def index(self):
"""Home page with the latest test results"""
# Migration (harstorage v1.0)
migration_handler = MongoDB(collection="migration")
if hasattr(c, "message"): return render("/error.html")
status = migration_handler.collection.find_one({"status": "ok"})
if status is None: redirect("/migration/status")
# MongoDB handler
mdb_handler = MongoDB()
if hasattr(c, "message"): return render("/error.html")
# Read aggregated data from database
# Aggregation is based on unique labels, urls and latest timestamps
latest_results = mdb_handler.collection.group(
key=["label", "url"],
condition=None,
initial={"timestamp": "1970-01-01 01:00:00"},
reduce="\
function(doc, prev) { \
if (doc.timestamp > prev.timestamp) { \
prev.timestamp = doc.timestamp; \
} \
}")
key = lambda timestamp: timestamp["timestamp"]
latest_results = sorted(latest_results, key=key, reverse=True)
# Numner of records
c.rowcount = len(latest_results)
# Populate data table with the latest test results
c.metrics_table = [[], [], [], [], [], []]
fields = [
"timestamp", "label", "url", "total_size", "requests",
"full_load_time"
]
for group in latest_results:
condition = {
"label": group["label"],
"timestamp": group["timestamp"]
}
result = mdb_handler.collection.find_one(condition, fields=fields)
c.metrics_table[0].append(result["timestamp"])
c.metrics_table[1].append(result["label"])
c.metrics_table[2].append(result["url"])
c.metrics_table[3].append(result["total_size"])
c.metrics_table[4].append(result["requests"])
c.metrics_table[5].append(
round(result["full_load_time"] / 1000.0, 1))
return render("/home/core.html")
def index(self):
"""Home page with the latest test results"""
# Migration (harstorage v1.0)
migration_handler = MongoDB(collection="migration")
if hasattr(c, "message"):
return render("/error.html")
status = migration_handler.collection.find_one({"status": "ok"})
if status is None:
redirect("/migration/status")
# MongoDB handler
mdb_handler = MongoDB()
if hasattr(c, "message"):
return render("/error.html")
# Read aggregated data from database
# Aggregation is based on unique labels, urls and latest timestamps
latest_results = mdb_handler.collection.group(
key=["label", "url"],
condition=None,
initial={"timestamp": "1970-01-01 01:00:00"},
reduce="\
function(doc, prev) { \
if (doc.timestamp > prev.timestamp) { \
prev.timestamp = doc.timestamp; \
} \
}")
key = lambda timestamp: timestamp["timestamp"]
latest_results = sorted(latest_results, key=key, reverse=True)
# Numner of records
c.rowcount = len(latest_results)
# Populate data table with the latest test results
c.metrics_table = [[], [], [], [], [], []]
fields = ["timestamp", "label", "url", "total_size", "requests",
"full_load_time"]
for group in latest_results:
condition = {
"label": group["label"],
"timestamp": group["timestamp"]
}
result = mdb_handler.collection.find_one(condition, fields=fields)
c.metrics_table[0].append(result["timestamp"])
c.metrics_table[1].append(result["label"])
c.metrics_table[2].append(result["url"])
c.metrics_table[3].append(result["total_size"])
c.metrics_table[4].append(result["requests"])
c.metrics_table[5].append(round(result["full_load_time"] / 1000.0, 1))
return render("/home/core.html")
def create(self):
"""Render form with list of labels and timestamps"""
# MongoDB handler
md_handler = MongoDB()
if hasattr(c, "message"): return render("/error.html")
# List of labels
c.labels = list()
for label in md_handler.collection.distinct("label"):
c.labels.append(label)
return render("/create/core.html")
def create(self):
"""Render form with list of labels and timestamps"""
# MongoDB handler
md_handler = MongoDB()
if hasattr(c, "message"): return render("/error.html")
# List of labels
c.labels = list()
for label in md_handler.collection.distinct("label"):
c.labels.append(label)
return render("/create/core.html")
def dashboard(self):
"""Page with test results"""
enabled = html.literal(config["app_conf"]["dashboard_enabled"])
if enabled != 'true':
c.message = str();
c.message += "Dashboard not enabled!"
return render("/error.html")
filename = os.path.join(config["app_conf"]["dashboard_config_dir"], config["app_conf"]["dashboard_config_filename"])
with open(filename) as json_file:
configData = json.load(json_file)
c.configData = html.literal(configData)
return render("/dashboard/core.html")
def document(self):
"""Render the error document"""
resp = request.environ.get("pylons.original_response")
c.message = literal(resp.status)
return render("/error.html")
def harviewer(self):
"""HAR Viewer iframe"""
# HAR Viewer customization via cookie
response.set_cookie("phaseInterval", "-1", max_age=365 * 24 * 3600)
return render("/harviewer.html")
def harviewer(self):
"""HAR Viewer iframe"""
# HAR Viewer customization via cookie
response.set_cookie("phaseInterval", "-1", max_age=365*24*3600 )
return render("/harviewer.html")
def details(self):
"""Page with test results"""
# Try to fetch data for selecetor box
try:
c.label = request.GET["url"]
c.mode = "url"
# Use label parameter instead of URL parameter
except:
c.label = request.GET["label"]
c.mode = "label"
# Generate context for selector
self._set_options_in_selector(c.mode, c.label)
# Define url for data aggregation
if c.mode == "label":
c.query = "/superposed/display?" + \
"step_1_label=" + c.label + \
"&step_1_start_ts=" + min(c.timestamp) + \
"&step_1_end_ts=" + max(c.timestamp)
c.histo = "true"
else:
c.histo = "false"
c.query = "None"
return render("/details/core.html")
def details(self):
"""Page with test results"""
# Try to fetch data for selecetor box
try:
c.label = request.GET["url"]
c.mode = "url"
# Use label parameter instead of URL parameter
except:
c.label = request.GET["label"]
c.mode = "label"
# Generate context for selector
self._set_options_in_selector(c.mode, c.label)
# Define url for data aggregation
if c.mode == "label":
c.query = "/superposed/display?" + \
"step_1_label=" + c.label + \
"&step_1_start_ts=" + min(c.timestamp) + \
"&step_1_end_ts=" + max(c.timestamp)
c.histo = "true"
else:
c.histo = "false"
c.query = "None"
return render("/details/core.html")
def dashboardLocation(self):
"""Page with test results"""
filename = os.path.join(config["app_conf"]["dashboard_config_dir"], config["app_conf"]["dashboard_config_filename"])
with open(filename) as json_file:
configData = json.load(json_file)
c.configData = html.literal(configData)
return render("/dashboard/location/core.html")
def migration(self):
# MongoDB handler
mdb_handler = MongoDB()
if hasattr(c, "message"): return render("/error.html")
for document in mdb_handler.collection.find(fields=["_id", "har"]):
id = document["_id"]
har = HAR(document["har"], True)
har.analyze()
domains_req_ratio = dict()
domains_weight_ratio = dict()
for key, value in har.domains.items():
domains_req_ratio[key] = value[0]
domains_weight_ratio[key] = value[1]
data = {
"full_load_time": har.full_load_time,
"onload_event": har.onload_event,
"start_render_time": har.start_render_time,
"time_to_first_byte": har.time_to_first_byte,
"total_dns_time": har.total_dns_time,
"total_transfer_time": har.total_transfer_time,
"total_server_time": har.total_server_time,
"avg_connecting_time": har.avg_connecting_time,
"avg_blocking_time": har.avg_blocking_time,
"total_size": har.total_size,
"text_size": har.text_size,
"media_size": har.media_size,
"cache_size": har.cache_size,
"requests": har.requests,
"redirects": har.redirects,
"bad_requests": har.bad_requests,
"domains": len(har.domains),
"weights_ratio": har.weight_ratio(),
"requests_ratio": har.req_ratio(),
"domains_ratio": har.domains
}
mdb_handler.collection.update({"_id": id}, {"$set": data})
migration_handler = MongoDB(collection="migration")
migration_handler.collection.insert({"status": "ok"})
redirect("/")
def wrapper(*args):
result, ext = function(*args)
if result == True:
try:
if request.headers["automated"] == "true":
return "Successful"
except KeyError:
redirect("/results/details?label=" + ext)
else:
try:
if request.headers["automated"] == "true":
return ext
except KeyError:
c.error = ext
return render("/upload.html")
def wrapper(*args):
result, ext = function(*args)
if result:
try:
if request.headers["automated"] == "true":
return "Successful"
except KeyError:
redirect("/results/details?label=" + ext)
else:
try:
if request.headers["automated"] == "true":
return ext
except KeyError:
c.error = ext
return render("/upload.html")
def migration(self):
# MongoDB handler
mdb_handler = MongoDB()
if hasattr(c, "message"):
return render("/error.html")
for document in mdb_handler.collection.find(fields=["_id", "har"]):
id = document["_id"]
har = HAR(document["har"], True)
har.analyze()
domains_req_ratio = dict()
domains_weight_ratio = dict()
for key, value in har.domains.items():
domains_req_ratio[key] = value[0]
domains_weight_ratio[key] = value[1]
data = {"full_load_time": har.full_load_time,
"onload_event": har.onload_event,
"start_render_time": har.start_render_time,
"time_to_first_byte": har.time_to_first_byte,
"total_dns_time": har.total_dns_time,
"total_transfer_time": har.total_transfer_time,
"total_server_time": har.total_server_time,
"avg_connecting_time": har.avg_connecting_time,
"avg_blocking_time": har.avg_blocking_time,
"total_size": har.total_size,
"text_size": har.text_size,
"media_size": har.media_size,
"cache_size": har.cache_size,
"requests": har.requests,
"redirects": har.redirects,
"bad_requests": har.bad_requests,
"domains": len(har.domains),
"weights_ratio": har.weight_ratio(),
"requests_ratio": har.req_ratio(),
"domains_ratio": har.domains}
mdb_handler.collection.update({"_id": id}, {"$set": data})
migration_handler = MongoDB(collection="migration")
migration_handler.collection.insert({"status": "ok"})
redirect(h.url_for('/'))
def details(self):
"""Page with test results"""
# Try to fetch data for selecetor box
try:
c.label = request.GET["url"]
c.mode = "url"
# Use label parameter instead of URL parameter
except:
c.label = request.GET["label"]
c.mode = "label"
# Try to fetch time filter
try:
timeFilter = request.GET["timeFilter"]
except:
timeFilter = "30"
if timeFilter == "7":
c.startTs = strftime("%Y-%m-%d %H:%M:%S", gmtime(time.time()-168*60*60))
elif timeFilter == "30":
c.startTs = strftime("%Y-%m-%d %H:%M:%S", gmtime(time.time()-720*60*60))
elif timeFilter == "60":
c.startTs = strftime("%Y-%m-%d %H:%M:%S", gmtime(time.time()-1440*60*60))
else:
c.startTs = "1970-01-01 01:00:00"
# Generate context for selector
self._set_options_in_selector(c.mode, c.label, c.startTs)
# Define url for data aggregation
if c.mode == "label":
c.query = "/superposed/display?" + \
"step_1_label=" + c.label + \
"&step_1_label_hidden=" + c.label + \
"&step_1_start_ts=" + c.startTs + \
"&step_1_end_ts=" + max(c.timestamp)
c.histo = "true"
else:
c.histo = "false"
c.query = "None"
return render("/details/core.html")
def index(self):
"""Home page with the latest test results"""
# Migration (harstorage v1.0)
migration_handler = MongoDB(collection="migration")
if hasattr(c, "message"):
return render("/error.html")
status = migration_handler.collection.find_one({"status": "ok"})
if status is None:
redirect("/migration/status")
# MongoDB handler
mdb_handler = MongoDB()
if hasattr(c, "message"):
return render("/error.html")
# Read aggregated data from database
# Aggregation is based on unique labels, urls and latest timestamps
'''
Replaced the original grouping with an aggregate function. This function
actually returns all of the fields needed such that we also do not needed
to make any subsequent requests back to MongoDB to retrieve details on
the list
'''
latest_results = mdb_handler.collection.aggregate([{
"$group": {
"_id": {
"label": "$label",
"url": "$url"
},
"timestamp": {
"$last": "$timestamp"
},
"total_size": {
"$last": "$total_size"
},
"requests": {
"$last": "$requests"
},
"full_load_time": {
"$last": "$full_load_time"
}
}
}, {
"$sort": {
"timestamp": -1
}
}])
'''
Get the number of records
Since we changed the initial request, we need to deal with the json array
differently as well.
'''
c.rowcount = len(latest_results["result"])
# Populate data table with the latest test results
c.metrics_table = [[], [], [], [], [], []]
'''
for group in latest_results["result"]:
condition = {"label": group["_id"]["label"], "timestamp": group["timestamp"]}
result = mdb_handler.collection.find_one(condition, fields=fields)
c.metrics_table[0].append(result["timestamp"])
c.metrics_table[1].append(result["label"])
c.metrics_table[2].append(result["url"])
c.metrics_table[3].append(result["total_size"])
c.metrics_table[4].append(result["requests"])
c.metrics_table[5].append(round(result["full_load_time"] / 1000.0, 1))
'''
# loop through our results and return them
for result in latest_results["result"]:
c.metrics_table[0].append(result["timestamp"])
c.metrics_table[1].append(result["_id"]["label"])
c.metrics_table[2].append(result["_id"]["url"])
c.metrics_table[3].append(result["total_size"])
c.metrics_table[4].append(result["requests"])
c.metrics_table[5].append(
round(result["full_load_time"] / 1000.0, 1))
return render("/home/core.html")
def display(self):
"""Render page with column chart and data table"""
# MongoDB handler
md_handler = MongoDB()
if hasattr(c, "message"): return render("/error.html")
# Checkbox options
c.chart_type = request.GET.get("chart", None)
c.table = request.GET.get("table", "false")
init = request.GET.get("metric", "true")
c.chart = "true" if c.chart_type else "false"
# Metric option
c.metric = request.GET.get("metric", "Average")
# Number of records
if c.chart == "true" and c.table == "true" and init != "true":
c.rowcount = len(request.GET) / 3 - 1
else:
c.rowcount = len(request.GET) / 3
# Data containers
METRICS = ( "full_load_time", "requests", "total_size",
"ps_scores", "onload_event", "start_render_time",
"time_to_first_byte", "total_dns_time",
"total_transfer_time", "total_server_time",
"avg_connecting_time", "avg_blocking_time", "text_size",
"media_size", "cache_size", "redirects", "bad_requests",
"domains", "api_time")
c.headers = [ "Label", "Full Load Time (ms)", "Total Requests",
"Total Size (kB)", "Page Speed Score",
"onLoad Event (ms)", "Start Render Time (ms)",
"Time to First Byte (ms)", "Total DNS Time (ms)",
"Total Transfer Time (ms)", "Total Server Time (ms)",
"Avg. Connecting Time (ms)", "Avg. Blocking Time (ms)",
"Text Size (kB)", "Media Size (kB)", "Cache Size (kB)",
"Redirects", "Bad Rquests", "Domains", "API Time (ms)"]
TITLES = [ "Full Load Time", "Total Requests",
"Total Size", "Page Speed Score", "onLoad Event",
"Start Render Time", "Time to First Byte",
"Total DNS Time", "Total Transfer Time", "Total Server Time",
"Avg. Connecting Time", "Avg. Blocking Time", "Text Size",
"Media Size", "Cache Size", "Redirects", "Bad Rquests",
"Domains", "API Time"]
# Set of metrics to exclude (due to missing data)
exclude = set()
data = dict()
for metric in METRICS:
data[metric] = list()
data["label"] = list()
# Data table
c.metrics_table = list()
c.metrics_table.append(list())
# Test results from database
for row in range(c.rowcount):
# Parameters from GET request
label = request.GET["step_" + str(row+1) + "_label"]
start_ts = request.GET["step_" + str(row+1) + "_start_ts"]
end_ts = request.GET["step_" + str(row+1) + "_end_ts"]
# Label
c.metrics_table[0].append(label)
data["label"].append(row)
data["label"][row] = label
# Fetch test results
condition = {"label": label,
"timestamp": {"$gte": start_ts, "$lte": end_ts}}
documents = md_handler.collection.find(condition, fields = METRICS)
for metric in METRICS:
data[metric].append(row)
data[metric][row] = list()
for document in documents:
for metric in METRICS:
if metric != "ps_scores":
data[metric][row].append(document[metric])
else:
data[metric][row].append(document[metric]["Total Score"])
# Aggregation
c.points = str()
for row in range(c.rowcount):
c.points += data["label"][row] + "#"
column = 1
agg_handler = Aggregator()
for metric in METRICS:
c.metrics_table.append(list())
c.points = c.points[:-1] + ";"
for row in range(c.rowcount):
if c.metric == "Average":
value = agg_handler.average(data[metric][row])
elif c.metric == "Minimum":
value = agg_handler.minimum(data[metric][row])
elif c.metric == "Maximum":
value = agg_handler.maximum(data[metric][row])
elif c.metric == "90th Percentile":
value = agg_handler.percentile(data[metric][row], 0.9)
elif c.metric == "Median":
value = agg_handler.percentile(data[metric][row], 0.5)
if value == "n/a":
exclude.add(metric)
else:
c.points += str(value) + "#"
c.metrics_table[column].append(value)
column += 1
# Update list of titles
if "onload_event" in exclude:
TITLES.pop(TITLES.index("onLoad Event"))
if "start_render_time" in exclude:
TITLES.pop(TITLES.index("Start Render Time"))
header = str()
for title in TITLES:
header += title + "#"
c.points = header[:-1] + ";" + c.points[:-1]
return render("/display/core.html")
def status(self):
return render("/migration.html")
def histogram(self):
"""Render chart with histograms"""
# MongoDB handler
md_handler = MongoDB()
if hasattr(c, "message"):
return render("/error.html")
# Options
c.label = request.GET["label"]
c.metric = request.GET["metric"]
# Metrics
METRICS = [("full_load_time", "Full Load Time"),
("onload_event", "onLoad Event"),
("start_render_time", "Start Render Time"),
("time_to_first_byte", "Time to First Byte"),
("total_dns_time", "Total DNS Time"),
("total_transfer_time", "Total Transfer Time"),
("total_server_time", "Total Server Time"),
("avg_connecting_time", "Avg. Connecting Time"),
("avg_blocking_time", "Avg. Blocking Time")]
time_metrics = ["full_load_time", "onload_event", "start_render_time",
"time_to_first_byte"]
c.metrics = list()
# Read data from database
condition = {"label": c.label}
fields = (metric for metric, title in METRICS)
documents = md_handler.collection.find(condition, fields=fields)
full_data = list(document for document in documents)
for metric, title in METRICS:
try:
data = (result[metric] for result in full_data)
histogram = Histogram(data)
if metric in time_metrics:
ranges = histogram.ranges(True)
else:
ranges = histogram.ranges()
frequencies = histogram.frequencies()
if metric == c.metric:
c.data = ""
for occ_range in ranges:
c.data += occ_range + "#"
c.data = c.data[:-1] + ";"
for frequency in frequencies:
c.data += str(frequency) + "#"
c.data = c.data[:-1] + ";"
c.title = title
c.metrics.append((metric, title))
except IndexError:
pass
except TypeError:
pass
except ValueError:
pass
if len(c.metrics):
return render("/histogram/core.html")
else:
c.message = "Sorry! You haven't enough data."
return render("/error.html")
def index(self):
"""Home page with the latest test results"""
# Migration (harstorage v1.0)
migration_handler = MongoDB(collection="migration")
if hasattr(c, "message"):
return render("/error.html")
status = migration_handler.collection.find_one({"status": "ok"})
if status is None:
redirect("/migration/status")
# MongoDB handler
mdb_handler = MongoDB()
if hasattr(c, "message"):
return render("/error.html")
# Read aggregated data from database
# Aggregation is based on unique labels, urls and latest timestamps
'''
Replaced the original grouping with an aggregate function. This function
actually returns all of the fields needed such that we also do not needed
to make any subsequent requests back to MongoDB to retrieve details on
the list
'''
latest_results = mdb_handler.collection.aggregate(
[{"$group":{"_id": {"label":"$label", "url":"$url"},
"timestamp":{"$last":"$timestamp"},
"total_size":{"$last":"$total_size"},
"requests":{"$last":"$requests"},
"full_load_time": {"$last":"$full_load_time"}}},
{"$sort":{"timestamp" : -1}}])
'''
Get the number of records
Since we changed the initial request, we need to deal with the json array
differently as well.
'''
c.rowcount = len(latest_results["result"])
# Populate data table with the latest test results
c.metrics_table = [[], [], [], [], [], []]
'''
for group in latest_results["result"]:
condition = {"label": group["_id"]["label"], "timestamp": group["timestamp"]}
result = mdb_handler.collection.find_one(condition, fields=fields)
c.metrics_table[0].append(result["timestamp"])
c.metrics_table[1].append(result["label"])
c.metrics_table[2].append(result["url"])
c.metrics_table[3].append(result["total_size"])
c.metrics_table[4].append(result["requests"])
c.metrics_table[5].append(round(result["full_load_time"] / 1000.0, 1))
'''
# loop through our results and return them
for result in latest_results["result"]:
c.metrics_table[0].append(result["timestamp"])
c.metrics_table[1].append(result["_id"]["label"])
c.metrics_table[2].append(result["_id"]["url"])
c.metrics_table[3].append(result["total_size"])
c.metrics_table[4].append(result["requests"])
c.metrics_table[5].append(round(result["full_load_time"] / 1000.0, 1))
return render("/home/core.html")
def display(self):
"""Render page with column chart and data table"""
# MongoDB handler
md_handler = MongoDB()
if hasattr(c, "message"):
return render("/error.html")
# Checkbox options
c.chart_type = request.GET.get("chart", None)
c.table = request.GET.get("table", "false")
init = request.GET.get("metric", "true")
c.chart = "true" if c.chart_type else "false"
# Aggregation option
c.agg_type = request.GET.get("metric", "Average")
# Number of records
if c.chart == "true" and c.table == "true" and init != "true":
c.rowcount = len(request.GET) / 3 - 1
else:
c.rowcount = len(request.GET) / 3
# Data table
c.headers = ["Label", "Full Load Time (ms)", "Total Requests",
"Total Size (kB)", "Page Speed Score",
"onLoad Event (ms)", "Start Render Time (ms)",
"Time to First Byte (ms)", "Total DNS Time (ms)",
"Total Transfer Time (ms)", "Total Server Time (ms)",
"Avg. Connecting Time (ms)", "Avg. Blocking Time (ms)",
"Text Size (kB)", "Media Size (kB)", "Cache Size (kB)",
"Redirects", "Bad Rquests", "Domains"]
c.metrics_table = list()
c.metrics_table.append(list())
# Chart points
c.points = str()
# Aggregator
aggregator = Aggregator()
# Test results from database
for row_index in range(c.rowcount):
# Parameters from GET request
label = request.GET["step_" + str(row_index + 1) + "_label"]
start_ts = request.GET["step_" + str(row_index + 1) + "_start_ts"]
end_ts = request.GET["step_" + str(row_index + 1) + "_end_ts"]
# Add label
c.metrics_table[0].append(label)
c.points += label + "#"
# Fetch test results
condition = {
"label": label,
"timestamp": {"$gte": start_ts, "$lte": end_ts}
}
documents = md_handler.collection.find(condition,
fields=aggregator.METRICS)
# Add data row to aggregator
aggregator.add_row(label, row_index, documents)
# Aggregated data per column
column = 1
for metric in aggregator.METRICS:
c.metrics_table.append(list())
c.points = c.points[:-1] + ";"
for row_index in range(c.rowcount):
data_list = aggregator.data[metric][row_index]
value = aggregator.get_aggregated_value(data_list, c.agg_type,
metric)
c.points += str(value) + "#"
c.metrics_table[column].append(value)
column += 1
# Names of series
titles = str()
for title in aggregator.TITLES:
titles += title + "#"
# Final chart points
c.points = titles[:-1] + ";" + c.points[:-1]
c.points = aggregator.exclude_missing(c.points)
return render("/display/core.html")
def dailyReport(self):
"""Page with test results"""
return render("/dailyReport.html")
