def setup_transform(cls, transform):
cls.transform = {}
for pattern, trans in transform.items():
cls.transform[pattern] = {
'function':
build_transform(trans,
vars=AttrDict(
(('content', None), ('handler', None))),
filename='url:%s' % cls.name),
'headers':
trans.get('headers', {}),
'encoding':
trans.get('encoding'),
}
def __init__(self, name, schedule, threadpool, ioloop=None):
'''
Create a new task based on a schedule in ioloop (default to current).
The schedule configuration accepts:
- startup: True to run at startup, '*' to run on every config change
- minutes, hours, dates, months, weekdays, years: cron schedule
- thread: True to run in a separate thread
'''
self.name = name
if 'function' not in schedule:
raise ValueError('schedule %s has no function:' % name)
if callable(schedule['function']):
self.function = schedule['function']
else:
self.function = build_transform(schedule,
vars={},
filename='schedule:%s' % name)
self.ioloop = ioloop or tornado.ioloop.IOLoop.current()
self.callback = None
if schedule.get('thread'):
fn = self.function
def on_done(future):
exception = future.exception(timeout=0)
if exception:
app_log.error('%s (thread): %s', name, exception)
self.function = lambda: threadpool.submit(fn).add_done_callback(
on_done)
# Run on schedule if any of the schedule periods are specified
periods = 'minutes hours dates months weekdays years'.split()
if any(schedule.get(key) for key in periods):
# Convert all valid values into strings (e.g. 30 => '30'), and ignore any spaces
cron = (str(schedule.get(key, '*')).replace(' ', '')
for key in periods)
self.cron = CronTab(' '.join(cron))
self.call_later()
elif not schedule.get('startup'):
app_log.warning('schedule:%s has no schedule nor startup', name)
# Run now if the task is to be run on startup. Don't re-run if the config was reloaded
startup = schedule.get('startup')
if startup == '*' or (startup is True
and not ioloop_running(self.ioloop)):
self.function()
def _setup(cls, **kwargs):
override_methods = {
'open': ['handler'],
'on_message': ['handler', 'message'],
'on_close': ['handler'],
'on_pong': ['handler', 'data'],
'select_subprotocol': ['handler', 'subprotocols'],
'get_compression_options': ['handler'],
}
for method in override_methods:
if method in kwargs:
setattr(cls, method, build_transform(
kwargs[method],
vars=OrderedDict((arg, None) for arg in override_methods[method]),
filename='url:%s.%s' % (cls.name, method)))
def setup(cls, url, request_headers={}, default={}, prepare=None, modify=None,
headers={}, connect_timeout=20, request_timeout=20, **kwargs):
super(ProxyHandler, cls).setup(**kwargs)
WebSocketHandler._setup(cls, **kwargs)
cls.url, cls.request_headers, cls.default = url, request_headers, default
cls.headers = headers
cls.connect_timeout, cls.request_timeout = connect_timeout, request_timeout
cls.info = {}
for key, fn in (('prepare', prepare), ('modify', modify)):
if fn:
cls.info[key] = build_transform(
{'function': fn}, filename='url:%s.%s' % (cls.name, key),
vars={'handler': None, 'request': None, 'response': None})
cls.browser = AsyncHTTPClient()
cls.post = cls.put = cls.delete = cls.patch = cls.options = cls.get
def register_commands(register: Dict[str, str]) -> None:
'''
Register a new command to the command list.
:arg dict register: keys are the command name. Values are the Python expression to run to apply
the command. The expression can use 3 variables: ``shape`` (the Shape object to modify),
``spec`` (the configuration passed to your command) and ``data``.
'''
assert isinstance(
register, dict), 'register: must be a dict, not %s' % type(register)
for key, conf in register.items():
commands.cmdlist[key] = build_transform({'function': conf},
vars={
'shape': None,
'spec': None,
'data': None
},
iter=False)
def stack_shapes(collection, change, data, handler):
'''
Function to stack Shapes if required.
'''
data_len = len(data)
for shape in collection:
if shape.name not in change:
continue
info = change[shape.name]
if 'data' in info and info.get('stack') is not None:
_vars = {'_color': None, 'data': None, 'handler': None}
if not isinstance(info['data'], (dict,)):
info['data'] = {'function': '{}'.format(info['data'])}
elif isinstance(info['data'], (dict,)) and 'function' not in info['data']:
info['data'] = {'function': '{}'.format(info['data'])}
args = {'data': data, 'handler': handler}
data_len = len(build_transform(info['data'], vars=_vars)(**args)[0])
stack_elements(data_len, shape, stack=info.get('stack'), margin=info.get('margin'))
def apply_transform(data, spec):
'''apply transform on dataframe'''
pandas_transforms = {
'REPLACE': pd.Series.replace,
'MAP': pd.Series.map,
'IN': pd.Series.isin,
'NOTIN': lambda s, v: ~s.isin(v),
'CONTAINS': {
'function': lambda s, v, **ops: s.str.contains(v, **ops),
'defaults': {
'case': False
}
},
'NOTCONTAINS': {
'function': lambda s, v, **ops: ~s.str.contains(v, **ops),
'defaults': {
'case': False
}
},
'LEN': lambda s, _: s.str.len(),
'LOWER': lambda s, _: s.str.lower(),
'UPPER': lambda s, _: s.str.upper(),
'PROPER': lambda s, _: s.str.capitalize(),
'STARTSWITH': lambda s, v: s.str.startswith(v),
'ENDSWITH': lambda s, v: s.str.endswith(v)
}
# TODO: STRREPLACE
if spec['type'] == 'function':
fn = build_transform({'function': spec['expr']},
vars={'data': None},
filename='lv: %s' % spec.get('name'))
fn(data) # applies on copy
return data
expr = spec['expr']
func = pandas_transforms[expr['op']]
kwargs = expr.get('kwargs', {})
if isinstance(func, dict):
# use defaults' kwargs if not present in expr.get
for key, val in func.get('defaults', {}).items():
if key not in kwargs:
kwargs[key] = val
func = func['function']
data[spec['as']] = func(data[expr['col']], expr.get('value'), **kwargs)
return data
def test_invalid_change(self):
fn = build_transform(yaml_parse('function: testlib.dummy.invalid\nargs: []'))
remove(self.dummy.replace('.py', '.pyc'))
with io.open(self.dummy, 'w', encoding='utf-8') as handle:
handle.write('def invalid():\n\tsyntax error\n')
with assert_raises(SyntaxError):
fn()
remove(self.dummy.replace('.py', '.pyc'))
with io.open(self.dummy, 'w', encoding='utf-8') as handle:
handle.write('1/0\ndef invalid():\n\treturn 100\n')
with assert_raises(ZeroDivisionError):
fn()
remove(self.dummy.replace('.py', '.pyc'))
with io.open(self.dummy, 'w', encoding='utf-8') as handle:
handle.write('def invalid():\n\treturn 100\n')
eq_(fn(), [100])
def load_data(data_config, handler=None):
'''
Loads data using gramex cache.
'''
if not isinstance(data_config, (dict, AttrDict,)):
raise ValueError('Data argument must be a dict like object.')
data = {}
for key, conf in data_config.items():
if isinstance(conf, (dict, AttrDict,)):
if 'function' in conf:
data[key] = build_transform(conf, vars={'handler': None})(handler=handler)[0]
elif conf.get('ext') in {'yaml', 'yml', 'json'}:
data[key] = gramex.cache.open(conf.pop('url'), conf.pop('ext'), **dict(conf))
elif 'url' in conf:
data[key] = gramex.data.filter(conf.pop('url'), **dict(conf))
else:
data[key] = conf
return data
def __init__(self, **kwargs):
self.params = kwargs
self.url = 'https://stream.twitter.com/1.1/statuses/filter.json'
self.valid_params = {
'follow', 'track', 'locations', 'delimited', 'stall_warnings',
'filter_level', 'language'}
self.enabled = True
self.delay = 0
# Set up writers
if 'path' in kwargs:
self.stream = StreamWriter(kwargs['path'], flush=kwargs.get('flush', False))
self.process_bytes = self.stream.write
elif 'function' in kwargs:
self.process_json = build_transform(
kwargs, vars={'message': {}}, filename='TwitterStream:function')
elif kwargs.get('driver') == 'sqlalchemy':
engine = gramex.data.create_engine(kwargs['url'], **kwargs.get('parameters', {}))
table = gramex.data.get_table(kwargs['table'])
fields = kwargs['fields']
for field in list(fields.keys()):
if field not in table.columns:
app_log.error('TwitterStream field %s not in table' % field)
fields.pop(field)
flatten = flattener(fields=fields)
self.process_json = lambda tweet: engine.execute(table.insert(flatten(tweet)))
self.buf = bytearray()
self.client = tornado.httpclient.HTTPClient()
while True:
# Set .enabled to False to temporarily disable streamer
if self.enabled:
params = {key: val.encode('utf-8') for key, val in self.params.items()
if key in self.valid_params}
if 'follow' not in params and 'track' not in params and 'locations' not in params:
self.enabled = False
self.delay = 5
app_log.error('TwitterStream needs follow, track or locations. Disabling')
else:
self.fetch_tweets(params)
# Restart after a delay determined by
time.sleep(self.delay)
def setup(cls, **kwargs):
super(DataHandler, cls).setup(**kwargs)
cls.setup_data(kwargs)
driver = kwargs.get('driver')
cls.driver_name = driver
if driver == 'sqlalchemy':
cls.driver_method = cls._sqlalchemy
# Create a cached metadata store for SQLAlchemy engines
cls.meta = sa.MetaData()
elif driver == 'blaze':
cls.driver_method = cls._blaze
else:
raise NotImplementedError('driver=%s is not supported yet.' %
driver)
posttransform = kwargs.get('posttransform', {})
cls.posttransform = []
if 'function' in posttransform:
cls.posttransform.append(
build_transform(posttransform,
vars=AttrDict(content=None),
filename='url:%s' % cls.name))
def check_transform(self, transform, yaml_code, vars=None, cache=True, iter=True):
fn = build_transform(yaml_parse(yaml_code), vars=vars, cache=cache, iter=iter)
eqfn(fn, transform)
return fn
def setup(cls, **kwargs):
super(FormHandler, cls).setup(**kwargs)
conf_kwargs = merge(
AttrDict(kwargs),
objectpath(gramex_conf, 'handlers.FormHandler', {}), 'setdefault')
cls.headers = conf_kwargs.pop('headers', {})
# Top level formats: key is special. Don't treat it as data
cls.formats = conf_kwargs.pop('formats', {})
default_config = conf_kwargs.pop('default', None)
# Remove other known special keys from dataset configuration
cls.clear_special_keys(conf_kwargs)
# If top level has url: then data spec is at top level. Else it's a set of sub-keys
if 'url' in conf_kwargs:
cls.datasets = AttrDict(data=conf_kwargs)
cls.single = True
else:
if 'modify' in conf_kwargs:
cls.modify_all = staticmethod(
build_transform(
conf={'function': conf_kwargs.pop('modify', None)},
vars=cls.function_vars['modify'],
filename='%s.%s' % (cls.name, 'modify'),
iter=False))
cls.datasets = conf_kwargs
cls.single = False
# Apply defaults to each key
if isinstance(default_config, dict):
for key in cls.datasets:
config = cls.datasets[key].get('default', {})
cls.datasets[key]['default'] = merge(config,
default_config,
mode='setdefault')
# Ensure that each dataset is a dict with a url: key at least
for key, dataset in list(cls.datasets.items()):
if not isinstance(dataset, dict):
app_log.error('%s: %s: must be a dict, not %r' %
(cls.name, key, dataset))
del cls.datasets[key]
elif 'url' not in dataset:
app_log.error('%s: %s: does not have a url: key' %
(cls.name, key))
del cls.datasets[key]
# Ensure that id: is a list -- if it exists
if 'id' in dataset and not isinstance(dataset['id'], list):
dataset['id'] = [dataset['id']]
# Convert function: into a data = transform(data) function
conf = {
'function': dataset.pop('function', None),
'args': dataset.pop('args', None),
'kwargs': dataset.pop('kwargs', None)
}
if conf['function'] is not None:
fn_name = '%s.%s.transform' % (cls.name, key)
dataset['transform'] = build_transform(conf,
vars={
'data': None,
'handler': None
},
filename=fn_name,
iter=False)
# Convert modify: and prepare: into a data = modify(data) function
for fn, fn_vars in cls.function_vars.items():
if fn in dataset:
dataset[fn] = build_transform(
conf={'function': dataset[fn]},
vars=fn_vars,
filename='%s.%s.%s' % (cls.name, key, fn),
iter=False)
def setup(cls,
prepare=None,
action=None,
delay=None,
session_expiry=None,
session_inactive=None,
user_key='user',
lookup=None,
recaptcha=None,
**kwargs):
# Switch SSL certificates if required to access Google, etc
gramex.service.threadpool.submit(check_old_certs)
# Set up default redirection based on ?next=...
if 'redirect' not in kwargs:
kwargs['redirect'] = AttrDict([('query', 'next'),
('header', 'Referer')])
super(AuthHandler, cls).setup(**kwargs)
# Set up logging for login/logout events
logger = logging.getLogger('gramex.user')
keys = objectpath(gramex.conf, 'log.handlers.user.keys', [])
log_info = build_log_info(keys, 'event')
cls.log_user_event = lambda handler, event: logger.info(
log_info(handler, event))
# Count failed logins
cls.failed_logins = Counter()
# Set delay for failed logins from the delay: parameter which can be a number or list
default_delay = [1, 1, 5]
cls.delay = delay
if isinstance(cls.delay, list) and not all(
isinstance(n, (int, float)) for n in cls.delay):
app_log.warning('%s: Ignoring invalid delay: %r', cls.name,
cls.delay)
cls.delay = default_delay
elif isinstance(cls.delay, (int, float)) or cls.delay is None:
cls.delay = default_delay
# Set up session user key, session expiry and inactive expiry
cls.session_user_key = user_key
cls.session_expiry = session_expiry
cls.session_inactive = session_inactive
# Set up lookup. Split a copy into self.lookup_id which has the ID, and
# self.lookup which has gramex.data keywords.
cls.lookup = None
if lookup is not None:
cls.lookup = lookup.copy()
if isinstance(lookup, dict):
cls.lookup_id = cls.lookup.pop('id', 'user')
else:
app_log.error('%s: lookup must be a dict, not %s', cls.name,
cls.lookup)
# Set up prepare
cls.auth_methods = {}
if prepare is not None:
cls.auth_methods['prepare'] = build_transform(
conf={'function': prepare},
vars={
'handler': None,
'args': None
},
filename='url:%s:prepare' % cls.name,
iter=False)
# Prepare recaptcha
if recaptcha is not None:
if 'key' not in recaptcha:
app_log.error('%s: recaptcha.key missing', cls.name)
elif 'key' not in recaptcha:
app_log.error('%s: recaptcha.secret missing', cls.name)
else:
recaptcha.setdefault('action', 'login')
cls.auth_methods['recaptcha'] = cls.check_recaptcha
# Set up post-login actions
cls.actions = []
if action is not None:
if not isinstance(action, list):
action = [action]
for conf in action:
cls.actions.append(
build_transform(conf,
vars=AttrDict(handler=None),
filename='url:%s:%s' %
(cls.name, conf.function)))
def load_data(_conf, _default_key: str = None, **kwargs) -> dict:
'''
Loads datasets based on configuration and returns a dict of those datasets.
:arg dataset _conf: The dataset configuration
:arg str _default_key: Can be ``function``, ``url`` or ``None`` (default).
If specified, it converts string data configurations into ``{_default_key: _conf}``.
:return: A dict of datasets loaded based on the configuration.
``_conf`` is processed as follows:
- String ``'data.xlsx'`` is loaded via :py:func:`gramex.cache.open` into ``{data: ...}`` if
``_default_key == 'url'``
- String ``'data[0]'`` is evaluated via :py:func:`gramex.transforms.build_transform` into
``{data: ...}``` if ``_default_key == 'function'``
- String ``anything``` raises an Exception if ``_default_key`` is None
- Dict ``{url: ...}`` is loaded with :py:func:`gramex.data.filter` into ``{data: ...}``
- Dict ``{function: ...}`` is evaluated via :py:func:`gramex.transforms.build_transform`
into ``{data: ...}``
- Dict ``{x: ..., y: ...}`` loads the respective datasets into ``x`` and ``y`` instead of
``data``. Each dataset is processed using the above rules.
- Any other datatype passed is returned as is in ``{data: ...}``
Any keyword arguments passed are also added to the resulting dataset, but overwritten only if
``_conf`` loaded a dataset that's not ``None``.
'''
def str2conf(data, key):
'''Convert string configurations to {url: str} or {function:str} based on _default_key'''
# If data is not a string, return data as-is
if not isinstance(data, str):
return data
# If data is a string, return {_default_key: data} (or raise a TypeError)
if _default_key is not None:
return {_default_key: data}
raise TypeError('%s: must be a dict, not %r' % (key, data))
data = str2conf(_conf, 'data')
if not isinstance(data, dict) or 'url' in data or 'function' in data:
data = {'data': data}
data = {key: str2conf(conf, key) for key, conf in data.items()}
for key, conf in data.items():
if isinstance(conf, dict):
conf = copy.copy(conf)
if 'url' in conf:
if 'transform' in conf:
conf['transform'] = build_transform(
{'function': conf['transform']},
vars={'data': None, 'handler': None},
filename='PPTXHandler:data.%s' % key, iter=False)
data[key] = gramex.data.filter(**conf)
if 'function' in conf:
# Let functions use previously defined data variables, including current one
_kwargs = {**kwargs, **data}
_vars = {key: None for key in _kwargs}
data[key] = build_transform(conf, vars=_vars, iter=False)(**_kwargs)
# If the dataset returns a None, don't overwrite the default kwargs.
# This allow defaults to pass through if a dataset is specified as None.
for key, val in data.items():
if (key not in kwargs) or (val is not None):
kwargs[key] = val
return kwargs
def create_alert(name, alert):
'''Generate the function to be run by alert() using the alert configuration'''
# Configure email service
if alert.get('service', None) is None:
if len(info.email) > 0:
alert['service'] = list(info.email.keys())[0]
app_log.warning('alert: %s: using first email service: %s', name,
alert['service'])
else:
app_log.error('alert: %s: define an email: service to use', name)
return
service = alert['service']
mailer = info.email.get(service, None)
if mailer is None:
app_log.error('alert: %s: undefined email service: %s', name, service)
return
# - Warn if to, cc, bcc exists and is not a string or list of strings. Ignore incorrect
# - if to: [1, '*****@*****.**'], then
# - log a warning about the 1. Drop the 1. to: becomes ['*****@*****.**']
# Error if to, cc, bcc are all missing, return None
if not any(key in alert for key in ['to', 'cc', 'bcc']):
app_log.error('alert: %s: missing to/cc/bcc', name)
return
# Ensure that config has the right type (str, dict, list)
contentfields = [
'body', 'html', 'bodyfile', 'htmlfile', 'markdown', 'markdownfile'
]
addr_fields = ['to', 'cc', 'bcc', 'reply_to', 'on_behalf_of', 'from']
for key in ['subject'] + addr_fields + contentfields:
if not isinstance(alert.get(key, ''), string_types + (list, )):
app_log.error('alert: %s.%s: %r must be a list or str', name, key,
alert[key])
return
if not isinstance(alert.get('images', {}), dict):
app_log.error('alert: %s.images: %r is not a dict', name,
alert['images'])
return
if not isinstance(alert.get('attachments', []), list):
app_log.error('alert: %s.attachments: %r is not a list', name,
alert['attachments'])
return
# Warn if subject is missing
if 'subject' not in alert:
app_log.warning('alert: %s: missing subject', name)
# Warn if body, html, bodyfile, htmlfile keys are missing
if not any(key in alert for key in contentfields):
app_log.warning('alert: %s: missing body/html/bodyfile/htmlfile/...',
name)
# Pre-compile data.
# - `data: {key: [...]}` -- loads data in-place
# - `data: {key: {url: file}}` -- loads from a file
# - `data: {key: {url: sqlalchemy-url, table: table}}` -- loads from a database
# - `data: file` -- same as `data: {data: {url: file}}`
# - `data: {key: file}` -- same as `data: {key: {url: file}}`
# - `data: [...]` -- same as `data: {data: [...]}`
datasets = {}
if 'data' in alert:
if isinstance(alert['data'], string_types):
datasets = {'data': {'url': alert['data']}}
elif isinstance(alert['data'], list):
datasets = {'data': alert['data']}
elif isinstance(alert['data'], dict):
for key, dataset in alert['data'].items():
if isinstance(dataset, string_types):
datasets[key] = {'url': dataset}
elif isinstance(dataset, list) or 'url' in dataset:
datasets[key] = dataset
else:
app_log.error('alert: %s.data: %s is missing url:', name,
key)
else:
app_log.error(
'alert: %s.data: must be a data file or dict. Not %s', name,
repr(alert['data']))
if 'each' in alert and alert['each'] not in datasets:
app_log.error('alert: %s.each: %s is not in data:', name,
alert['each'])
return
vars = {key: None for key in datasets}
vars.update({'config': None, 'args': None})
condition = build_transform({'function': alert.get('condition', 'True')},
filename='alert: %s' % name,
vars=vars,
iter=False)
alert_logger = logging.getLogger('gramex.alert')
def load_datasets(data, each):
'''
Modify data by load datasets and filter by condition.
Modify each to apply the each: argument, else return (None, None)
'''
for key, val in datasets.items():
# Allow raw data in lists as-is. Treat dicts as {url: ...}
data[key] = val if isinstance(val, list) else gramex.data.filter(
**val)
result = condition(**data)
# Avoiding isinstance(result, pd.DataFrame) to avoid importing pandas
if type(result).__name__ == 'DataFrame':
data['data'] = result
elif isinstance(result, dict):
data.update(result)
elif not result:
app_log.debug('alert: %s stopped. condition = %s', name, result)
return
if 'each' in alert:
each_data = data[alert['each']]
if isinstance(each_data, dict):
each += list(each_data.items())
elif isinstance(each_data, list):
each += list(enumerate(each_data))
elif hasattr(each_data, 'iterrows'):
each += list(each_data.iterrows())
else:
raise ValueError(
'alert: %s: each: data.%s must be dict/list/DF, not %s' %
(name, alert['each'], type(each_data)))
else:
each.append((0, None))
def create_mail(data):
'''
Return kwargs that can be passed to a mailer.mail
'''
mail = {}
for key in ['bodyfile', 'htmlfile', 'markdownfile']:
target = key.replace('file', '')
if key in alert and target not in alert:
path = _tmpl(alert[key]).generate(**data).decode('utf-8')
tmpl = gramex.cache.open(path, 'template')
mail[target] = tmpl.generate(**data).decode('utf-8')
for key in addr_fields + ['subject', 'body', 'html', 'markdown']:
if key not in alert:
continue
if isinstance(alert[key], list):
mail[key] = [
_tmpl(v).generate(**data).decode('utf-8')
for v in alert[key]
]
else:
mail[key] = _tmpl(alert[key]).generate(**data).decode('utf-8')
headers = {}
# user: {id: ...} creates an X-Gramex-User header to mimic the user
if 'user' in alert:
user = deepcopy(alert['user'])
for key, val, node in walk(user):
node[key] = _tmpl(val).generate(**data).decode('utf-8')
user = json.dumps(user, ensure_ascii=True, separators=(',', ':'))
headers['X-Gramex-User'] = tornado.web.create_signed_value(
info.app.settings['cookie_secret'], 'user', user)
if 'markdown' in mail:
mail['html'] = _markdown_convert(mail.pop('markdown'))
if 'images' in alert:
mail['images'] = {}
for cid, val in alert['images'].items():
urlpath = _tmpl(val).generate(**data).decode('utf-8')
urldata = urlfetch(urlpath, info=True, headers=headers)
if urldata['content_type'].startswith('image/'):
mail['images'][cid] = urldata['name']
else:
with io.open(urldata['name'], 'rb') as temp_file:
bytestoread = 80
first_line = temp_file.read(bytestoread)
# TODO: let admin know that the image was not processed
app_log.error(
'alert: %s: %s: %d (%s) not an image: %s\n%r', name,
cid, urldata['r'].status_code, urldata['content_type'],
urlpath, first_line)
if 'attachments' in alert:
mail['attachments'] = [
urlfetch(_tmpl(v).generate(**data).decode('utf-8'),
headers=headers) for v in alert['attachments']
]
return mail
def run_alert(callback=None, args=None):
'''
Runs the configured alert. If a callback is specified, calls the
callback with all email arguments. Else sends the email.
If args= is specified, add it as data['args'].
'''
app_log.info('alert: %s running', name)
data, each, fail = {
'config': alert,
'args': {} if args is None else args
}, [], []
try:
load_datasets(data, each)
except Exception as e:
app_log.exception('alert: %s data processing failed', name)
fail.append({'error': e})
retval = []
for index, row in each:
data['index'], data['row'], data['config'] = index, row, alert
try:
retval.append(
AttrDict(index=index, row=row, mail=create_mail(data)))
except Exception as e:
app_log.exception('alert: %s[%s] templating (row=%r)', name,
index, row)
fail.append({'index': index, 'row': row, 'error': e})
callback = mailer.mail if not callable(callback) else callback
done = []
for v in retval:
try:
callback(**v.mail)
except Exception as e:
fail.append({
'index': v.index,
'row': v.row,
'mail': v.mail,
'error': e
})
app_log.exception('alert: %s[%s] delivery (row=%r)', name,
v.index, v.row)
else:
done.append(v)
event = {
'alert':
name,
'service':
service,
'from':
mailer.email or '',
'to':
'',
'cc':
'',
'bcc':
'',
'subject':
'',
'datetime':
datetime.datetime.utcnow().strftime("%Y-%m-%d %H:%M:%SZ")
}
event.update({k: v for k, v in v.mail.items() if k in event})
event['attachments'] = ', '.join(v.mail.get('attachments', []))
alert_logger.info(event)
# Run notifications
args = {'done': done, 'fail': fail}
for notification_name in alert.get('notify', []):
notify = info.alert.get(notification_name)
if notify is not None:
notify.run(callback=callback, args=args)
else:
app_log.error('alert: %s.notify: alert %s not defined', name,
notification_name)
return args
return run_alert
def setup(cls, data=None, model={}, config_dir='', **kwargs):
cls.slug = slugify(cls.name)
# Create the config store directory
if not config_dir:
config_dir = op.join(gramex.config.variables['GRAMEXDATA'], 'apps',
'mlhandler', cls.slug)
_mkdir(config_dir)
cls.config_dir = config_dir
cls.config_store = cache.JSONStore(op.join(cls.config_dir,
'config.json'),
flush=None)
cls.data_store = op.join(cls.config_dir, 'data.h5')
cls.template = kwargs.pop('template', DEFAULT_TEMPLATE)
super(MLHandler, cls).setup(**kwargs)
try:
if 'transform' in data:
data['transform'] = build_transform(
{'function': data['transform']},
vars={
'data': None,
'handler': None
},
filename='MLHandler:data',
iter=False)
cls._built_transform = staticmethod(data['transform'])
else:
cls._built_transform = staticmethod(lambda x: x)
data = gdata.filter(**data)
cls.store_data(data)
except TypeError:
app_log.warning('MLHandler could not find training data.')
data = None
cls._built_transform = staticmethod(lambda x: x)
default_model_path = op.join(cls.config_dir,
slugify(cls.name) + '.pkl')
cls.model_path = model.pop('path', default_model_path)
# store the model kwargs from gramex.yaml into the store
for key in TRANSFORMS:
cls.set_opt(key, model.get(key, cls.get_opt(key)))
# Remove target_col if it appears anywhere in cats or nums
target_col = cls.get_opt('target_col')
cls.set_opt('cats', list(set(cls.get_opt('cats')) - {target_col}))
cls.set_opt('nums', list(set(cls.get_opt('nums')) - {target_col}))
cls.set_opt('class', model.get('class'))
cls.set_opt('params', model.get('params', {}))
if op.exists(cls.model_path): # If the pkl exists, load it
cls.model = joblib.load(cls.model_path)
elif data is not None:
mclass = cls.get_opt('class', model.get('class', False))
params = cls.get_opt('params', {})
data = cls._filtercols(data)
data = cls._filterrows(data)
cls.model = cls._assemble_pipeline(data,
mclass=mclass,
params=params)
# train the model
target = data[target_col]
train = data[[c for c in data if c != target_col]]
gramex.service.threadpool.submit(_fit, cls.model, train, target,
cls.model_path, cls.name)
cls.config_store.flush()
def create_alert(name, alert):
'''Generate the function to be run by alert() using the alert configuration'''
# Configure email service
if alert.get('service', None) is None:
if len(info.email) > 0:
alert['service'] = list(info.email.keys())[0]
app_log.warning('alert: %s: using first email service: %s', name,
alert['service'])
else:
app_log.error('alert: %s: define an email: service to use', name)
return
service = alert['service']
mailer = info.email.get(service, None)
if mailer is None:
app_log.error('alert: %s: undefined email service: %s', name, service)
return
# - Warn if to, cc, bcc exists and is not a string or list of strings. Ignore incorrect
# - if to: [1, '*****@*****.**'], then
# - log a warning about the 1. Drop the 1. to: becomes ['*****@*****.**']
# Error if to, cc, bcc are all missing, return None
if not any(key in alert for key in ['to', 'cc', 'bcc']):
app_log.error('alert: %s: missing to/cc/bcc', name)
return
# Warn if subject is missing
if 'subject' not in alert:
app_log.warning('alert: %s: missing subject', name)
# Warn if body, html, bodyfile, htmlfile keys are missing
contentfields = [
'body', 'html', 'bodyfile', 'htmlfile', 'markdown', 'markdownfile'
]
if not any(key in alert for key in contentfields):
app_log.warning('alert: %s: missing body/html/bodyfile/htmlfile/...',
name)
# Precompile templates
templates = {}
for key in ['to', 'cc', 'bcc', 'from', 'subject'] + contentfields:
if key in alert:
tmpl = alert[key]
if isinstance(tmpl, string_types):
templates[key] = Template(tmpl)
elif isinstance(tmpl, list):
templates[key] = [Template(subtmpl) for subtmpl in tmpl]
else:
app_log.error('alert: %s: %s: %r must be a list or str', name,
key, tmpl)
return
if 'images' in alert:
images = alert['images']
if isinstance(images, dict):
templates['images'] = {
cid: Template(path)
for cid, path in images.items()
}
else:
app_log.error('alert: %s images: %r is not a dict', name, images)
if 'attachments' in alert:
attachments = alert['attachments']
if isinstance(attachments, list):
templates['attachments'] = [Template(path) for path in attachments]
# Pre-compile data.
# - `data: {key: [...]}` -- loads data in-place
# - `data: {key: {url: file}}` -- loads from a file
# - `data: {key: {url: sqlalchemy-url, table: table}}` -- loads from a database
# - `data: file` -- same as `data: {data: {url: file}}`
# - `data: {key: file}` -- same as `data: {key: {url: file}}`
# - `data: [...]` -- same as `data: {data: [...]}`
datasets = {}
if 'data' in alert:
if isinstance(alert['data'], string_types):
datasets = {'data': {'url': alert['data']}}
elif isinstance(alert['data'], list):
datasets = {'data': alert['data']}
elif isinstance(alert['data'], dict):
for key, dataset in alert['data'].items():
if isinstance(dataset, string_types):
datasets[key] = {'url': dataset}
elif isinstance(dataset, list) or 'url' in dataset:
datasets[key] = dataset
else:
app_log.error('alert: %s data: %s is missing url:', name,
key)
else:
app_log.error(
'alert: %s data: must be a data file or dict. Not %s', name,
repr(alert['data']))
if 'each' in alert and alert['each'] not in datasets:
app_log.error('alert: %s each: %s is not in data:', name,
alert['each'])
return
vars = {key: None for key in datasets}
vars['config'] = None
condition = build_transform({'function': alert.get('condition', 'True')},
filename='alert: %s' % name,
vars=vars,
iter=False)
alert_logger = logging.getLogger('gramex.alert')
def run_alert(callback=None):
'''
Runs the configured alert. If a callback is specified, calls the
callback with all email arguments. Else sends the email.
'''
app_log.info('alert: %s running', name)
data = {'config': alert}
for key, dataset in datasets.items():
# Allow raw data in lists as-is. Treat dicts as {url: ...}
data[key] = dataset if isinstance(
dataset, list) else gramex.data.filter(**dataset)
result = condition(**data)
# Avoiding isinstance(result, pd.DataFrame) to avoid importing pandas
if type(result).__name__ == 'DataFrame':
data['data'] = result
elif isinstance(result, dict):
data.update(result)
elif not result:
app_log.debug('alert: %s stopped. condition = %s', name, result)
return
each = [(None, None)]
if 'each' in alert:
each_data = data[alert['each']]
if isinstance(each_data, dict):
each = list(each_data.items())
elif isinstance(each_data, list):
each = list(enumerate(each_data))
elif hasattr(each_data, 'iterrows'):
each = list(each_data.iterrows())
else:
app_log.error(
'alert: %s: each: requires data.%s to be a dict/list/DataFrame',
name, alert['each'])
return
kwargslist = []
for index, row in each:
data['index'], data['row'], data['config'] = index, row, alert
# Generate email content
kwargs = {}
kwargslist.append(kwargs)
for key in ['bodyfile', 'htmlfile', 'markdownfile']:
target = key.replace('file', '')
if key in templates and target not in templates:
path = templates[key].generate(**data).decode('utf-8')
tmpl = gramex.cache.open(path, 'template')
kwargs[target] = tmpl.generate(**data).decode('utf-8')
try:
for key in [
'to', 'cc', 'bcc', 'from', 'subject', 'body', 'html',
'markdown'
]:
if key in templates:
tmpl = templates[key]
if isinstance(tmpl, list):
kwargs[key] = []
for subtmpl in tmpl:
kwargs[key].append(
subtmpl.generate(**data).decode('utf-8'))
else:
kwargs[key] = tmpl.generate(**data).decode('utf-8')
except Exception:
# If any template raises an exception, log it and continue with next email
app_log.exception('alert: %s(#%s).%s: Template exception',
name, index, key)
continue
headers = {}
# user: {id: ...} creates an X-Gramex-User header to mimic the user
if 'user' in alert:
user = json.dumps(alert['user'],
ensure_ascii=True,
separators=(',', ':'))
headers['X-Gramex-User'] = tornado.web.create_signed_value(
info.app.settings['cookie_secret'], 'user', user)
if 'markdown' in kwargs:
kwargs['html'] = _markdown_convert(kwargs.pop('markdown'))
if 'images' in templates:
kwargs['images'] = {}
for cid, val in templates['images'].items():
urlpath = val.generate(**data).decode('utf-8')
urldata = urlfetch(urlpath, info=True, headers=headers)
if urldata['content_type'].startswith('image/'):
kwargs['images'][cid] = urldata['name']
else:
with io.open(urldata['name'], 'rb') as temp_file:
bytestoread = 80
first_line = temp_file.read(bytestoread)
app_log.error(
'alert: %s: %s: %d (%s) not an image: %s\n%r',
name, cid, urldata['r'].status_code,
urldata['content_type'], urlpath, first_line)
if 'attachments' in templates:
kwargs['attachments'] = [
urlfetch(attachment.generate(**data).decode('utf-8'),
headers=headers)
for attachment in templates['attachments']
]
if callable(callback):
return callback(**kwargs)
# Email recipient. TODO: run this in a queue. (Anand)
mailer.mail(**kwargs)
# Log the event
event = {
'alert':
name,
'service':
service,
'from':
mailer.email or '',
'to':
'',
'cc':
'',
'bcc':
'',
'subject':
'',
'datetime':
datetime.datetime.utcnow().strftime("%Y-%m-%d %H:%M:%SZ")
}
event.update({k: v for k, v in kwargs.items() if k in event})
event['attachments'] = ', '.join(kwargs.get('attachments', []))
alert_logger.info(event)
return kwargslist
return run_alert
def change_shapes(collection, change, data, handler, **kwargs):
'''
Apply changes to a collection of shapes in the context of data.
``collection`` is a slide.shapes or group shapes.
``change`` is typically a dict of <shape-name>: commands.
``data`` is a dictionary passed to the template engine.
'''
prs = kwargs.get('prs')
new_slide = kwargs.get('new_slide')
copy_slide = kwargs.get('copy_slide', False)
source_slide = kwargs.get('source_slide')
dest = prs.slides.add_slide(new_slide) if copy_slide else None
mapping = {}
for shape in collection:
if shape.name not in change:
copy_slide_elem(shape, dest)
continue
spec = change[shape.name]
if shape.name not in mapping:
mapping[shape.name] = 0
if spec.get('data'):
if not isinstance(spec['data'], (dict, )):
spec['data'] = {
'function':
'{}'.format(spec['data'])
if not isinstance(spec['data'], (
str,
six.string_types,
)) else spec['data']
}
shape_data = build_transform(spec['data'],
vars={
'data': None,
'handler': None
})(data=data, handler=handler)[0]
else:
if isinstance(data, (
dict,
AttrDict,
)) and 'handler' in data:
data.pop('handler')
shape_data = copy.deepcopy(data)
if isinstance(shape_data, (
dict,
AttrDict,
)):
shape_data['handler'] = handler
if spec.get('stack'):
shape_data = shape_data[mapping[shape.name]]
mapping[shape.name] = mapping[shape.name] + 1
# If the shape is a group, apply spec to each sub-shape
if is_group(shape):
sub_shapes = SlideShapes(shape.element, collection)
change_shapes(sub_shapes, spec, shape_data, handler)
# Add args to shape_data
if hasattr(handler, 'args'):
args = {k: v[0] for k, v in handler.args.items() if len(v) > 0}
shape_data['args'] = args
# Run commands in the spec
for cmd, method in COMMANDS_LIST.items():
if cmd in spec:
method(shape, spec, shape_data)
copy_slide_elem(shape, dest)
add_new_slide(dest, source_slide)
def setup_error(cls, error):
'''
Sample configuration::
error:
404:
path: template.json # Use a template
autoescape: false # with no autoescape
whitespace: single # as a single line
headers:
Content-Type: application/json
500:
function: module.fn
args: [=status_code, =kwargs, =handler]
'''
if not error:
return
if not isinstance(error, dict):
return app_log.error('url:%s.error is not a dict', cls.name)
# Compile all errors handlers
cls.error = {}
for error_code, error_config in error.items():
try:
error_code = int(error_code)
if error_code < 100 or error_code > 1000:
raise ValueError()
except ValueError:
app_log.error(
'url.%s.error code %s is not a number (100 - 1000)',
cls.name, error_code)
continue
if not isinstance(error_config, dict):
return app_log.error('url:%s.error.%d is not a dict', cls.name,
error_code)
# Make a copy of the original. When we add headers, etc, it shouldn't affect original
error_config = AttrDict(error_config)
error_path, error_function = error_config.get(
'path'), error_config.get('function')
if error_function:
if error_path:
error_config.pop('path')
app_log.warning(
'url.%s.error.%d has function: AND path:. Ignoring path:',
cls.name, error_code)
cls.error[error_code] = {
'function':
build_transform(
error_config,
vars=AttrDict((('status_code', None), ('kwargs', None),
('handler', None))),
filename='url:%s.error.%d' % (cls.name, error_code))
}
elif error_path:
encoding = error_config.get('encoding', 'utf-8')
cls.error[error_code] = {
'function': cls._error_fn(error_code, error_config)
}
mime_type, encoding = mimetypes.guess_type(error_path,
strict=False)
if mime_type:
error_config.setdefault('headers', {}).setdefault(
'Content-Type', mime_type)
else:
app_log.error(
'url.%s.error.%d must have a path or function key',
cls.name, error_code)
# Add the error configuration for reference
if error_code in cls.error:
cls.error[error_code]['conf'] = error_config
cls._write_error, cls.write_error = cls.write_error, cls._write_custom_error
def heatgrid(shape, spec, data):
'''Create a heat grid.'''
if shape.auto_shape_type != MSO_SHAPE.RECTANGLE:
raise NotImplementedError()
spec = copy.deepcopy(spec['heatgrid'])
top = shape.top
left = shape.left
width = shape.width
pixel_inch = 10000
default_height = 20
height = spec.get('cell-height', default_height) * pixel_inch
parent = shape._parent
shape.element.delete()
# Loading config
handler = data.pop('handler') if 'handler' in data else None
for key in ['row', 'column', 'value', 'column-order', 'row-order']:
if key not in spec:
continue
if isinstance(spec[key], (dict, )) and 'function' in spec[key]:
spec[key] = compile_function(spec, key, data, handler)
# Loading data
data = compile_function(spec, 'data', data, handler)
data = data.sort_values(by=[spec['column']])
rows = spec.get('row-order') or sorted(data[spec['row']].unique().tolist())
columns = spec.get('column-order') or sorted(
data[spec['column']].unique().tolist())
left_margin = (width * spec.get('left-margin', 0.15))
padding = spec.get('style', {}).get('padding', 5)
if not isinstance(padding, (dict, )):
padding = {
'left': padding,
'right': padding,
'top': padding,
'bottom': padding
}
styles = copy.deepcopy(spec.get('style', {}))
if styles.get('gradient'):
_min, _max = data[spec['value']].min(), data[spec['value']].max()
# Compiling style elements if required
for key in [
'gradient', 'color', 'fill', 'font-size', 'font-family', 'stroke'
]:
if isinstance(styles.get(key), (dict, )) and 'function' in styles[key]:
prop = compile_function(styles, key, data, handler)
styles[key] = prop(**{
'data': data,
'handler': handler
}) if callable(prop) else prop
# Calculating cell's width based on config
_width = (width - left_margin) / float(len(columns)) / pixel_inch
_width = spec.get('cell-width', _width) * pixel_inch
# Adding Columns to the HeatGrid.
for idx, column in enumerate(columns):
txt = parent.add_textbox(left + _width * idx + left_margin,
top - height, _width, height)
add_text_to_shape(txt, '{}'.format(column), **styles)
# Cell width
for index, row in enumerate(rows):
_data = data[data[spec['row']] == row].dropna()
_data = pd.merge(pd.DataFrame({spec['column']: list(columns)}),
_data,
left_on=spec['column'],
right_on=spec['column'],
how='left').reset_index(drop=True)
for _idx, _row in _data.iterrows():
style = copy.deepcopy(styles)
# Setting callable padding args
_vars = {
'handler': None,
'row': None,
'column': None,
'value': None
}
args = {
'handler': handler,
'row': row,
'column': _row[spec['column']],
'value': _row[spec['value']]
}
# Setting padding if callable.
_pad = copy.deepcopy(padding)
for key, val in _pad.items():
if isinstance(val, (dict, )) and 'function' in val:
_pad[key] = build_transform(val, vars=_vars)(**args)[0]
top_pad = _pad.get('top', 5) * pixel_inch
left_pad = _pad.get('left', 5) * pixel_inch
right_pad = _pad.get('right', 5) * pixel_inch
bottom_pad = _pad.get('bottom', 5) * pixel_inch
# Adding cells
xaxis = left + (_width * _idx) + left_margin + left_pad
yaxis = top + (height * index) + (top_pad) * index
_rect = rect(parent, xaxis, yaxis, _width - left_pad - right_pad,
height - top_pad)
# Adding color gradient to cell if gradient is True
if style.get('gradient'):
grad_txt = scale_data(_row[spec['value']], _min, _max)
gradient = matplotlib.cm.get_cmap(style['gradient'])
style['fill'] = matplotlib.colors.to_hex(gradient(grad_txt))
style['color'] = _color.contrast(style['fill'])
if np.isnan(_row[spec['value']]) and spec.get('na-color'):
style['fill'] = spec.get('na-color')
style['color'] = _color.contrast(style['fill'])
style['stroke'] = style.get('stroke', style['fill'])
rect_css(_rect, **style)
# Adding text to cells if required.
if spec.get('text'):
_txt = parent.add_textbox(xaxis, yaxis,
_width - left_pad - right_pad,
height - top_pad - bottom_pad)
if isinstance(spec['text'],
dict) and 'function' in spec['text']:
cell_txt = compile_function(spec, 'text', _row, handler)
else:
cell_txt = '{}'.format(_row[spec['value']])
if pd.isnull(cell_txt) and spec.get('na-text'):
cell_txt = spec.get('na-text')
add_text_to_shape(_txt, cell_txt, **style)
# Adding row's text in left side
txt = parent.add_textbox(left,
top + (height * index) + top_pad * index,
_width + left_margin, height)
add_text_to_shape(txt, row, **styles)
def pptgen(source, target=None, **config):
'''
Process a configuration. This loads a Presentation from source, applies the
(optional) configuration changes and saves it into target.
'''
# Config was being over written using PPTXHandler and data key was being
# removed from yaml config.
handler = config.pop('handler', None)
_config = copy.deepcopy(config)
if _config.get('is_formhandler', False):
data = _config.pop('data')
_config.pop('is_formhandler')
else:
data = AttrDict(load_data(_config.pop('data', {}), handler=handler))
# Register a `command` if present in configuration
register(_config)
# Loading input template
prs = Presentation(source)
# Removing not required slides from presentation.
prs = manage_slides(prs, _config)
slides = prs.slides
# Loop through each change configuration
slides_to_remove = []
manage_slide_order = collections.defaultdict(list)
for key, change in _config.items():
# Apply it to every slide
slide_data = copy.deepcopy(data)
if 'data' in change and change['data'] is not None:
if not isinstance(change['data'], (dict,)):
change['data'] = {'function': change.pop('data')}
slide_data = build_transform(change['data'], vars={'data': None})(slide_data)[0]
for index, slide in enumerate(slides):
# Restrict to specific slides, if specified
if not is_slide_allowed(change, slide, index + 1):
continue
if change.get('replicate'):
is_grp = isinstance(slide_data, pd.core.groupby.DataFrameGroupBy)
if isinstance(slide_data, collections.Iterable):
for _slide_data in slide_data:
_slide_data = _slide_data[1] if is_grp is True else _slide_data
replicate_slides(
_slide_data, prs, change, slide, slides_to_remove, index, handler)
# Creating dict mapping to order slides.
manage_slide_order[index + 1].append(len(prs.slides))
else:
raise NotImplementedError()
else:
# Stacking shapes if required.
stack_shapes(slide.shapes, change, slide_data, handler)
change_shapes(slide.shapes, change, slide_data, handler)
indexes = []
slides_to_remove = list(set(slides_to_remove))
for key in sorted(manage_slide_order.keys()):
indexes.append(manage_slide_order[key])
matrix = list(map(list, zip(*indexes)))
for indx_lst in matrix:
for idx in indx_lst:
src = prs.slides[idx - 1]
slides_to_remove.append(idx - 1)
copy_slide = copy.deepcopy(src)
new_slide = generate_slide(prs, copy_slide)
dest = prs.slides.add_slide(new_slide)
for shape in copy_slide.shapes:
copy_slide_elem(shape, dest)
add_new_slide(dest, src)
removed_status = 0
for sld_idx in set(slides_to_remove):
delete_slide(prs, (sld_idx - removed_status))
for slide_num in manage_slide_order:
manage_slide_order[slide_num] = [(i - 1) for i in manage_slide_order[slide_num]]
removed_status += 1
if target is None:
return prs
else:
prs.save(target)
