mirror/0bin
1
0
Fork 0
mirror of https://github.com/Tygs/0bin.git synced 2023-08-10 21:13:00 +03:00
Code Issues Projects Releases Wiki Activity

Porting zerobin to python 3

Browse Source
This commit is contained in:
sametmax
2015-05-10 19:19:02 +02:00
parent 391df055f9
commit 9b84122414
137 changed files with 22928 additions and 4370 deletions
Download Patch File Download Diff File Expand all files Collapse all files

249
libs/cherrypy/lib/cpstats.py
View File

@@ -21,33 +21,37 @@ to collect stats to import a third-party module. Therefore, we choose to
re-use the `logging` module by adding a `statistics` object to it.
That `logging.statistics` object is a nested dict. It is not a custom class,
because that would 1) require libraries and applications to import a third-
party module in order to participate, 2) inhibit innovation in extrapolation
approaches and in reporting tools, and 3) be slow. There are, however, some
specifications regarding the structure of the dict.
because that would:
{
+----"SQLAlchemy": {
| "Inserts": 4389745,
| "Inserts per Second":
| lambda s: s["Inserts"] / (time() - s["Start"]),
| C +---"Table Statistics": {
| o | "widgets": {-----------+
N | l | "Rows": 1.3M, | Record
a | l | "Inserts": 400, |
m | e | },---------------------+
e | c | "froobles": {
s | t | "Rows": 7845,
p | i | "Inserts": 0,
a | o | },
c | n +---},
e | "Slow Queries":
| [{"Query": "SELECT * FROM widgets;",
| "Processing Time": 47.840923343,
| },
| ],
+----},
}
1. require libraries and applications to import a third-party module in
order to participate
2. inhibit innovation in extrapolation approaches and in reporting tools, and
3. be slow.
There are, however, some specifications regarding the structure of the dict.::
{
+----"SQLAlchemy": {
| "Inserts": 4389745,
| "Inserts per Second":
| lambda s: s["Inserts"] / (time() - s["Start"]),
| C +---"Table Statistics": {
| o | "widgets": {-----------+
N | l | "Rows": 1.3M, | Record
a | l | "Inserts": 400, |
m | e | },---------------------+
e | c | "froobles": {
s | t | "Rows": 7845,
p | i | "Inserts": 0,
a | o | },
c | n +---},
e | "Slow Queries":
| [{"Query": "SELECT * FROM widgets;",
| "Processing Time": 47.840923343,
| },
| ],
+----},
}
The `logging.statistics` dict has four levels. The topmost level is nothing
more than a set of names to introduce modularity, usually along the lines of
@@ -65,13 +69,13 @@ Each namespace, then, is a dict of named statistical values, such as
good on a report: spaces and capitalization are just fine.
In addition to scalars, values in a namespace MAY be a (third-layer)
dict, or a list, called a "collection". For example, the CherryPy StatsTool
keeps track of what each request is doing (or has most recently done)
in a 'Requests' collection, where each key is a thread ID; each
dict, or a list, called a "collection". For example, the CherryPy
:class:`StatsTool` keeps track of what each request is doing (or has most
recently done) in a 'Requests' collection, where each key is a thread ID; each
value in the subdict MUST be a fourth dict (whew!) of statistical data about
each thread. We call each subdict in the collection a "record". Similarly,
the StatsTool also keeps a list of slow queries, where each record contains
data about each slow query, in order.
the :class:`StatsTool` also keeps a list of slow queries, where each record
contains data about each slow query, in order.
Values in a namespace or record may also be functions, which brings us to:
@@ -86,17 +90,17 @@ scalar values you already have on hand.
When it comes time to report on the gathered data, however, we usually have
much more freedom in what we can calculate. Therefore, whenever reporting
tools (like the provided StatsPage CherryPy class) fetch the contents of
`logging.statistics` for reporting, they first call `extrapolate_statistics`
(passing the whole `statistics` dict as the only argument). This makes a
deep copy of the statistics dict so that the reporting tool can both iterate
over it and even change it without harming the original. But it also expands
any functions in the dict by calling them. For example, you might have a
'Current Time' entry in the namespace with the value "lambda scope: time.time()".
The "scope" parameter is the current namespace dict (or record, if we're
currently expanding one of those instead), allowing you access to existing
static entries. If you're truly evil, you can even modify more than one entry
at a time.
tools (like the provided :class:`StatsPage` CherryPy class) fetch the contents
of `logging.statistics` for reporting, they first call
`extrapolate_statistics` (passing the whole `statistics` dict as the only
argument). This makes a deep copy of the statistics dict so that the
reporting tool can both iterate over it and even change it without harming
the original. But it also expands any functions in the dict by calling them.
For example, you might have a 'Current Time' entry in the namespace with the
value "lambda scope: time.time()". The "scope" parameter is the current
namespace dict (or record, if we're currently expanding one of those
instead), allowing you access to existing static entries. If you're truly
evil, you can even modify more than one entry at a time.
However, don't try to calculate an entry and then use its value in further
extrapolations; the order in which the functions are called is not guaranteed.
@@ -108,19 +112,20 @@ After the whole thing has been extrapolated, it's time for:
Reporting
---------
The StatsPage class grabs the `logging.statistics` dict, extrapolates it all,
and then transforms it to HTML for easy viewing. Each namespace gets its own
header and attribute table, plus an extra table for each collection. This is
NOT part of the statistics specification; other tools can format how they like.
The :class:`StatsPage` class grabs the `logging.statistics` dict, extrapolates
it all, and then transforms it to HTML for easy viewing. Each namespace gets
its own header and attribute table, plus an extra table for each collection.
This is NOT part of the statistics specification; other tools can format how
they like.
You can control which columns are output and how they are formatted by updating
StatsPage.formatting, which is a dict that mirrors the keys and nesting of
`logging.statistics`. The difference is that, instead of data values, it has
formatting values. Use None for a given key to indicate to the StatsPage that a
given column should not be output. Use a string with formatting (such as '%.3f')
to interpolate the value(s), or use a callable (such as lambda v: v.isoformat())
for more advanced formatting. Any entry which is not mentioned in the formatting
dict is output unchanged.
given column should not be output. Use a string with formatting
(such as '%.3f') to interpolate the value(s), or use a callable (such as
lambda v: v.isoformat()) for more advanced formatting. Any entry which is not
mentioned in the formatting dict is output unchanged.
Monitoring
----------
@@ -145,12 +150,12 @@ entries to False or True, if present.
Usage
=====
To collect statistics on CherryPy applications:
To collect statistics on CherryPy applications::
from cherrypy.lib import cpstats
appconfig['/']['tools.cpstats.on'] = True
To collect statistics on your own code:
To collect statistics on your own code::
import logging
# Initialize the repository
@@ -172,20 +177,22 @@ To collect statistics on your own code:
if mystats.get('Enabled', False):
mystats['Important Events'] += 1
To report statistics:
To report statistics::
root.cpstats = cpstats.StatsPage()
To format statistics reports:
To format statistics reports::
See 'Reporting', above.
"""
# -------------------------------- Statistics -------------------------------- #
# ------------------------------- Statistics -------------------------------- #
import logging
if not hasattr(logging, 'statistics'): logging.statistics = {}
if not hasattr(logging, 'statistics'):
logging.statistics = {}
def extrapolate_statistics(scope):
"""Return an extrapolated copy of the given scope."""
@@ -201,7 +208,7 @@ def extrapolate_statistics(scope):
return c
# --------------------- CherryPy Applications Statistics --------------------- #
# -------------------- CherryPy Applications Statistics --------------------- #
import threading
import time
@@ -211,12 +218,20 @@ import cherrypy
appstats = logging.statistics.setdefault('CherryPy Applications', {})
appstats.update({
'Enabled': True,
'Bytes Read/Request': lambda s: (s['Total Requests'] and
(s['Total Bytes Read'] / float(s['Total Requests'])) or 0.0),
'Bytes Read/Request': lambda s: (
s['Total Requests'] and
(s['Total Bytes Read'] / float(s['Total Requests'])) or
0.0
),
'Bytes Read/Second': lambda s: s['Total Bytes Read'] / s['Uptime'](s),
'Bytes Written/Request': lambda s: (s['Total Requests'] and
(s['Total Bytes Written'] / float(s['Total Requests'])) or 0.0),
'Bytes Written/Second': lambda s: s['Total Bytes Written'] / s['Uptime'](s),
'Bytes Written/Request': lambda s: (
s['Total Requests'] and
(s['Total Bytes Written'] / float(s['Total Requests'])) or
0.0
),
'Bytes Written/Second': lambda s: (
s['Total Bytes Written'] / s['Uptime'](s)
),
'Current Time': lambda s: time.time(),
'Current Requests': 0,
'Requests/Second': lambda s: float(s['Total Requests']) / s['Uptime'](s),
@@ -228,28 +243,29 @@ appstats.update({
'Total Time': 0,
'Uptime': lambda s: time.time() - s['Start Time'],
'Requests': {},
})
})
proc_time = lambda s: time.time() - s['Start Time']
class ByteCountWrapper(object):
"""Wraps a file-like object, counting the number of bytes read."""
def __init__(self, rfile):
self.rfile = rfile
self.bytes_read = 0
def read(self, size=-1):
data = self.rfile.read(size)
self.bytes_read += len(data)
return data
def readline(self, size=-1):
data = self.rfile.readline(size)
self.bytes_read += len(data)
return data
def readlines(self, sizehint=0):
# Shamelessly stolen from StringIO
total = 0
@@ -262,13 +278,13 @@ class ByteCountWrapper(object):
break
line = self.readline()
return lines
def close(self):
self.rfile.close()
def __iter__(self):
return self
def next(self):
data = self.rfile.next()
self.bytes_read += len(data)
@@ -279,30 +295,31 @@ average_uriset_time = lambda s: s['Count'] and (s['Sum'] / s['Count']) or 0
class StatsTool(cherrypy.Tool):
"""Record various information about the current request."""
def __init__(self):
cherrypy.Tool.__init__(self, 'on_end_request', self.record_stop)
def _setup(self):
"""Hook this tool into cherrypy.request.
The standard CherryPy request object will automatically call this
method when the tool is "turned on" in config.
"""
if appstats.get('Enabled', False):
cherrypy.Tool._setup(self)
self.record_start()
def record_start(self):
"""Record the beginning of a request."""
request = cherrypy.serving.request
if not hasattr(request.rfile, 'bytes_read'):
request.rfile = ByteCountWrapper(request.rfile)
request.body.fp = request.rfile
r = request.remote
appstats['Current Requests'] += 1
appstats['Total Requests'] += 1
appstats['Requests'][threading._get_ident()] = {
@@ -315,37 +332,39 @@ class StatsTool(cherrypy.Tool):
'Request-Line': request.request_line,
'Response Status': None,
'Start Time': time.time(),
}
}
def record_stop(self, uriset=None, slow_queries=1.0, slow_queries_count=100,
debug=False, **kwargs):
def record_stop(
self, uriset=None, slow_queries=1.0, slow_queries_count=100,
debug=False, **kwargs):
"""Record the end of a request."""
resp = cherrypy.serving.response
w = appstats['Requests'][threading._get_ident()]
r = cherrypy.request.rfile.bytes_read
w['Bytes Read'] = r
appstats['Total Bytes Read'] += r
if resp.stream:
w['Bytes Written'] = 'chunked'
else:
cl = int(resp.headers.get('Content-Length', 0))
w['Bytes Written'] = cl
appstats['Total Bytes Written'] += cl
w['Response Status'] = getattr(resp, 'output_status', None) or resp.status
w['Response Status'] = getattr(
resp, 'output_status', None) or resp.status
w['End Time'] = time.time()
p = w['End Time'] - w['Start Time']
w['Processing Time'] = p
appstats['Total Time'] += p
appstats['Current Requests'] -= 1
if debug:
cherrypy.log('Stats recorded: %s' % repr(w), 'TOOLS.CPSTATS')
if uriset:
rs = appstats.setdefault('URI Set Tracking', {})
r = rs.setdefault(uriset, {
@@ -357,7 +376,7 @@ class StatsTool(cherrypy.Tool):
r['Max'] = p
r['Count'] += 1
r['Sum'] += p
if slow_queries and p > slow_queries:
sq = appstats.setdefault('Slow Queries', [])
sq.append(w.copy())
@@ -388,6 +407,7 @@ missing = object()
locale_date = lambda v: time.strftime('%c', time.gmtime(v))
iso_format = lambda v: time.strftime('%Y-%m-%d %H:%M:%S', time.gmtime(v))
def pause_resume(ns):
def _pause_resume(enabled):
pause_disabled = ''
@@ -410,7 +430,7 @@ def pause_resume(ns):
class StatsPage(object):
formatting = {
'CherryPy Applications': {
'Enabled': pause_resume('CherryPy Applications'),
@@ -427,20 +447,20 @@ class StatsPage(object):
'End Time': None,
'Processing Time': '%.3f',
'Start Time': iso_format,
},
},
'URI Set Tracking': {
'Avg': '%.3f',
'Max': '%.3f',
'Min': '%.3f',
'Sum': '%.3f',
},
},
'Requests': {
'Bytes Read': '%s',
'Bytes Written': '%s',
'End Time': None,
'Processing Time': '%.3f',
'Start Time': None,
},
},
},
'CherryPy WSGIServer': {
'Enabled': pause_resume('CherryPy WSGIServer'),
@@ -448,8 +468,7 @@ class StatsPage(object):
'Start time': iso_format,
},
}
def index(self):
# Transform the raw data into pretty output for HTML
yield """
@@ -500,18 +519,25 @@ table.stats2 th {
""" % title
for i, (key, value) in enumerate(scalars):
colnum = i % 3
if colnum == 0: yield """
if colnum == 0:
yield """
<tr>"""
yield (
"""
<th>%(key)s</th><td id='%(title)s-%(key)s'>%(value)s</td>""" %
vars()
)
if colnum == 2:
yield """
</tr>"""
if colnum == 0:
yield """
<th>%(key)s</th><td id='%(title)s-%(key)s'>%(value)s</td>""" % vars()
if colnum == 2: yield """
</tr>"""
if colnum == 0: yield """
<th></th><td></td>
<th></th><td></td>
</tr>"""
elif colnum == 1: yield """
elif colnum == 1:
yield """
<th></th><td></td>
</tr>"""
yield """
@@ -547,7 +573,7 @@ table.stats2 th {
</html>
"""
index.exposed = True
def get_namespaces(self):
"""Yield (title, scalars, collections) for each namespace."""
s = extrapolate_statistics(logging.statistics)
@@ -574,7 +600,7 @@ table.stats2 th {
v = format % v
scalars.append((k, v))
yield title, scalars, collections
def get_dict_collection(self, v, formatting):
"""Return ([headers], [rows]) for the given collection."""
# E.g., the 'Requests' dict.
@@ -588,7 +614,7 @@ table.stats2 th {
if k3 not in headers:
headers.append(k3)
headers.sort()
subrows = []
for k2, record in sorted(v.items()):
subrow = [k2]
@@ -604,9 +630,9 @@ table.stats2 th {
v3 = format % v3
subrow.append(v3)
subrows.append(subrow)
return headers, subrows
def get_list_collection(self, v, formatting):
"""Return ([headers], [subrows]) for the given collection."""
# E.g., the 'Slow Queries' list.
@@ -620,7 +646,7 @@ table.stats2 th {
if k3 not in headers:
headers.append(k3)
headers.sort()
subrows = []
for record in v:
subrow = []
@@ -636,27 +662,26 @@ table.stats2 th {
v3 = format % v3
subrow.append(v3)
subrows.append(subrow)
return headers, subrows
if json is not None:
def data(self):
s = extrapolate_statistics(logging.statistics)
cherrypy.response.headers['Content-Type'] = 'application/json'
return json.dumps(s, sort_keys=True, indent=4)
data.exposed = True
def pause(self, namespace):
logging.statistics.get(namespace, {})['Enabled'] = False
raise cherrypy.HTTPRedirect('./')
pause.exposed = True
pause.cp_config = {'tools.allow.on': True,
'tools.allow.methods': ['POST']}
def resume(self, namespace):
logging.statistics.get(namespace, {})['Enabled'] = True
raise cherrypy.HTTPRedirect('./')
resume.exposed = True
resume.cp_config = {'tools.allow.on': True,
'tools.allow.methods': ['POST']}