story', len(stories)))
for story in stories:
reply += '\n' + '*<%s|%s>*' % (story.url, story.name.strip())
# Get linger rate data
linger_rows = analytics.get_linger_rows(slug)
linger_histogram_url = ChartTools.linger_histogram_link(
linger_rows, median)
all_graphics_rows = analytics.get_linger_rows()
all_graphics_median = analytics.get_linger_rate()
all_histogram = ChartTools.linger_histogram_link(
all_graphics_rows, all_graphics_median)
attachments = [{
"fallback": slug + " update",
"color": "#eeeeee",
"title": slug,
"image_url": linger_histogram_url
}, {
"fallback": slug + " update",
"color": "#eeeeee",
"title": "How all graphics performed",
"image_url": all_histogram
}]
# Get scroll data, if any.
scroll_depth_rows = analytics.get_depth_rate(slug)
if scroll_depth_rows:
scroll_histogram_url = ChartTools.scroll_histogram_link(
scroll_depth_rows)
if stories[0].screenshot:
scroll_histogram_url = ChartTools.add_screenshot_to_chart(
stories[0].screenshot, scroll_histogram_url)
attachments.append({
"fallback": slug + " update",
"color": "#eeeeee",
"title": "How far down did people scroll?",
"image_url": scroll_histogram_url
})
slackTools.send_message(message.body['channel'],
reply,
attachments,
unfurl_links=False)
else:
message.reply("I wasn't able to figure out the linger rate of %s" %
slug)
def time_bucket(self):
return TimeTools.time_bucket(self.article_posted)
def time_bucket(self):
return TimeTools.time_bucket(self.date)
