def send_manifest(form_data,
port=0,
servicename=None,
protocolversion=COMPATIBILITY_VERSION,
no_default=False):
'''Replies to the client with matching service for a service.
Args
form_data - the postData passed in from the client request
port - the port of the old client
servicename - the name of the service being used
protocolversion - the version of the AI service RE: handshake
no_default - boolean flag to signify whether or not we should hand
back the default manifest and profiles if one cannot
be matched based on the client criteria.
Returns
None
Raises
None
'''
# figure out the appropriate path for the AI database,
# and get service name if necessary.
# currently service information is stored in a port directory.
# When the cherrypy webserver new service directories should be
# separated via service-name only. Old services will still use
# port numbers as the separation mechanism.
path = None
found_servicename = None
service = None
port = str(port)
if servicename:
service = AIService(servicename)
path = service.database_path
else:
for name in config.get_all_service_names():
if config.get_service_port(name) == port:
found_servicename = name
service = AIService(name)
path = service.database_path
break
# Check to insure that a valid path was found
if not path or not os.path.exists(path):
print 'Content-Type: text/html' # HTML is following
print # blank line, end of headers
if servicename:
print '<pre><b>Error</b>:unable to find<i>', servicename + '</i>.'
else:
print '<pre><b>Error</b>:unable to find<i>', port + '</i>.'
print 'Available services are:<p><ol><i>'
hostname = socket.gethostname()
for name in config.get_all_service_names():
port = config.get_service_port(name)
sys.stdout.write(
'<a href="http://%s:%d/cgi-bin/'
'cgi_get_manifest.py?version=%s&service=%s">%s</a><br>\n' %
(hostname, port, VERSION, name, name))
print '</i></ol>Please select a service from the above list.'
return
if found_servicename:
servicename = found_servicename
# load to the AI database
aisql = AIdb.DB(path)
aisql.verifyDBStructure()
# convert the form data into a criteria dictionary
criteria = dict()
orig_data = form_data
while form_data:
try:
[key_value, form_data] = form_data.split(';', 1)
except (ValueError, NameError, TypeError, KeyError):
key_value = form_data
form_data = ''
try:
[key, value] = key_value.split('=')
criteria[key] = value
except (ValueError, NameError, TypeError, KeyError):
criteria = dict()
# Generate templating dictionary from criteria
template_dict = dict()
for crit in criteria:
template_dict["AI_" + crit.upper()] = \
AIdb.formatValue(crit, criteria[crit], units=False)
# find the appropriate manifest
try:
manifest = AIdb.findManifest(criteria, aisql)
except StandardError as err:
print 'Content-Type: text/html' # HTML is following
print # blank line, end of headers
print '<pre><b>Error</b>:findManifest criteria<br>'
print err, '<br>'
print '<ol>servicename =', servicename
print 'port =', port
print 'path =', path
print 'form_data =', orig_data
print 'criteria =', criteria
print 'servicename found by port =', found_servicename, '</ol>'
print '</pre>'
return
# check if findManifest() returned a number equal to 0
# (means we got no manifests back -- thus we serve the default if desired)
if manifest is None and not no_default:
manifest = service.get_default_manifest()
# if we have a manifest to return, prepare its return
if manifest is not None:
try:
# construct the fully qualified filename
filename = os.path.abspath(
os.path.join(service.manifest_dir, manifest))
# open and read the manifest
with open(filename, 'rb') as mfp:
manifest_str = mfp.read()
# maintain compability with older AI client
if servicename is None or \
float(protocolversion) < float(PROFILES_VERSION):
content_type = mimetypes.types_map.get('.xml', 'text/plain')
print 'Content-Length:', len(
manifest_str) # Length of the file
print 'Content-Type:', content_type # XML is following
print # blank line, end of headers
print manifest_str
logging.info('Manifest sent from %s.' % filename)
return
except OSError as err:
print 'Content-Type: text/html' # HTML is following
print # blank line, end of headers
print '<pre>'
# report the internal error to error_log and requesting client
sys.stderr.write(_('error:manifest (%s) %s\n') % \
(str(manifest), err))
sys.stdout.write(_('error:manifest (%s) %s\n') % \
(str(manifest), err))
print '</pre>'
return
# get AI service image path
service = AIService(servicename)
image_dir = service.image.path
# construct object to contain MIME multipart message
outermime = MIMEMultipart()
client_msg = list() # accumulate message output for AI client
# If we have a manifest, attach it to the return message
if manifest is not None:
# add manifest as attachment
msg = MIMEText(manifest_str, 'xml')
# indicate manifest using special name
msg.add_header('Content-Disposition',
'attachment',
filename=sc.AI_MANIFEST_ATTACHMENT_NAME)
outermime.attach(msg) # add manifest as an attachment
# search for any profiles matching client criteria
# formulate database query to profiles table
q_str = "SELECT DISTINCT name, file FROM " + \
AIdb.PROFILES_TABLE + " WHERE "
nvpairs = list() # accumulate criteria values from post-data
# for all AI client criteria
for crit in AIdb.getCriteria(aisql.getQueue(),
table=AIdb.PROFILES_TABLE,
onlyUsed=False):
if crit not in criteria:
msgtxt = _("Warning: client criteria \"%s\" not provided in "
"request. Setting value to NULL for profile lookup.") \
% crit
client_msg += [msgtxt]
logging.warn(msgtxt)
# fetch only global profiles destined for all clients
if AIdb.isRangeCriteria(aisql.getQueue(), crit,
AIdb.PROFILES_TABLE):
nvpairs += ["MIN" + crit + " IS NULL"]
nvpairs += ["MAX" + crit + " IS NULL"]
else:
nvpairs += [crit + " IS NULL"]
continue
# prepare criteria value to add to query
envval = AIdb.sanitizeSQL(criteria[crit])
if AIdb.isRangeCriteria(aisql.getQueue(), crit, AIdb.PROFILES_TABLE):
# If no default profiles are requested, then we mustn't allow
# this criteria to be NULL. It must match the client's given
# value for this criteria.
if no_default:
if crit == "mac":
nvpairs += ["(HEX(MIN" + crit + ")<=HEX(X'" + envval + \
"'))"]
nvpairs += ["(HEX(MAX" + crit + ")>=HEX(X'" + envval + \
"'))"]
else:
nvpairs += ["(MIN" + crit + "<='" + envval + "')"]
nvpairs += ["(MAX" + crit + ">='" + envval + "')"]
else:
if crit == "mac":
nvpairs += [
"(MIN" + crit + " IS NULL OR "
"HEX(MIN" + crit + ")<=HEX(X'" + envval + "'))"
]
nvpairs += [
"(MAX" + crit + " IS NULL OR HEX(MAX" + crit +
")>=HEX(X'" + envval + "'))"
]
else:
nvpairs += [
"(MIN" + crit + " IS NULL OR MIN" + crit + "<='" +
envval + "')"
]
nvpairs += [
"(MAX" + crit + " IS NULL OR MAX" + crit + ">='" +
envval + "')"
]
else:
# If no default profiles are requested, then we mustn't allow
# this criteria to be NULL. It must match the client's given
# value for this criteria.
#
# Also, since this is a non-range criteria, the value stored
# in the DB may be a whitespace separated list of single
# values. We use a special user-defined function in the
# determine if the given criteria is in that textual list.
if no_default:
nvpairs += ["(is_in_list('" + crit + "', '" + envval + \
"', " + crit + ", 'None') == 1)"]
else:
nvpairs += ["(" + crit + " IS NULL OR is_in_list('" + crit + \
"', '" + envval + "', " + crit + ", 'None') == 1)"]
if len(nvpairs) > 0:
q_str += " AND ".join(nvpairs)
# issue database query
logging.info("Profile query: " + q_str)
query = AIdb.DBrequest(q_str)
aisql.getQueue().put(query)
query.waitAns()
if query.getResponse() is None or len(query.getResponse()) == 0:
msgtxt = _("No profiles found.")
client_msg += [msgtxt]
logging.info(msgtxt)
else:
for row in query.getResponse():
profpath = row['file']
profname = row['name']
if profname is None: # should not happen
profname = 'unnamed'
try:
if profpath is None:
msgtxt = "Database record error - profile path is " \
"empty."
client_msg += [msgtxt]
logging.error(msgtxt)
continue
msgtxt = _('Processing profile %s') % profname
client_msg += [msgtxt]
logging.info(msgtxt)
with open(profpath, 'r') as pfp:
raw_profile = pfp.read()
# do any template variable replacement {{AI_xxx}}
tmpl_profile = sc.perform_templating(
raw_profile, template_dict)
# precautionary validation of profile, logging only
sc.validate_profile_string(tmpl_profile,
image_dir,
dtd_validation=True,
warn_if_dtd_missing=True)
except IOError as err:
msgtxt = _("Error: I/O error: ") + str(err)
client_msg += [msgtxt]
logging.error(msgtxt)
continue
except OSError:
msgtxt = _("Error: OS error on profile ") + profpath
client_msg += [msgtxt]
logging.error(msgtxt)
continue
except KeyError:
msgtxt = _('Error: could not find criteria to substitute '
'in template: ') + profpath
client_msg += [msgtxt]
logging.error(msgtxt)
logging.error('Profile with template substitution error:' +
raw_profile)
continue
except lxml.etree.XMLSyntaxError as err:
# log validation error and proceed
msgtxt = _(
'Warning: syntax error found in profile: ') \
+ profpath
client_msg += [msgtxt]
logging.error(msgtxt)
for error in err.error_log:
msgtxt = _('Error: ') + error.message
client_msg += [msgtxt]
logging.error(msgtxt)
logging.info([
_('Profile failing validation: ') +
lxml.etree.tostring(root)
])
# build MIME message and attach to outer MIME message
msg = MIMEText(tmpl_profile, 'xml')
# indicate in header that this is an attachment
msg.add_header('Content-Disposition',
'attachment',
filename=profname)
# attach this profile to the manifest and any other profiles
outermime.attach(msg)
msgtxt = _('Parsed and loaded profile: ') + profname
client_msg += [msgtxt]
logging.info(msgtxt)
# any profiles and AI manifest have been attached to MIME message
# specially format list of messages for display on AI client console
if client_msg:
outtxt = ''
for msgtxt in client_msg:
msgtxt = _('SC profile locator:') + msgtxt
outtxt += str(msgtxt) + '\n'
# add AI client console messages as single plain text attachment
msg = MIMEText(outtxt, 'plain') # create MIME message
outermime.attach(msg) # attach MIME message to response
print outermime.as_string() # send MIME-formatted message
def delete_manifest_from_db(db, manifest_instance, service_name, data_loc):
"""
Remove manifest from DB
"""
instance = manifest_instance[1]
# check to see that the manifest is found in the database (as entered)
if manifest_instance[0] not in AIdb.getManNames(db.getQueue()):
# since all manifest names have to have .xml appended try adding that
if manifest_instance[0] + '.xml' in AIdb.getManNames(db.getQueue()):
man_name = manifest_instance[0] + '.xml'
else:
raise SystemExit(_("Error:\tManifest %s not found in database!" %
manifest_instance[0]))
else:
man_name = manifest_instance[0]
service = AIService(service_name)
# Do not delete if this manifest is set up as the default.
if man_name == service.get_default_manifest():
raise ValueError(_("Error:\tCannot delete default manifest %s.") %
man_name)
# if we do not have an instance remove the entire manifest
if instance is None:
# remove manifest from database
query = AIdb.DBrequest("DELETE FROM manifests WHERE name = '%s'" %
AIdb.sanitizeSQL(man_name), commit=True)
db.getQueue().put(query)
query.waitAns()
# run getResponse to handle and errors
query.getResponse()
# clean up file on file system
try:
os.remove(os.path.join(service.manifest_dir, man_name))
except OSError:
print >> sys.stderr, _("Warning:\tUnable to find file %s for " +
"removal!") % man_name
# we are removing a specific instance
else:
# check that the instance number is within bounds for that manifest
# (0..numInstances)
if instance > AIdb.numInstances(man_name, db.getQueue()) or \
instance < 0:
raise SystemExit(_("Error:\tManifest %(name)s has %(num)i "
"instances" % {'name': man_name, 'num':
AIdb.numInstances(man_name, db.getQueue())}))
# remove instance from database
query = ("DELETE FROM manifests WHERE name = '%s' AND "
"instance = '%i'") % (AIdb.sanitizeSQL(man_name), instance)
query = AIdb.DBrequest(query, commit=True)
db.getQueue().put(query)
query.waitAns()
# run getResponse to handle and errors
query.getResponse()
# We may need to reshuffle manifests to prevent gaps in instance
# numbering as the DB routines expect instances to be contiguous and
# increasing. We may have removed an instance with instances numbered
# above thus leaving a gap.
# get the number of instances with a larger instance
for num in range(instance, AIdb.numInstances(man_name,
db.getQueue()) + 1):
# now decrement the instance number
query = ("UPDATE manifests SET instance = '%i' WHERE "
"name = '%s' ") % (num - 1, AIdb.sanitizeSQL(man_name))
query += "AND instance = '%i'" % num
query = AIdb.DBrequest(query, commit=True)
db.getQueue().put(query)
query.waitAns()
# run getResponse to handle and errors
query.getResponse()
# remove file if manifest is no longer in database
if man_name not in AIdb.getManNames(db.getQueue()):
try:
os.remove(os.path.join(service.manifest_dir, man_name))
except OSError:
print >> sys.stderr, _("Warning: Unable to find file %s for " +
"removal!") % man_name
def send_manifest(form_data, port=0, servicename=None,
protocolversion=COMPATIBILITY_VERSION, no_default=False):
'''Replies to the client with matching service for a service.
Args
form_data - the postData passed in from the client request
port - the port of the old client
servicename - the name of the service being used
protocolversion - the version of the AI service RE: handshake
no_default - boolean flag to signify whether or not we should hand
back the default manifest and profiles if one cannot
be matched based on the client criteria.
Returns
None
Raises
None
'''
# figure out the appropriate path for the AI database,
# and get service name if necessary.
# currently service information is stored in a port directory.
# When the cherrypy webserver new service directories should be
# separated via service-name only. Old services will still use
# port numbers as the separation mechanism.
path = None
found_servicename = None
service = None
port = str(port)
if servicename:
service = AIService(servicename)
path = service.database_path
else:
for name in config.get_all_service_names():
if config.get_service_port(name) == port:
found_servicename = name
service = AIService(name)
path = service.database_path
break
# Check to insure that a valid path was found
if not path or not os.path.exists(path):
print 'Content-Type: text/html' # HTML is following
print # blank line, end of headers
if servicename:
print '<pre><b>Error</b>:unable to find<i>', servicename + '</i>.'
else:
print '<pre><b>Error</b>:unable to find<i>', port + '</i>.'
print 'Available services are:<p><ol><i>'
hostname = socket.gethostname()
for name in config.get_all_service_names():
port = config.get_service_port(name)
sys.stdout.write('<a href="http://%s:%d/cgi-bin/'
'cgi_get_manifest.py?version=%s&service=%s">%s</a><br>\n' %
(hostname, port, VERSION, name, name))
print '</i></ol>Please select a service from the above list.'
return
if found_servicename:
servicename = found_servicename
# load to the AI database
aisql = AIdb.DB(path)
aisql.verifyDBStructure()
# convert the form data into a criteria dictionary
criteria = dict()
orig_data = form_data
while form_data:
try:
[key_value, form_data] = form_data.split(';', 1)
except (ValueError, NameError, TypeError, KeyError):
key_value = form_data
form_data = ''
try:
[key, value] = key_value.split('=')
criteria[key] = value
except (ValueError, NameError, TypeError, KeyError):
criteria = dict()
# Generate templating dictionary from criteria
template_dict = dict()
for crit in criteria:
template_dict["AI_" + crit.upper()] = \
AIdb.formatValue(crit, criteria[crit], units=False)
# find the appropriate manifest
try:
manifest = AIdb.findManifest(criteria, aisql)
except StandardError as err:
print 'Content-Type: text/html' # HTML is following
print # blank line, end of headers
print '<pre><b>Error</b>:findManifest criteria<br>'
print err, '<br>'
print '<ol>servicename =', servicename
print 'port =', port
print 'path =', path
print 'form_data =', orig_data
print 'criteria =', criteria
print 'servicename found by port =', found_servicename, '</ol>'
print '</pre>'
return
# check if findManifest() returned a number equal to 0
# (means we got no manifests back -- thus we serve the default if desired)
if manifest is None and not no_default:
manifest = service.get_default_manifest()
# if we have a manifest to return, prepare its return
if manifest is not None:
try:
# construct the fully qualified filename
filename = os.path.abspath(os.path.join(service.manifest_dir,
manifest))
# open and read the manifest
with open(filename, 'rb') as mfp:
manifest_str = mfp.read()
# maintain compability with older AI client
if servicename is None or \
float(protocolversion) < float(PROFILES_VERSION):
content_type = mimetypes.types_map.get('.xml', 'text/plain')
print 'Content-Length:', len(manifest_str) # Length of the file
print 'Content-Type:', content_type # XML is following
print # blank line, end of headers
print manifest_str
logging.info('Manifest sent from %s.' % filename)
return
except OSError as err:
print 'Content-Type: text/html' # HTML is following
print # blank line, end of headers
print '<pre>'
# report the internal error to error_log and requesting client
sys.stderr.write(_('error:manifest (%s) %s\n') % \
(str(manifest), err))
sys.stdout.write(_('error:manifest (%s) %s\n') % \
(str(manifest), err))
print '</pre>'
return
# get AI service image path
service = AIService(servicename)
image_dir = service.image.path
# construct object to contain MIME multipart message
outermime = MIMEMultipart()
client_msg = list() # accumulate message output for AI client
# If we have a manifest, attach it to the return message
if manifest is not None:
# add manifest as attachment
msg = MIMEText(manifest_str, 'xml')
# indicate manifest using special name
msg.add_header('Content-Disposition', 'attachment',
filename=sc.AI_MANIFEST_ATTACHMENT_NAME)
outermime.attach(msg) # add manifest as an attachment
# search for any profiles matching client criteria
# formulate database query to profiles table
q_str = "SELECT DISTINCT name, file FROM " + \
AIdb.PROFILES_TABLE + " WHERE "
nvpairs = list() # accumulate criteria values from post-data
# for all AI client criteria
for crit in AIdb.getCriteria(aisql.getQueue(), table=AIdb.PROFILES_TABLE,
onlyUsed=False):
if crit not in criteria:
msgtxt = _("Warning: client criteria \"%s\" not provided in "
"request. Setting value to NULL for profile lookup.") \
% crit
client_msg += [msgtxt]
logging.warn(msgtxt)
# fetch only global profiles destined for all clients
if AIdb.isRangeCriteria(aisql.getQueue(), crit,
AIdb.PROFILES_TABLE):
nvpairs += ["MIN" + crit + " IS NULL"]
nvpairs += ["MAX" + crit + " IS NULL"]
else:
nvpairs += [crit + " IS NULL"]
continue
# prepare criteria value to add to query
envval = AIdb.sanitizeSQL(criteria[crit])
if AIdb.isRangeCriteria(aisql.getQueue(), crit, AIdb.PROFILES_TABLE):
# If no default profiles are requested, then we mustn't allow
# this criteria to be NULL. It must match the client's given
# value for this criteria.
if no_default:
if crit == "mac":
nvpairs += ["(HEX(MIN" + crit + ")<=HEX(X'" + envval + \
"'))"]
nvpairs += ["(HEX(MAX" + crit + ")>=HEX(X'" + envval + \
"'))"]
else:
nvpairs += ["(MIN" + crit + "<='" + envval + "')"]
nvpairs += ["(MAX" + crit + ">='" + envval + "')"]
else:
if crit == "mac":
nvpairs += ["(MIN" + crit + " IS NULL OR "
"HEX(MIN" + crit + ")<=HEX(X'" + envval + "'))"]
nvpairs += ["(MAX" + crit + " IS NULL OR HEX(MAX" +
crit + ")>=HEX(X'" + envval + "'))"]
else:
nvpairs += ["(MIN" + crit + " IS NULL OR MIN" +
crit + "<='" + envval + "')"]
nvpairs += ["(MAX" + crit + " IS NULL OR MAX" +
crit + ">='" + envval + "')"]
else:
# If no default profiles are requested, then we mustn't allow
# this criteria to be NULL. It must match the client's given
# value for this criteria.
#
# Also, since this is a non-range criteria, the value stored
# in the DB may be a whitespace separated list of single
# values. We use a special user-defined function in the
# determine if the given criteria is in that textual list.
if no_default:
nvpairs += ["(is_in_list('" + crit + "', '" + envval + \
"', " + crit + ", 'None') == 1)"]
else:
nvpairs += ["(" + crit + " IS NULL OR is_in_list('" + crit + \
"', '" + envval + "', " + crit + ", 'None') == 1)"]
if len(nvpairs) > 0:
q_str += " AND ".join(nvpairs)
# issue database query
logging.info("Profile query: " + q_str)
query = AIdb.DBrequest(q_str)
aisql.getQueue().put(query)
query.waitAns()
if query.getResponse() is None or len(query.getResponse()) == 0:
msgtxt = _("No profiles found.")
client_msg += [msgtxt]
logging.info(msgtxt)
else:
for row in query.getResponse():
profpath = row['file']
profname = row['name']
if profname is None: # should not happen
profname = 'unnamed'
try:
if profpath is None:
msgtxt = "Database record error - profile path is " \
"empty."
client_msg += [msgtxt]
logging.error(msgtxt)
continue
msgtxt = _('Processing profile %s') % profname
client_msg += [msgtxt]
logging.info(msgtxt)
with open(profpath, 'r') as pfp:
raw_profile = pfp.read()
# do any template variable replacement {{AI_xxx}}
tmpl_profile = sc.perform_templating(raw_profile,
template_dict)
# precautionary validation of profile, logging only
sc.validate_profile_string(tmpl_profile, image_dir,
dtd_validation=True,
warn_if_dtd_missing=True)
except IOError as err:
msgtxt = _("Error: I/O error: ") + str(err)
client_msg += [msgtxt]
logging.error(msgtxt)
continue
except OSError:
msgtxt = _("Error: OS error on profile ") + profpath
client_msg += [msgtxt]
logging.error(msgtxt)
continue
except KeyError:
msgtxt = _('Error: could not find criteria to substitute '
'in template: ') + profpath
client_msg += [msgtxt]
logging.error(msgtxt)
logging.error('Profile with template substitution error:' +
raw_profile)
continue
except lxml.etree.XMLSyntaxError as err:
# log validation error and proceed
msgtxt = _(
'Warning: syntax error found in profile: ') \
+ profpath
client_msg += [msgtxt]
logging.error(msgtxt)
for error in err.error_log:
msgtxt = _('Error: ') + error.message
client_msg += [msgtxt]
logging.error(msgtxt)
logging.info([_('Profile failing validation: ') +
lxml.etree.tostring(root)])
# build MIME message and attach to outer MIME message
msg = MIMEText(tmpl_profile, 'xml')
# indicate in header that this is an attachment
msg.add_header('Content-Disposition', 'attachment',
filename=profname)
# attach this profile to the manifest and any other profiles
outermime.attach(msg)
msgtxt = _('Parsed and loaded profile: ') + profname
client_msg += [msgtxt]
logging.info(msgtxt)
# any profiles and AI manifest have been attached to MIME message
# specially format list of messages for display on AI client console
if client_msg:
outtxt = ''
for msgtxt in client_msg:
msgtxt = _('SC profile locator:') + msgtxt
outtxt += str(msgtxt) + '\n'
# add AI client console messages as single plain text attachment
msg = MIMEText(outtxt, 'plain') # create MIME message
outermime.attach(msg) # attach MIME message to response
print outermime.as_string() # send MIME-formatted message