idx int64 0 251k | question stringlengths 53 3.53k | target stringlengths 5 1.23k | len_question int64 20 893 | len_target int64 3 238 |
|---|---|---|---|---|
237,000 | def _get_table ( name ) : # If name is a variable referencing a table, use that. item = google . datalab . utils . commands . get_notebook_item ( name ) if isinstance ( item , bigquery . Table ) : return item # Else treat this as a BQ table name and return the (cached) table if it exists. try : return _existing_table_cache [ name ] except KeyError : table = bigquery . Table ( name ) if table . exists ( ) : _existing_table_cache [ name ] = table return table return None | Given a variable or table name get a Table if it exists . | 127 | 13 |
237,001 | def _render_list ( data ) : return IPython . core . display . HTML ( google . datalab . utils . commands . HtmlBuilder . render_list ( data ) ) | Helper to render a list of objects as an HTML list object . | 41 | 13 |
237,002 | def _dataset_line ( args ) : if args [ 'command' ] == 'list' : filter_ = args [ 'filter' ] if args [ 'filter' ] else '*' context = google . datalab . Context . default ( ) if args [ 'project' ] : context = google . datalab . Context ( args [ 'project' ] , context . credentials ) return _render_list ( [ str ( dataset ) for dataset in bigquery . Datasets ( context ) if fnmatch . fnmatch ( str ( dataset ) , filter_ ) ] ) elif args [ 'command' ] == 'create' : try : bigquery . Dataset ( args [ 'name' ] ) . create ( friendly_name = args [ 'friendly' ] ) except Exception as e : print ( 'Failed to create dataset %s: %s' % ( args [ 'name' ] , e ) ) elif args [ 'command' ] == 'delete' : try : bigquery . Dataset ( args [ 'name' ] ) . delete ( ) except Exception as e : print ( 'Failed to delete dataset %s: %s' % ( args [ 'name' ] , e ) ) | Implements the BigQuery dataset magic subcommand used to operate on datasets | 263 | 15 |
237,003 | def _table_cell ( args , cell_body ) : if args [ 'command' ] == 'list' : filter_ = args [ 'filter' ] if args [ 'filter' ] else '*' if args [ 'dataset' ] : if args [ 'project' ] is None : datasets = [ bigquery . Dataset ( args [ 'dataset' ] ) ] else : context = google . datalab . Context ( args [ 'project' ] , google . datalab . Context . default ( ) . credentials ) datasets = [ bigquery . Dataset ( args [ 'dataset' ] , context ) ] else : default_context = google . datalab . Context . default ( ) context = google . datalab . Context ( default_context . project_id , default_context . credentials ) if args [ 'project' ] : context . set_project_id ( args [ 'project' ] ) datasets = bigquery . Datasets ( context ) tables = [ ] for dataset in datasets : tables . extend ( [ table . full_name for table in dataset if fnmatch . fnmatch ( table . full_name , filter_ ) ] ) return _render_list ( tables ) elif args [ 'command' ] == 'create' : if cell_body is None : print ( 'Failed to create %s: no schema specified' % args [ 'name' ] ) else : try : record = google . datalab . utils . commands . parse_config ( cell_body , google . datalab . utils . commands . notebook_environment ( ) , as_dict = False ) jsonschema . validate ( record , BigQuerySchema . TABLE_SCHEMA_SCHEMA ) schema = bigquery . Schema ( record [ 'schema' ] ) bigquery . Table ( args [ 'name' ] ) . create ( schema = schema , overwrite = args [ 'overwrite' ] ) except Exception as e : print ( 'Failed to create table %s: %s' % ( args [ 'name' ] , e ) ) elif args [ 'command' ] == 'describe' : name = args [ 'name' ] table = _get_table ( name ) if not table : raise Exception ( 'Could not find table %s' % name ) html = _repr_html_table_schema ( table . schema ) return IPython . core . display . HTML ( html ) elif args [ 'command' ] == 'delete' : try : bigquery . Table ( args [ 'name' ] ) . delete ( ) except Exception as e : print ( 'Failed to delete table %s: %s' % ( args [ 'name' ] , e ) ) elif args [ 'command' ] == 'view' : name = args [ 'name' ] table = _get_table ( name ) if not table : raise Exception ( 'Could not find table %s' % name ) return table | Implements the BigQuery table magic subcommand used to operate on tables | 644 | 15 |
237,004 | def _extract_cell ( args , cell_body ) : env = google . datalab . utils . commands . notebook_environment ( ) config = google . datalab . utils . commands . parse_config ( cell_body , env , False ) or { } parameters = config . get ( 'parameters' ) if args [ 'table' ] : table = google . datalab . bigquery . Query . resolve_parameters ( args [ 'table' ] , parameters ) source = _get_table ( table ) if not source : raise Exception ( 'Could not find table %s' % table ) csv_delimiter = args [ 'delimiter' ] if args [ 'format' ] == 'csv' else None path = google . datalab . bigquery . Query . resolve_parameters ( args [ 'path' ] , parameters ) job = source . extract ( path , format = args [ 'format' ] , csv_delimiter = csv_delimiter , csv_header = args [ 'header' ] , compress = args [ 'compress' ] ) elif args [ 'query' ] or args [ 'view' ] : source_name = args [ 'view' ] or args [ 'query' ] source = google . datalab . utils . commands . get_notebook_item ( source_name ) if not source : raise Exception ( 'Could not find ' + ( 'view ' + args [ 'view' ] if args [ 'view' ] else 'query ' + args [ 'query' ] ) ) query = source if args [ 'query' ] else bigquery . Query . from_view ( source ) query_params = get_query_parameters ( args , cell_body ) if args [ 'query' ] else None output_options = QueryOutput . file ( path = args [ 'path' ] , format = args [ 'format' ] , csv_delimiter = args [ 'delimiter' ] , csv_header = args [ 'header' ] , compress = args [ 'compress' ] , use_cache = not args [ 'nocache' ] ) context = google . datalab . utils . _utils . _construct_context_for_args ( args ) job = query . execute ( output_options , context = context , query_params = query_params ) else : raise Exception ( 'A query, table, or view is needed to extract' ) if job . failed : raise Exception ( 'Extract failed: %s' % str ( job . fatal_error ) ) elif job . errors : raise Exception ( 'Extract completed with errors: %s' % str ( job . errors ) ) return job . result ( ) | Implements the BigQuery extract magic used to extract query or table data to GCS . | 594 | 19 |
237,005 | def bq ( line , cell = None ) : return google . datalab . utils . commands . handle_magic_line ( line , cell , _bigquery_parser ) | Implements the bq cell magic for ipython notebooks . | 39 | 13 |
237,006 | def _build_js ( inputs , outputs , name , implementation , support_code ) : # Construct a comma-separated list of input field names # For example, field1,field2,... input_fields = json . dumps ( [ f [ 0 ] for f in inputs ] ) # Construct a json representation of the output schema # For example, [{'name':'field1','type':'string'},...] output_fields = [ { 'name' : f [ 0 ] , 'type' : f [ 1 ] } for f in outputs ] output_fields = json . dumps ( output_fields , sort_keys = True ) # Build the JS from the individual bits with proper escaping of the implementation if support_code is None : support_code = '' return ( '{code}\n{name}={implementation};\nbigquery.defineFunction(\'{name}\', {inputs}, ' '{outputs}, {name});' ) . format ( code = support_code , name = name , implementation = implementation , inputs = str ( input_fields ) , outputs = str ( output_fields ) ) | Creates a BigQuery SQL UDF javascript object . | 239 | 11 |
237,007 | def sampling_query ( sql , fields = None , count = 5 , sampling = None ) : if sampling is None : sampling = Sampling . default ( count = count , fields = fields ) return sampling ( sql ) | Returns a sampling query for the SQL object . | 45 | 9 |
237,008 | def _remove_nonascii ( self , df ) : df_copy = df . copy ( deep = True ) for col in df_copy . columns : if ( df_copy [ col ] . dtype == np . dtype ( 'O' ) ) : df_copy [ col ] = df [ col ] . apply ( lambda x : re . sub ( r'[^\x00-\x7f]' , r'' , x ) if isinstance ( x , six . string_types ) else x ) return df_copy | Make copy and remove non - ascii characters from it . | 117 | 13 |
237,009 | def plot ( self , data ) : import IPython if not isinstance ( data , dict ) or not all ( isinstance ( v , pd . DataFrame ) for v in data . values ( ) ) : raise ValueError ( 'Expect a dictionary where the values are all dataframes.' ) gfsg = GenericFeatureStatisticsGenerator ( ) data = [ { 'name' : k , 'table' : self . _remove_nonascii ( v ) } for k , v in six . iteritems ( data ) ] data_proto = gfsg . ProtoFromDataFrames ( data ) protostr = base64 . b64encode ( data_proto . SerializeToString ( ) ) . decode ( "utf-8" ) html_id = 'f' + datalab . utils . commands . Html . next_id ( ) HTML_TEMPLATE = """<link rel="import" href="/nbextensions/gcpdatalab/extern/facets-jupyter.html" > <facets-overview id="{html_id}"></facets-overview> <script> document.querySelector("#{html_id}").protoInput = "{protostr}"; </script>""" html = HTML_TEMPLATE . format ( html_id = html_id , protostr = protostr ) return IPython . core . display . HTML ( html ) | Plots an overview in a list of dataframes | 318 | 10 |
237,010 | def plot ( self , data , height = 1000 , render_large_data = False ) : import IPython if not isinstance ( data , pd . DataFrame ) : raise ValueError ( 'Expect a DataFrame.' ) if ( len ( data ) > 10000 and not render_large_data ) : raise ValueError ( 'Facets dive may not work well with more than 10000 rows. ' + 'Reduce data or set "render_large_data" to True.' ) jsonstr = data . to_json ( orient = 'records' ) html_id = 'f' + datalab . utils . commands . Html . next_id ( ) HTML_TEMPLATE = """ <link rel="import" href="/nbextensions/gcpdatalab/extern/facets-jupyter.html"> <facets-dive id="{html_id}" height="{height}"></facets-dive> <script> var data = {jsonstr}; document.querySelector("#{html_id}").data = data; </script>""" html = HTML_TEMPLATE . format ( html_id = html_id , jsonstr = jsonstr , height = height ) return IPython . core . display . HTML ( html ) | Plots a detail view of data . | 281 | 8 |
237,011 | def DtypeToType ( self , dtype ) : if dtype . char in np . typecodes [ 'AllFloat' ] : return self . fs_proto . FLOAT elif ( dtype . char in np . typecodes [ 'AllInteger' ] or dtype == np . bool or np . issubdtype ( dtype , np . datetime64 ) or np . issubdtype ( dtype , np . timedelta64 ) ) : return self . fs_proto . INT else : return self . fs_proto . STRING | Converts a Numpy dtype to the FeatureNameStatistics . Type proto enum . | 122 | 17 |
237,012 | def NdarrayToEntry ( self , x ) : row_counts = [ ] for row in x : try : rc = np . count_nonzero ( ~ np . isnan ( row ) ) if rc != 0 : row_counts . append ( rc ) except TypeError : try : row_counts . append ( row . size ) except AttributeError : row_counts . append ( 1 ) data_type = self . DtypeToType ( x . dtype ) converter = self . DtypeToNumberConverter ( x . dtype ) flattened = x . ravel ( ) orig_size = len ( flattened ) # Remove all None and nan values and count how many were removed. flattened = flattened [ flattened != np . array ( None ) ] if converter : flattened = converter ( flattened ) if data_type == self . fs_proto . STRING : flattened_temp = [ ] for x in flattened : try : if str ( x ) != 'nan' : flattened_temp . append ( x ) except UnicodeEncodeError : if x . encode ( 'utf-8' ) != 'nan' : flattened_temp . append ( x ) flattened = flattened_temp else : flattened = flattened [ ~ np . isnan ( flattened ) ] . tolist ( ) missing = orig_size - len ( flattened ) return { 'vals' : flattened , 'counts' : row_counts , 'missing' : missing , 'type' : data_type } | Converts an ndarray to the Entry format . | 317 | 11 |
237,013 | def serving_from_csv_input ( train_config , args , keep_target ) : examples = tf . placeholder ( dtype = tf . string , shape = ( None , ) , name = 'csv_input_string' ) features = parse_example_tensor ( examples = examples , train_config = train_config , keep_target = keep_target ) if keep_target : target = features . pop ( train_config [ 'target_column' ] ) else : target = None features , target = preprocess_input ( features = features , target = target , train_config = train_config , preprocess_output_dir = args . preprocess_output_dir , model_type = args . model_type ) return input_fn_utils . InputFnOps ( features , target , { 'csv_line' : examples } ) | Read the input features from a placeholder csv string tensor . | 183 | 13 |
237,014 | def parse_example_tensor ( examples , train_config , keep_target ) : csv_header = [ ] if keep_target : csv_header = train_config [ 'csv_header' ] else : csv_header = [ name for name in train_config [ 'csv_header' ] if name != train_config [ 'target_column' ] ] # record_defaults are used by tf.decode_csv to insert defaults, and to infer # the datatype. record_defaults = [ [ train_config [ 'csv_defaults' ] [ name ] ] for name in csv_header ] tensors = tf . decode_csv ( examples , record_defaults , name = 'csv_to_tensors' ) # I'm not really sure why expand_dims needs to be called. If using regression # models, it errors without it. tensors = [ tf . expand_dims ( x , axis = 1 ) for x in tensors ] tensor_dict = dict ( zip ( csv_header , tensors ) ) return tensor_dict | Read the csv files . | 240 | 6 |
237,015 | def get_estimator ( output_dir , train_config , args ) : # Check the requested mode fits the preprocessed data. target_name = train_config [ 'target_column' ] if is_classification_model ( args . model_type ) and target_name not in train_config [ 'categorical_columns' ] : raise ValueError ( 'When using a classification model, the target must be a ' 'categorical variable.' ) if is_regression_model ( args . model_type ) and target_name not in train_config [ 'numerical_columns' ] : raise ValueError ( 'When using a regression model, the target must be a ' 'numerical variable.' ) # Check layers used for dnn models. if is_dnn_model ( args . model_type ) and not args . layer_sizes : raise ValueError ( '--layer-size* must be used with DNN models' ) if is_linear_model ( args . model_type ) and args . layer_sizes : raise ValueError ( '--layer-size* cannot be used with linear models' ) # Build tf.learn features feature_columns = _tflearn_features ( train_config , args ) # Set how often to run checkpointing in terms of time. config = tf . contrib . learn . RunConfig ( save_checkpoints_secs = args . save_checkpoints_secs ) train_dir = os . path . join ( output_dir , 'train' ) if args . model_type == 'dnn_regression' : estimator = tf . contrib . learn . DNNRegressor ( feature_columns = feature_columns , hidden_units = args . layer_sizes , config = config , model_dir = train_dir , optimizer = tf . train . AdamOptimizer ( args . learning_rate , epsilon = args . epsilon ) ) elif args . model_type == 'linear_regression' : estimator = tf . contrib . learn . LinearRegressor ( feature_columns = feature_columns , config = config , model_dir = train_dir , optimizer = tf . train . AdamOptimizer ( args . learning_rate , epsilon = args . epsilon ) ) elif args . model_type == 'dnn_classification' : estimator = tf . contrib . learn . DNNClassifier ( feature_columns = feature_columns , hidden_units = args . layer_sizes , n_classes = train_config [ 'vocab_stats' ] [ target_name ] [ 'n_classes' ] , config = config , model_dir = train_dir , optimizer = tf . train . AdamOptimizer ( args . learning_rate , epsilon = args . epsilon ) ) elif args . model_type == 'linear_classification' : estimator = tf . contrib . learn . LinearClassifier ( feature_columns = feature_columns , n_classes = train_config [ 'vocab_stats' ] [ target_name ] [ 'n_classes' ] , config = config , model_dir = train_dir , optimizer = tf . train . AdamOptimizer ( args . learning_rate , epsilon = args . epsilon ) ) else : raise ValueError ( 'bad --model-type value' ) return estimator | Returns a tf learn estimator . | 753 | 7 |
237,016 | def _scale_tensor ( tensor , range_min , range_max , scale_min , scale_max ) : if range_min == range_max : return tensor float_tensor = tf . to_float ( tensor ) scaled_tensor = tf . divide ( ( tf . subtract ( float_tensor , range_min ) * tf . constant ( float ( scale_max - scale_min ) ) ) , tf . constant ( float ( range_max - range_min ) ) ) shifted_tensor = scaled_tensor + tf . constant ( float ( scale_min ) ) return shifted_tensor | Scale a tensor to scale_min to scale_max . | 136 | 13 |
237,017 | def _tflearn_features ( train_config , args ) : feature_columns = [ ] target_name = train_config [ 'target_column' ] key_name = train_config [ 'key_column' ] for name in train_config [ 'numerical_columns' ] : if name != target_name and name != key_name : feature_columns . append ( tf . contrib . layers . real_valued_column ( name , dimension = 1 ) ) # Supported transforms: # for DNN # 1) string -> make int -> embedding (embedding) # 2) string -> make int -> one_hot (one_hot, default) # for linear # 1) string -> sparse_column_with_hash_bucket (embedding) # 2) string -> make int -> sparse_column_with_integerized_feature (one_hot, default) # It is unfortunate that tf.layers has different feature transforms if the # model is linear or DNN. This pacakge should not expose to the user that # we are using tf.layers. It is crazy that DNN models support more feature # types (like string -> hash sparse column -> embedding) for name in train_config [ 'categorical_columns' ] : if name != target_name and name != key_name : transform_config = train_config [ 'transforms' ] . get ( name , { } ) transform_name = transform_config . get ( 'transform' , None ) if is_dnn_model ( args . model_type ) : if transform_name == 'embedding' : sparse = tf . contrib . layers . sparse_column_with_integerized_feature ( name , bucket_size = train_config [ 'vocab_stats' ] [ name ] [ 'n_classes' ] ) learn_feature = tf . contrib . layers . embedding_column ( sparse , dimension = transform_config [ 'embedding_dim' ] ) elif transform_name == 'one_hot' or transform_name is None : sparse = tf . contrib . layers . sparse_column_with_integerized_feature ( name , bucket_size = train_config [ 'vocab_stats' ] [ name ] [ 'n_classes' ] ) learn_feature = tf . contrib . layers . one_hot_column ( sparse ) else : raise ValueError ( ( 'Unknown transform name. Only \'embedding\' ' 'and \'one_hot\' transforms are supported. Got %s' ) % transform_name ) elif is_linear_model ( args . model_type ) : if transform_name == 'one_hot' or transform_name is None : learn_feature = tf . contrib . layers . sparse_column_with_integerized_feature ( name , bucket_size = train_config [ 'vocab_stats' ] [ name ] [ 'n_classes' ] ) elif transform_name == 'embedding' : learn_feature = tf . contrib . layers . sparse_column_with_hash_bucket ( name , hash_bucket_size = transform_config [ 'embedding_dim' ] ) else : raise ValueError ( ( 'Unknown transform name. Only \'embedding\' ' 'and \'one_hot\' transforms are supported. Got %s' ) % transform_name ) # Save the feature feature_columns . append ( learn_feature ) return feature_columns | Builds the tf . learn feature list . | 750 | 9 |
237,018 | def get_vocabulary ( preprocess_output_dir , name ) : vocab_file = os . path . join ( preprocess_output_dir , CATEGORICAL_ANALYSIS % name ) if not file_io . file_exists ( vocab_file ) : raise ValueError ( 'File %s not found in %s' % ( CATEGORICAL_ANALYSIS % name , preprocess_output_dir ) ) labels = python_portable_string ( file_io . read_file_to_string ( vocab_file ) ) . split ( '\n' ) label_values = [ x for x in labels if x ] # remove empty lines return label_values | Loads the vocabulary file as a list of strings . | 157 | 11 |
237,019 | def validate_metadata ( train_config ) : # Make sure we have a default for every column if len ( train_config [ 'csv_header' ] ) != len ( train_config [ 'csv_defaults' ] ) : raise ValueError ( 'Unequal number of columns in input features file and ' 'schema file.' ) # Check there are no missing columns. sorted_colums has two copies of the # target column because the target column is also listed in # categorical_columns or numerical_columns. sorted_columns = sorted ( train_config [ 'csv_header' ] + [ train_config [ 'target_column' ] ] ) sorted_columns2 = sorted ( train_config [ 'categorical_columns' ] + train_config [ 'numerical_columns' ] + [ train_config [ 'key_column' ] ] + [ train_config [ 'target_column' ] ] ) if sorted_columns2 != sorted_columns : raise ValueError ( 'Each csv header must be a numerical/categorical type, a ' ' key, or a target.' ) | Perform some checks that the trainig config is correct . | 247 | 12 |
237,020 | def get_default_id ( credentials = None ) : project_id = _utils . get_project_id ( ) if project_id is None : projects , _ = Projects ( credentials ) . _retrieve_projects ( None , 2 ) if len ( projects ) == 1 : project_id = projects [ 0 ] . id return project_id | Get default project id . | 74 | 5 |
237,021 | def init_app ( state ) : app = state . app app . config . setdefault ( 'SPLIT_ALLOW_MULTIPLE_EXPERIMENTS' , False ) app . config . setdefault ( 'SPLIT_DB_FAILOVER' , False ) app . config . setdefault ( 'SPLIT_IGNORE_IP_ADDRESSES' , [ ] ) app . config . setdefault ( 'SPLIT_ROBOT_REGEX' , r""" (?i)\b( Baidu| Gigabot| Googlebot| libwww-perl| lwp-trivial| msnbot| SiteUptime| Slurp| WordPress| ZIBB| ZyBorg )\b """ ) app . jinja_env . globals . update ( { 'ab_test' : ab_test , 'finished' : finished } ) @ app . template_filter ( ) def percentage ( number ) : number *= 100 if abs ( number ) < 10 : return "%.1f%%" % round ( number , 1 ) else : return "%d%%" % round ( number ) | Prepare the Flask application for Flask - Split . | 250 | 10 |
237,022 | def finished ( experiment_name , reset = True ) : if _exclude_visitor ( ) : return redis = _get_redis_connection ( ) try : experiment = Experiment . find ( redis , experiment_name ) if not experiment : return alternative_name = _get_session ( ) . get ( experiment . key ) if alternative_name : split_finished = set ( session . get ( 'split_finished' , [ ] ) ) if experiment . key not in split_finished : alternative = Alternative ( redis , alternative_name , experiment_name ) alternative . increment_completion ( ) if reset : _get_session ( ) . pop ( experiment . key , None ) try : split_finished . remove ( experiment . key ) except KeyError : pass else : split_finished . add ( experiment . key ) session [ 'split_finished' ] = list ( split_finished ) except ConnectionError : if not current_app . config [ 'SPLIT_DB_FAILOVER' ] : raise | Track a conversion . | 218 | 4 |
237,023 | def _is_robot ( ) : robot_regex = current_app . config [ 'SPLIT_ROBOT_REGEX' ] user_agent = request . headers . get ( 'User-Agent' , '' ) return re . search ( robot_regex , user_agent , flags = re . VERBOSE ) | Return True if the current visitor is a robot or spider or False otherwise . | 73 | 15 |
237,024 | def start_time ( self ) : t = self . redis . hget ( 'experiment_start_times' , self . name ) if t : return datetime . strptime ( t , '%Y-%m-%dT%H:%M:%S' ) | The start time of this experiment . | 64 | 7 |
237,025 | def reset ( self ) : for alternative in self . alternatives : alternative . reset ( ) self . reset_winner ( ) self . increment_version ( ) | Delete all data for this experiment . | 32 | 7 |
237,026 | def delete ( self ) : for alternative in self . alternatives : alternative . delete ( ) self . reset_winner ( ) self . redis . srem ( 'experiments' , self . name ) self . redis . delete ( self . name ) self . increment_version ( ) | Delete this experiment and all its data . | 60 | 8 |
237,027 | def _get_redis_connection ( ) : url = current_app . config . get ( 'REDIS_URL' , 'redis://localhost:6379' ) return redis . from_url ( url , decode_responses = True ) | Return a Redis connection based on the Flask application s configuration . | 55 | 13 |
237,028 | def set_experiment_winner ( experiment ) : redis = _get_redis_connection ( ) experiment = Experiment . find ( redis , experiment ) if experiment : alternative_name = request . form . get ( 'alternative' ) alternative = Alternative ( redis , alternative_name , experiment . name ) if alternative . name in experiment . alternative_names : experiment . winner = alternative . name return redirect ( url_for ( '.index' ) ) | Mark an alternative as the winner of the experiment . | 97 | 10 |
237,029 | def reset_experiment ( experiment ) : redis = _get_redis_connection ( ) experiment = Experiment . find ( redis , experiment ) if experiment : experiment . reset ( ) return redirect ( url_for ( '.index' ) ) | Delete all data for an experiment . | 52 | 7 |
237,030 | def delete_experiment ( experiment ) : redis = _get_redis_connection ( ) experiment = Experiment . find ( redis , experiment ) if experiment : experiment . delete ( ) return redirect ( url_for ( '.index' ) ) | Delete an experiment and all its data . | 52 | 8 |
237,031 | def _get_ipaddress ( node ) : if "ipaddress" not in node : with settings ( hide ( 'stdout' ) , warn_only = True ) : output = sudo ( 'ohai -l warn ipaddress' ) if output . succeeded : try : node [ 'ipaddress' ] = json . loads ( output ) [ 0 ] except ValueError : abort ( "Could not parse ohai's output for ipaddress" ":\n {0}" . format ( output ) ) return True return False | Adds the ipaddress attribute to the given node object if not already present and it is correctly given by ohai Returns True if ipaddress is added False otherwise | 109 | 31 |
237,032 | def sync_node ( node ) : if node . get ( 'dummy' ) or 'dummy' in node . get ( 'tags' , [ ] ) : lib . print_header ( "Skipping dummy: {0}" . format ( env . host ) ) return False current_node = lib . get_node ( node [ 'name' ] ) # Always configure Chef Solo solo . configure ( current_node ) ipaddress = _get_ipaddress ( node ) # Everything was configured alright, so save the node configuration # This is done without credentials, so that we keep the node name used # by the user and not the hostname or IP translated by .ssh/config filepath = save_config ( node , ipaddress ) try : # Synchronize the kitchen directory _synchronize_node ( filepath , node ) # Execute Chef Solo _configure_node ( ) finally : _node_cleanup ( ) return True | Builds synchronizes and configures a node . It also injects the ipaddress to the node s config file if not already existent . | 201 | 29 |
237,033 | def build_dct ( dic , keys , value ) : key = keys . pop ( 0 ) if len ( keys ) : dic . setdefault ( key , { } ) build_dct ( dic [ key ] , keys , value ) else : # Transform cookbook default attribute strings into proper booleans if value == "false" : value = False elif value == "true" : value = True # It's a leaf, assign value dic [ key ] = deepcopy ( value ) | Builds a dictionary with arbitrary depth out of a key list | 108 | 12 |
237,034 | def update_dct ( dic1 , dic2 ) : for key , val in dic2 . items ( ) : if isinstance ( val , dict ) : dic1 . setdefault ( key , { } ) update_dct ( dic1 [ key ] , val ) else : dic1 [ key ] = val | Merges two dictionaries recursively dic2 will have preference over dic1 | 73 | 18 |
237,035 | def _add_merged_attributes ( node , all_recipes , all_roles ) : # Get cookbooks from extended recipes attributes = { } for recipe in node [ 'recipes' ] : # Find this recipe found = False for r in all_recipes : if recipe == r [ 'name' ] : found = True for attr in r [ 'attributes' ] : if r [ 'attributes' ] [ attr ] . get ( 'type' ) == "hash" : value = { } else : value = r [ 'attributes' ] [ attr ] . get ( 'default' ) # Attribute dictionaries are defined as a single # compound key. Split and build proper dict build_dct ( attributes , attr . split ( "/" ) , value ) if not found : error = "Could not find recipe '{0}' while " . format ( recipe ) error += "building node data bag for '{0}'" . format ( node [ 'name' ] ) abort ( error ) # Get default role attributes for role in node [ 'roles' ] : for r in all_roles : if role == r [ 'name' ] : update_dct ( attributes , r . get ( 'default_attributes' , { } ) ) # Get default environment attributes environment = lib . get_environment ( node [ 'chef_environment' ] ) update_dct ( attributes , environment . get ( 'default_attributes' , { } ) ) # Get normal node attributes non_attribute_fields = [ 'id' , 'name' , 'role' , 'roles' , 'recipes' , 'run_list' , 'ipaddress' ] node_attributes = { } for key in node : if key in non_attribute_fields : continue node_attributes [ key ] = node [ key ] update_dct ( attributes , node_attributes ) # Get override role attributes for role in node [ 'roles' ] : for r in all_roles : if role == r [ 'name' ] : update_dct ( attributes , r . get ( 'override_attributes' , { } ) ) # Get override environment attributes update_dct ( attributes , environment . get ( 'override_attributes' , { } ) ) # Merge back to the original node object node . update ( attributes ) | Merges attributes from cookbooks node and roles | 513 | 9 |
237,036 | def build_node_data_bag ( ) : nodes = lib . get_nodes ( ) node_data_bag_path = os . path . join ( 'data_bags' , 'node' ) # In case there are leftovers remove_local_node_data_bag ( ) os . makedirs ( node_data_bag_path ) all_recipes = lib . get_recipes ( ) all_roles = lib . get_roles ( ) for node in nodes : # Dots are not allowed (only alphanumeric), substitute by underscores node [ 'id' ] = node [ 'name' ] . replace ( '.' , '_' ) # Build extended role list node [ 'role' ] = lib . get_roles_in_node ( node ) node [ 'roles' ] = node [ 'role' ] [ : ] for role in node [ 'role' ] : node [ 'roles' ] . extend ( lib . get_roles_in_role ( role ) ) node [ 'roles' ] = list ( set ( node [ 'roles' ] ) ) # Build extended recipe list node [ 'recipes' ] = lib . get_recipes_in_node ( node ) # Add recipes found inside each roles in the extended role list for role in node [ 'roles' ] : node [ 'recipes' ] . extend ( lib . get_recipes_in_role ( role ) ) node [ 'recipes' ] = list ( set ( node [ 'recipes' ] ) ) # Add node attributes _add_merged_attributes ( node , all_recipes , all_roles ) _add_automatic_attributes ( node ) # Save node data bag item with open ( os . path . join ( 'data_bags' , 'node' , node [ 'id' ] + '.json' ) , 'w' ) as f : f . write ( json . dumps ( node ) ) | Builds one node data bag item per file found in the nodes directory | 427 | 14 |
237,037 | def remove_local_node_data_bag ( ) : node_data_bag_path = os . path . join ( 'data_bags' , 'node' ) if os . path . exists ( node_data_bag_path ) : shutil . rmtree ( node_data_bag_path ) | Removes generated node data_bag locally | 68 | 8 |
237,038 | def ensure_berksfile_cookbooks_are_installed ( ) : msg = "Vendoring cookbooks from Berksfile {0} to directory {1}..." print ( msg . format ( env . berksfile , env . berksfile_cookbooks_directory ) ) run_vendor = True cookbooks_dir = env . berksfile_cookbooks_directory berksfile_lock_path = cookbooks_dir + '/Berksfile.lock' berksfile_lock_exists = os . path . isfile ( berksfile_lock_path ) cookbooks_dir_exists = os . path . isdir ( cookbooks_dir ) if cookbooks_dir_exists and berksfile_lock_exists : berksfile_mtime = os . stat ( 'Berksfile' ) . st_mtime cookbooks_mtime = os . stat ( berksfile_lock_path ) . st_mtime run_vendor = berksfile_mtime > cookbooks_mtime if run_vendor : if cookbooks_dir_exists : shutil . rmtree ( env . berksfile_cookbooks_directory ) p = subprocess . Popen ( [ 'berks' , 'vendor' , env . berksfile_cookbooks_directory ] , stdout = subprocess . PIPE , stderr = subprocess . PIPE ) stdout , stderr = p . communicate ( ) if env . verbose or p . returncode : print stdout , stderr | Run berks vendor to berksfile cookbooks directory | 340 | 11 |
237,039 | def _remove_remote_node_data_bag ( ) : node_data_bag_path = os . path . join ( env . node_work_path , 'data_bags' , 'node' ) if exists ( node_data_bag_path ) : sudo ( "rm -rf {0}" . format ( node_data_bag_path ) ) | Removes generated node data_bag from the remote node | 79 | 11 |
237,040 | def _remove_remote_data_bags ( ) : data_bags_path = os . path . join ( env . node_work_path , 'data_bags' ) if exists ( data_bags_path ) : sudo ( "rm -rf {0}" . format ( data_bags_path ) ) | Remove remote data bags so it won t leak any sensitive information | 67 | 12 |
237,041 | def _configure_node ( ) : print ( "" ) msg = "Cooking..." if env . parallel : msg = "[{0}]: {1}" . format ( env . host_string , msg ) print ( msg ) # Backup last report with settings ( hide ( 'stdout' , 'warnings' , 'running' ) , warn_only = True ) : sudo ( "mv {0} {0}.1" . format ( LOGFILE ) ) # Build chef-solo command cmd = "RUBYOPT=-Ku chef-solo" if whyrun : cmd += " --why-run" cmd += ' -l {0} -j /etc/chef/node.json' . format ( env . loglevel ) if ENABLE_LOGS : cmd += ' | tee {0}' . format ( LOGFILE ) if env . loglevel == "debug" : print ( "Executing Chef Solo with the following command:\n" "{0}" . format ( cmd ) ) with settings ( hide ( 'warnings' , 'running' ) , warn_only = True ) : output = sudo ( cmd ) if ( output . failed or "FATAL: Stacktrace dumped" in output or ( "Chef Run complete" not in output and "Report handlers complete" not in output ) ) : if 'chef-solo: command not found' in output : print ( colors . red ( "\nFAILED: Chef Solo is not installed on this node" ) ) print ( "Type 'fix node:{0} deploy_chef' to install it" . format ( env . host ) ) abort ( "" ) else : print ( colors . red ( "\nFAILED: chef-solo could not finish configuring the node\n" ) ) import sys sys . exit ( 1 ) else : msg = "\n" if env . parallel : msg += "[{0}]: " . format ( env . host_string ) msg += "SUCCESS: Node correctly configured" print ( colors . green ( msg ) ) | Exectutes chef - solo to apply roles and recipes to a node | 444 | 14 |
237,042 | def _resolve_hostname ( name ) : if env . ssh_config is None : return name elif not os . path . exists ( os . path . join ( "nodes" , name + ".json" ) ) : resolved_name = env . ssh_config . lookup ( name ) [ 'hostname' ] if os . path . exists ( os . path . join ( "nodes" , resolved_name + ".json" ) ) : name = resolved_name return name | Returns resolved hostname using the ssh config | 105 | 8 |
237,043 | def get_environment ( name ) : if name == "_default" : return env_from_template ( name ) filename = os . path . join ( "environments" , name + ".json" ) try : with open ( filename ) as f : try : return json . loads ( f . read ( ) ) except ValueError as e : msg = 'LittleChef found the following error in' msg += ' "{0}":\n {1}' . format ( filename , str ( e ) ) abort ( msg ) except IOError : raise FileNotFoundError ( 'File {0} not found' . format ( filename ) ) | Returns a JSON environment file as a dictionary | 135 | 8 |
237,044 | def get_environments ( ) : envs = [ ] for root , subfolders , files in os . walk ( 'environments' ) : for filename in files : if filename . endswith ( ".json" ) : path = os . path . join ( root [ len ( 'environments' ) : ] , filename [ : - len ( '.json' ) ] ) envs . append ( get_environment ( path ) ) return sorted ( envs , key = lambda x : x [ 'name' ] ) | Gets all environments found in the environments directory | 111 | 9 |
237,045 | def get_node ( name , merged = False ) : if merged : node_path = os . path . join ( "data_bags" , "node" , name . replace ( '.' , '_' ) + ".json" ) else : node_path = os . path . join ( "nodes" , name + ".json" ) if os . path . exists ( node_path ) : # Read node.json with open ( node_path , 'r' ) as f : try : node = json . loads ( f . read ( ) ) except ValueError as e : msg = 'LittleChef found the following error in' msg += ' "{0}":\n {1}' . format ( node_path , str ( e ) ) abort ( msg ) else : print "Creating new node file '{0}.json'" . format ( name ) node = { 'run_list' : [ ] } # Add node name so that we can tell to which node it is node [ 'name' ] = name if not node . get ( 'chef_environment' ) : node [ 'chef_environment' ] = '_default' return node | Returns a JSON node file as a dictionary | 249 | 8 |
237,046 | def get_nodes_with_role ( role_name , environment = None ) : prefix_search = role_name . endswith ( "*" ) if prefix_search : role_name = role_name . rstrip ( "*" ) for n in get_nodes ( environment ) : roles = get_roles_in_node ( n , recursive = True ) if prefix_search : if any ( role . startswith ( role_name ) for role in roles ) : yield n else : if role_name in roles : yield n | Get all nodes which include a given role prefix - searches are also supported | 120 | 14 |
237,047 | def get_nodes_with_tag ( tag , environment = None , include_guests = False ) : nodes = get_nodes ( environment ) nodes_mapping = dict ( ( n [ 'name' ] , n ) for n in nodes ) for n in nodes : if tag in n . get ( 'tags' , [ ] ) : # Remove from node mapping so it doesn't get added twice by # guest walking below try : del nodes_mapping [ n [ 'fqdn' ] ] except KeyError : pass yield n # Walk guest if it is a host if include_guests and n . get ( 'virtualization' , { } ) . get ( 'role' ) == 'host' : for guest in n [ 'virtualization' ] . get ( 'guests' , [ ] ) : try : yield nodes_mapping [ guest [ 'fqdn' ] ] except KeyError : # we ignore guests which are not in the same # chef environments than their hosts for now pass | Get all nodes which include a given tag | 216 | 8 |
237,048 | def get_nodes_with_recipe ( recipe_name , environment = None ) : prefix_search = recipe_name . endswith ( "*" ) if prefix_search : recipe_name = recipe_name . rstrip ( "*" ) for n in get_nodes ( environment ) : recipes = get_recipes_in_node ( n ) for role in get_roles_in_node ( n , recursive = True ) : recipes . extend ( get_recipes_in_role ( role ) ) if prefix_search : if any ( recipe . startswith ( recipe_name ) for recipe in recipes ) : yield n else : if recipe_name in recipes : yield n | Get all nodes which include a given recipe prefix - searches are also supported | 152 | 14 |
237,049 | def print_node ( node , detailed = False ) : nodename = node [ 'name' ] print ( colors . yellow ( "\n" + nodename ) ) # Roles if detailed : for role in get_roles_in_node ( node ) : print_role ( _get_role ( role ) , detailed = False ) else : print ( ' Roles: {0}' . format ( ", " . join ( get_roles_in_node ( node ) ) ) ) # Recipes if detailed : for recipe in get_recipes_in_node ( node ) : print " Recipe:" , recipe print " attributes: {0}" . format ( node . get ( recipe , "" ) ) else : print ( ' Recipes: {0}' . format ( ", " . join ( get_recipes_in_node ( node ) ) ) ) # Node attributes print " Node attributes:" for attribute in node . keys ( ) : if attribute == "run_list" or attribute == "name" : continue print " {0}: {1}" . format ( attribute , node [ attribute ] ) | Pretty prints the given node | 235 | 5 |
237,050 | def print_nodes ( nodes , detailed = False ) : found = 0 for node in nodes : found += 1 print_node ( node , detailed = detailed ) print ( "\nFound {0} node{1}" . format ( found , "s" if found != 1 else "" ) ) | Prints all the given nodes | 62 | 6 |
237,051 | def _generate_metadata ( path , cookbook_path , name ) : global knife_installed if not knife_installed : return metadata_path_rb = os . path . join ( path , 'metadata.rb' ) metadata_path_json = os . path . join ( path , 'metadata.json' ) if ( os . path . exists ( metadata_path_rb ) and ( not os . path . exists ( metadata_path_json ) or os . stat ( metadata_path_rb ) . st_mtime > os . stat ( metadata_path_json ) . st_mtime ) ) : error_msg = "Warning: metadata.json for {0}" . format ( name ) error_msg += " in {0} is older that metadata.rb" . format ( cookbook_path ) error_msg += ", cookbook attributes could be out of date\n\n" try : proc = subprocess . Popen ( [ 'knife' , 'cookbook' , 'metadata' , '-o' , cookbook_path , name ] , stdout = subprocess . PIPE , stderr = subprocess . PIPE ) resp , error = proc . communicate ( ) if ( 'ERROR:' in resp or 'FATAL:' in resp or 'Generating metadata for' not in resp ) : if ( "No user specified, pass via -u or specifiy 'node_name'" in error ) : error_msg += "You need to have an up-to-date (>=0.10.x)" error_msg += " version of knife installed locally in order" error_msg += " to generate metadata.json.\nError " else : error_msg += "Unkown error " error_msg += "while executing knife to generate " error_msg += "metadata.json for {0}" . format ( path ) print ( error_msg ) print resp if env . loglevel == 'debug' : print "\n" . join ( resp . split ( "\n" ) [ : 2 ] ) except OSError : knife_installed = False error_msg += "If you locally install Chef's knife tool, LittleChef" error_msg += " will regenerate metadata.json files automatically\n" print ( error_msg ) else : print ( "Generated metadata.json for {0}\n" . format ( path ) ) | Checks whether metadata . rb has changed and regenerate metadata . json | 513 | 14 |
237,052 | def get_recipes_in_cookbook ( name ) : recipes = { } path = None cookbook_exists = False metadata_exists = False for cookbook_path in cookbook_paths : path = os . path . join ( cookbook_path , name ) path_exists = os . path . exists ( path ) # cookbook exists if present in any of the cookbook paths cookbook_exists = cookbook_exists or path_exists if not path_exists : continue _generate_metadata ( path , cookbook_path , name ) # Now try to open metadata.json try : with open ( os . path . join ( path , 'metadata.json' ) , 'r' ) as f : try : cookbook = json . loads ( f . read ( ) ) except ValueError as e : msg = "Little Chef found the following error in your" msg += " {0} file:\n {1}" . format ( os . path . join ( path , 'metadata.json' ) , e ) abort ( msg ) # Add each recipe defined in the cookbook metadata_exists = True recipe_defaults = { 'description' : '' , 'version' : cookbook . get ( 'version' ) , 'dependencies' : cookbook . get ( 'dependencies' , { } ) . keys ( ) , 'attributes' : cookbook . get ( 'attributes' , { } ) } for recipe in cookbook . get ( 'recipes' , [ ] ) : recipes [ recipe ] = dict ( recipe_defaults , name = recipe , description = cookbook [ 'recipes' ] [ recipe ] ) # Cookbook metadata.json was found, don't try next cookbook path # because metadata.json in site-cookbooks has preference break except IOError : # metadata.json was not found, try next cookbook_path pass if not cookbook_exists : abort ( 'Unable to find cookbook "{0}"' . format ( name ) ) elif not metadata_exists : abort ( 'Cookbook "{0}" has no metadata.json' . format ( name ) ) # Add recipes found in the 'recipes' directory but not listed # in the metadata for cookbook_path in cookbook_paths : recipes_dir = os . path . join ( cookbook_path , name , 'recipes' ) if not os . path . isdir ( recipes_dir ) : continue for basename in os . listdir ( recipes_dir ) : fname , ext = os . path . splitext ( basename ) if ext != '.rb' : continue if fname != 'default' : recipe = '%s::%s' % ( name , fname ) else : recipe = name if recipe not in recipes : recipes [ recipe ] = dict ( recipe_defaults , name = recipe ) # When a recipe has no default recipe (libraries?), # add one so that it is listed if not recipes : recipes [ name ] = dict ( recipe_defaults , name = name , description = 'This cookbook has no default recipe' ) return recipes . values ( ) | Gets the name of all recipes present in a cookbook Returns a list of dictionaries | 677 | 18 |
237,053 | def get_recipes_in_node ( node ) : recipes = [ ] for elem in node . get ( 'run_list' , [ ] ) : if elem . startswith ( "recipe" ) : recipe = elem . split ( '[' ) [ 1 ] . split ( ']' ) [ 0 ] recipes . append ( recipe ) return recipes | Gets the name of all recipes present in the run_list of a node | 79 | 16 |
237,054 | def get_recipes ( ) : dirnames = set ( ) for path in cookbook_paths : dirnames . update ( [ d for d in os . listdir ( path ) if os . path . isdir ( os . path . join ( path , d ) ) and not d . startswith ( '.' ) ] ) recipes = [ ] for dirname in dirnames : recipes . extend ( get_recipes_in_cookbook ( dirname ) ) return sorted ( recipes , key = lambda x : x [ 'name' ] ) | Gets all recipes found in the cookbook directories | 118 | 10 |
237,055 | def print_recipe ( recipe ) : print ( colors . yellow ( "\n{0}" . format ( recipe [ 'name' ] ) ) ) print " description: {0}" . format ( recipe [ 'description' ] ) print " version: {0}" . format ( recipe [ 'version' ] ) print " dependencies: {0}" . format ( ", " . join ( recipe [ 'dependencies' ] ) ) print " attributes: {0}" . format ( ", " . join ( recipe [ 'attributes' ] ) ) | Pretty prints the given recipe | 114 | 5 |
237,056 | def _get_role ( rolename ) : path = os . path . join ( 'roles' , rolename + '.json' ) if not os . path . exists ( path ) : abort ( "Couldn't read role file {0}" . format ( path ) ) with open ( path , 'r' ) as f : try : role = json . loads ( f . read ( ) ) except ValueError as e : msg = "Little Chef found the following error in your" msg += " {0}.json file:\n {1}" . format ( rolename , str ( e ) ) abort ( msg ) role [ 'fullname' ] = rolename return role | Reads and parses a file containing a role | 147 | 10 |
237,057 | def get_roles ( ) : roles = [ ] for root , subfolders , files in os . walk ( 'roles' ) : for filename in files : if filename . endswith ( ".json" ) : path = os . path . join ( root [ len ( 'roles' ) : ] , filename [ : - len ( '.json' ) ] ) roles . append ( _get_role ( path ) ) return sorted ( roles , key = lambda x : x [ 'fullname' ] ) | Gets all roles found in the roles directory | 110 | 9 |
237,058 | def print_role ( role , detailed = True ) : if detailed : print ( colors . yellow ( role . get ( 'fullname' ) ) ) else : print ( " Role: {0}" . format ( role . get ( 'fullname' ) ) ) if detailed : print ( " description: {0}" . format ( role . get ( 'description' ) ) ) if 'default_attributes' in role : print ( " default_attributes:" ) _pprint ( role [ 'default_attributes' ] ) if 'override_attributes' in role : print ( " override_attributes:" ) _pprint ( role [ 'override_attributes' ] ) if detailed : print ( " run_list: {0}" . format ( role . get ( 'run_list' ) ) ) print ( "" ) | Pretty prints the given role | 180 | 5 |
237,059 | def import_plugin ( name ) : path = os . path . join ( "plugins" , name + ".py" ) try : with open ( path , 'rb' ) as f : try : plugin = imp . load_module ( "p_" + name , f , name + '.py' , ( '.py' , 'rb' , imp . PY_SOURCE ) ) except SyntaxError as e : error = "Found plugin '{0}', but it seems" . format ( name ) error += " to have a syntax error: {0}" . format ( str ( e ) ) abort ( error ) except IOError : abort ( "Sorry, could not find '{0}.py' in the plugin directory" . format ( name ) ) return plugin | Imports plugin python module | 163 | 5 |
237,060 | def get_cookbook_path ( cookbook_name ) : for cookbook_path in cookbook_paths : path = os . path . join ( cookbook_path , cookbook_name ) if os . path . exists ( path ) : return path raise IOError ( 'Can\'t find cookbook with name "{0}"' . format ( cookbook_name ) ) | Returns path to the cookbook for the given cookbook name | 82 | 12 |
237,061 | def global_confirm ( question , default = True ) : if env . abort_on_prompts : return True original_parallel = env . parallel env . parallel = False result = confirm ( question , default ) env . parallel = original_parallel return result | Shows a confirmation that applies to all hosts by temporarily disabling parallel execution in Fabric | 57 | 16 |
237,062 | def _pprint ( dic ) : for key , value in dic . items ( ) : print ( " {0}: {1}" . format ( key , value ) ) | Prints a dictionary with one indentation level | 38 | 9 |
237,063 | def get_margin ( length ) : if length > 23 : margin_left = "\t" chars = 1 elif length > 15 : margin_left = "\t\t" chars = 2 elif length > 7 : margin_left = "\t\t\t" chars = 3 else : margin_left = "\t\t\t\t" chars = 4 return margin_left | Add enough tabs to align in two columns | 83 | 8 |
237,064 | def configure ( current_node = None ) : current_node = current_node or { } # Ensure that the /tmp/chef-solo/cache directory exist cache_dir = "{0}/cache" . format ( env . node_work_path ) # First remote call, could go wrong try : cache_exists = exists ( cache_dir ) except EOFError as e : abort ( "Could not login to node, got: {0}" . format ( e ) ) if not cache_exists : with settings ( hide ( 'running' , 'stdout' ) , warn_only = True ) : output = sudo ( 'mkdir -p {0}' . format ( cache_dir ) ) if output . failed : error = "Could not create {0} dir. " . format ( env . node_work_path ) error += "Do you have sudo rights?" abort ( error ) # Change ownership of /tmp/chef-solo/ so that we can rsync with hide ( 'running' , 'stdout' ) : with settings ( warn_only = True ) : output = sudo ( 'chown -R {0} {1}' . format ( env . user , env . node_work_path ) ) if output . failed : error = "Could not modify {0} dir. " . format ( env . node_work_path ) error += "Do you have sudo rights?" abort ( error ) # Set up chef solo configuration logging_path = os . path . dirname ( LOGFILE ) if not exists ( logging_path ) : sudo ( 'mkdir -p {0}' . format ( logging_path ) ) if not exists ( '/etc/chef' ) : sudo ( 'mkdir -p /etc/chef' ) # Set parameters and upload solo.rb template reversed_cookbook_paths = cookbook_paths [ : ] reversed_cookbook_paths . reverse ( ) cookbook_paths_list = '[{0}]' . format ( ', ' . join ( [ '"{0}/{1}"' . format ( env . node_work_path , x ) for x in reversed_cookbook_paths ] ) ) data = { 'node_work_path' : env . node_work_path , 'cookbook_paths_list' : cookbook_paths_list , 'environment' : current_node . get ( 'chef_environment' , '_default' ) , 'verbose' : "true" if env . verbose else "false" , 'http_proxy' : env . http_proxy , 'https_proxy' : env . https_proxy } with settings ( hide ( 'everything' ) ) : try : upload_template ( 'solo.rb.j2' , '/etc/chef/solo.rb' , context = data , use_sudo = True , backup = False , template_dir = BASEDIR , use_jinja = True , mode = 0400 ) except SystemExit : error = ( "Failed to upload '/etc/chef/solo.rb'\nThis " "can happen when the deployment user does not have a " "home directory, which is needed as a temporary location" ) abort ( error ) with hide ( 'stdout' ) : sudo ( 'chown root:$(id -g -n root) {0}' . format ( '/etc/chef/solo.rb' ) ) | Deploy chef - solo specific files | 755 | 6 |
237,065 | def execute ( node ) : with hide ( 'everything' ) : virt = json . loads ( sudo ( 'ohai virtualization' ) ) if not len ( virt ) or virt [ 0 ] [ 1 ] != "host" : # It may work for virtualization solutions other than Xen print ( "This node is not a Xen host, doing nothing" ) return node [ 'virtualization' ] = { 'role' : 'host' , 'system' : 'xen' , 'vms' : [ ] , } # VMs with hide ( 'everything' ) : vm_list = sudo ( "xm list" ) for vm in vm_list . split ( "\n" ) [ 2 : ] : data = vm . split ( ) if len ( data ) != 6 : break node [ 'virtualization' ] [ 'vms' ] . append ( { 'fqdn' : data [ 0 ] , 'RAM' : data [ 2 ] , 'cpus' : data [ 3 ] } ) print ( "Found {0} VMs for this Xen host" . format ( len ( node [ 'virtualization' ] [ 'vms' ] ) ) ) # Save node file and remove the returned temp file del node [ 'name' ] os . remove ( chef . save_config ( node , True ) ) | Uses ohai to get virtualization information which is then saved to then node file | 283 | 17 |
237,066 | def nodes_with_role ( rolename ) : nodes = [ n [ 'name' ] for n in lib . get_nodes_with_role ( rolename , env . chef_environment ) ] if not len ( nodes ) : print ( "No nodes found with role '{0}'" . format ( rolename ) ) sys . exit ( 0 ) return node ( * nodes ) | Configures a list of nodes that have the given role in their run list | 86 | 15 |
237,067 | def nodes_with_recipe ( recipename ) : nodes = [ n [ 'name' ] for n in lib . get_nodes_with_recipe ( recipename , env . chef_environment ) ] if not len ( nodes ) : print ( "No nodes found with recipe '{0}'" . format ( recipename ) ) sys . exit ( 0 ) return node ( * nodes ) | Configures a list of nodes that have the given recipe in their run list | 85 | 15 |
237,068 | def node ( * nodes ) : chef . build_node_data_bag ( ) if not len ( nodes ) or nodes [ 0 ] == '' : abort ( 'No node was given' ) elif nodes [ 0 ] == 'all' : # Fetch all nodes and add them to env.hosts for node in lib . get_nodes ( env . chef_environment ) : env . hosts . append ( node [ 'name' ] ) if not len ( env . hosts ) : abort ( 'No nodes found in /nodes/' ) message = "Are you sure you want to configure all nodes ({0})" . format ( len ( env . hosts ) ) if env . chef_environment : message += " in the {0} environment" . format ( env . chef_environment ) message += "?" if not __testing__ : if not lib . global_confirm ( message ) : abort ( 'Aborted by user' ) else : # A list of nodes was given env . hosts = list ( nodes ) env . all_hosts = list ( env . hosts ) # Shouldn't be needed # Check whether another command was given in addition to "node:" if not ( littlechef . __cooking__ and 'node:' not in sys . argv [ - 1 ] and 'nodes_with_role:' not in sys . argv [ - 1 ] and 'nodes_with_recipe:' not in sys . argv [ - 1 ] and 'nodes_with_tag:' not in sys . argv [ - 1 ] ) : # If user didn't type recipe:X, role:Y or deploy_chef, # configure the nodes with settings ( ) : execute ( _node_runner ) chef . remove_local_node_data_bag ( ) | Selects and configures a list of nodes . all configures all nodes | 382 | 15 |
237,069 | def _node_runner ( ) : env . host_string = lib . get_env_host_string ( ) node = lib . get_node ( env . host_string ) _configure_fabric_for_platform ( node . get ( "platform" ) ) if __testing__ : print "TEST: would now configure {0}" . format ( env . host_string ) else : lib . print_header ( "Configuring {0}" . format ( env . host_string ) ) if env . autodeploy_chef and not chef . chef_test ( ) : deploy_chef ( ask = "no" ) chef . sync_node ( node ) | This is only used by node so that we can execute in parallel | 146 | 13 |
237,070 | def deploy_chef ( ask = "yes" , version = "11" ) : env . host_string = lib . get_env_host_string ( ) if ask == "no" or littlechef . noninteractive : print ( "Deploying Chef using omnibus installer version: ..." . format ( version ) ) else : message = ( '\nAre you sure you want to install Chef version:' '{0} on node {1}?' . format ( version , env . host_string ) ) if not confirm ( message ) : abort ( 'Aborted by user' ) lib . print_header ( "Configuring Chef Solo on {0}" . format ( env . host_string ) ) if not __testing__ : solo . install ( version ) solo . configure ( ) # Build a basic node file if there isn't one already # with some properties from ohai with settings ( hide ( 'stdout' ) , warn_only = True ) : output = sudo ( 'ohai -l warn' ) if output . succeeded : try : ohai = json . loads ( output ) except ValueError : abort ( "Could not parse ohai's output" ":\n {0}" . format ( output ) ) node = { "run_list" : [ ] } for attribute in [ "ipaddress" , "platform" , "platform_family" , "platform_version" ] : if ohai . get ( attribute ) : node [ attribute ] = ohai [ attribute ] chef . save_config ( node ) | Install chef - solo on a node | 325 | 7 |
237,071 | def plugin ( name ) : env . host_string = lib . get_env_host_string ( ) plug = lib . import_plugin ( name ) lib . print_header ( "Executing plugin '{0}' on " "{1}" . format ( name , env . host_string ) ) node = lib . get_node ( env . host_string ) if node == { 'run_list' : [ ] } : node [ 'name' ] = env . host_string plug . execute ( node ) print ( "Finished executing plugin" ) | Executes the selected plugin Plugins are expected to be found in the kitchen s plugins directory | 120 | 18 |
237,072 | def list_envs ( ) : for env in lib . get_environments ( ) : margin_left = lib . get_margin ( len ( env [ 'name' ] ) ) print ( "{0}{1}{2}" . format ( env [ 'name' ] , margin_left , env . get ( 'description' , '(no description)' ) ) ) | List all environments | 78 | 3 |
237,073 | def list_nodes_with_tag ( tag ) : lib . print_nodes ( lib . get_nodes_with_tag ( tag , env . chef_environment , littlechef . include_guests ) ) | Show all nodes which have assigned a given tag | 49 | 9 |
237,074 | def list_recipes ( ) : for recipe in lib . get_recipes ( ) : margin_left = lib . get_margin ( len ( recipe [ 'name' ] ) ) print ( "{0}{1}{2}" . format ( recipe [ 'name' ] , margin_left , recipe [ 'description' ] ) ) | Show a list of all available recipes | 71 | 7 |
237,075 | def list_roles ( ) : for role in lib . get_roles ( ) : margin_left = lib . get_margin ( len ( role [ 'fullname' ] ) ) print ( "{0}{1}{2}" . format ( role [ 'fullname' ] , margin_left , role . get ( 'description' , '(no description)' ) ) ) | Show a list of all available roles | 80 | 7 |
237,076 | def _check_appliances ( ) : filenames = os . listdir ( os . getcwd ( ) ) missing = [ ] for dirname in [ 'nodes' , 'environments' , 'roles' , 'cookbooks' , 'data_bags' ] : if ( dirname not in filenames ) or ( not os . path . isdir ( dirname ) ) : missing . append ( dirname ) return ( not bool ( missing ) ) , missing | Looks around and return True or False based on whether we are in a kitchen | 105 | 15 |
237,077 | def create_ticket_str ( self , prefix = None ) : if not prefix : prefix = self . model . TICKET_PREFIX return "%s-%d-%s" % ( prefix , int ( time . time ( ) ) , get_random_string ( length = self . model . TICKET_RAND_LEN ) ) | Generate a sufficiently opaque ticket string to ensure the ticket is not guessable . If a prefix is provided prepend it to the string . | 77 | 28 |
237,078 | def validate_ticket ( self , ticket , service , renew = False , require_https = False ) : if not ticket : raise InvalidRequest ( "No ticket string provided" ) if not self . model . TICKET_RE . match ( ticket ) : raise InvalidTicket ( "Ticket string %s is invalid" % ticket ) try : t = self . get ( ticket = ticket ) except self . model . DoesNotExist : raise InvalidTicket ( "Ticket %s does not exist" % ticket ) if t . is_consumed ( ) : raise InvalidTicket ( "%s %s has already been used" % ( t . name , ticket ) ) if t . is_expired ( ) : raise InvalidTicket ( "%s %s has expired" % ( t . name , ticket ) ) if not service : raise InvalidRequest ( "No service identifier provided" ) if require_https and not is_scheme_https ( service ) : raise InvalidService ( "Service %s is not HTTPS" % service ) if not service_allowed ( service ) : raise InvalidService ( "Service %s is not a valid %s URL" % ( service , t . name ) ) try : if not match_service ( t . service , service ) : raise InvalidService ( "%s %s for service %s is invalid for " "service %s" % ( t . name , ticket , t . service , service ) ) except AttributeError : pass try : if renew and not t . is_primary ( ) : raise InvalidTicket ( "%s %s was not issued via primary " "credentials" % ( t . name , ticket ) ) except AttributeError : pass logger . debug ( "Validated %s %s" % ( t . name , ticket ) ) return t | Given a ticket string and service identifier validate the corresponding Ticket . If validation succeeds return the Ticket . If validation fails raise an appropriate error . | 383 | 27 |
237,079 | def delete_invalid_tickets ( self ) : for ticket in self . filter ( Q ( consumed__isnull = False ) | Q ( expires__lte = now ( ) ) ) . order_by ( '-expires' ) : try : ticket . delete ( ) except models . ProtectedError : pass | Delete consumed or expired Ticket s that are not referenced by other Ticket s . Invalid tickets are no longer valid for authentication and can be safely deleted . | 68 | 29 |
237,080 | def consume_tickets ( self , user ) : for ticket in self . filter ( user = user , consumed__isnull = True , expires__gt = now ( ) ) : ticket . consume ( ) | Consume all valid Ticket s for a specified user . This is run when the user logs out to ensure all issued tickets are no longer valid for future authentication attempts . | 43 | 33 |
237,081 | def request_sign_out ( self , user ) : session = Session ( ) for ticket in self . filter ( user = user , consumed__gte = user . last_login ) : ticket . request_sign_out ( session = session ) | Send a single logout request to each service accessed by a specified user . This is called at logout when single logout is enabled . | 52 | 28 |
237,082 | def request_sign_out ( self , session = requests ) : if logout_allowed ( self . service ) : request = SingleSignOutRequest ( context = { 'ticket' : self } ) url = get_logout_url ( self . service ) or self . service session . post ( url , data = { 'logoutRequest' : request . render_content ( ) } ) logger . info ( "Single sign-out request sent to %s" % url ) | Send a POST request to the ServiceTicket s logout URL to request sign - out . | 101 | 19 |
237,083 | def validate_callback ( self , service , pgturl , pgtid , pgtiou ) : if not proxy_allowed ( service ) : raise UnauthorizedServiceProxy ( "%s is not authorized to use proxy authentication" % service ) if not is_scheme_https ( pgturl ) : raise InvalidProxyCallback ( "Proxy callback %s is not HTTPS" % pgturl ) if not proxy_callback_allowed ( service , pgturl ) : raise InvalidProxyCallback ( "%s is not an authorized proxy callback URL" % pgturl ) # Verify that the SSL certificate is valid verify = os . environ . get ( 'REQUESTS_CA_BUNDLE' , True ) try : requests . get ( pgturl , verify = verify , timeout = 5 ) except requests . exceptions . SSLError : raise InvalidProxyCallback ( "SSL certificate validation failed for proxy callback %s" % pgturl ) except requests . exceptions . RequestException as e : raise InvalidProxyCallback ( e ) # Callback certificate appears valid, so send the ticket strings pgturl = add_query_params ( pgturl , { 'pgtId' : pgtid , 'pgtIou' : pgtiou } ) try : response = requests . get ( pgturl , verify = verify , timeout = 5 ) except requests . exceptions . RequestException as e : raise InvalidProxyCallback ( e ) try : response . raise_for_status ( ) except requests . exceptions . HTTPError as e : raise InvalidProxyCallback ( "Proxy callback %s returned %s" % ( pgturl , e ) ) | Verify the provided proxy callback URL . | 349 | 8 |
237,084 | def _get_backends ( ) : backends = [ ] backend_paths = getattr ( settings , 'MAMA_CAS_SERVICE_BACKENDS' , [ 'mama_cas.services.backends.SettingsBackend' ] ) for backend_path in backend_paths : backend = import_string ( backend_path ) ( ) backends . append ( backend ) return backends | Retrieve the list of configured service backends . | 89 | 10 |
237,085 | def _is_allowed ( attr , * args ) : for backend in _get_backends ( ) : try : if getattr ( backend , attr ) ( * args ) : return True except AttributeError : raise NotImplementedError ( "%s.%s.%s() not implemented" % ( backend . __class__ . __module__ , backend . __class__ . __name__ , attr ) ) return False | Test if a given attribute is allowed according to the current set of configured service backends . | 94 | 18 |
237,086 | def _is_valid_service_url ( url ) : valid_services = getattr ( settings , 'MAMA_CAS_VALID_SERVICES' , ( ) ) if not valid_services : return True warnings . warn ( 'The MAMA_CAS_VALID_SERVICES setting is deprecated. Services ' 'should be configured using MAMA_CAS_SERVICES.' , DeprecationWarning ) for service in [ re . compile ( s ) for s in valid_services ] : if service . match ( url ) : return True return False | Access services list from MAMA_CAS_VALID_SERVICES . | 123 | 17 |
237,087 | def get_backend_path ( service ) : for backend in _get_backends ( ) : try : if backend . service_allowed ( service ) : return "%s.%s" % ( backend . __class__ . __module__ , backend . __class__ . __name__ ) except AttributeError : raise NotImplementedError ( "%s.%s.service_allowed() not implemented" % ( backend . __class__ . __module__ , backend . __class__ . __name__ ) ) return None | Return the dotted path of the matching backend . | 113 | 9 |
237,088 | def get_callbacks ( service ) : callbacks = list ( getattr ( settings , 'MAMA_CAS_ATTRIBUTE_CALLBACKS' , [ ] ) ) if callbacks : warnings . warn ( 'The MAMA_CAS_ATTRIBUTE_CALLBACKS setting is deprecated. Service callbacks ' 'should be configured using MAMA_CAS_SERVICES.' , DeprecationWarning ) for backend in _get_backends ( ) : try : callbacks . extend ( backend . get_callbacks ( service ) ) except AttributeError : raise NotImplementedError ( "%s.%s.get_callbacks() not implemented" % ( backend . __class__ . __module__ , backend . __class__ . __name__ ) ) return callbacks | Get configured callbacks list for a given service identifier . | 175 | 11 |
237,089 | def get_logout_url ( service ) : for backend in _get_backends ( ) : try : return backend . get_logout_url ( service ) except AttributeError : raise NotImplementedError ( "%s.%s.get_logout_url() not implemented" % ( backend . __class__ . __module__ , backend . __class__ . __name__ ) ) return None | Get the configured logout URL for a given service identifier if any . | 89 | 14 |
237,090 | def logout_allowed ( service ) : if hasattr ( settings , 'MAMA_CAS_SERVICES' ) : return _is_allowed ( 'logout_allowed' , service ) if hasattr ( settings , 'MAMA_CAS_ENABLE_SINGLE_SIGN_OUT' ) : warnings . warn ( 'The MAMA_CAS_ENABLE_SINGLE_SIGN_OUT setting is deprecated. SLO ' 'should be configured using MAMA_CAS_SERVICES.' , DeprecationWarning ) return getattr ( settings , 'MAMA_CAS_ENABLE_SINGLE_SIGN_OUT' , False ) | Check if a given service identifier should be sent a logout request . | 146 | 14 |
237,091 | def proxy_callback_allowed ( service , pgturl ) : if hasattr ( settings , 'MAMA_CAS_SERVICES' ) : return _is_allowed ( 'proxy_callback_allowed' , service , pgturl ) return _is_valid_service_url ( service ) | Check if a given proxy callback is allowed for the given service identifier . | 65 | 14 |
237,092 | def clean ( self ) : username = self . cleaned_data . get ( 'username' ) password = self . cleaned_data . get ( 'password' ) if username and password : try : self . user = authenticate ( request = self . request , username = username , password = password ) except Exception : logger . exception ( "Error authenticating %s" % username ) error_msg = _ ( 'Internal error while authenticating user' ) raise forms . ValidationError ( error_msg ) if self . user is None : logger . warning ( "Failed authentication for %s" % username ) error_msg = _ ( 'The username or password is not correct' ) raise forms . ValidationError ( error_msg ) else : if not self . user . is_active : logger . warning ( "User account %s is disabled" % username ) error_msg = _ ( 'This user account is disabled' ) raise forms . ValidationError ( error_msg ) return self . cleaned_data | Pass the provided username and password to the active authentication backends and verify the user account is not disabled . If authentication succeeds the User object is assigned to the form so it can be accessed in the view . | 212 | 41 |
237,093 | def ns ( self , prefix , tag ) : return etree . QName ( self . prefixes [ prefix ] , tag ) | Given a prefix and an XML tag output the qualified name for proper namespace handling on output . | 27 | 18 |
237,094 | def validate_service_ticket ( service , ticket , pgturl = None , renew = False , require_https = False ) : logger . debug ( "Service validation request received for %s" % ticket ) # Check for proxy tickets passed to /serviceValidate if ticket and ticket . startswith ( ProxyTicket . TICKET_PREFIX ) : raise InvalidTicketSpec ( 'Proxy tickets cannot be validated with /serviceValidate' ) st = ServiceTicket . objects . validate_ticket ( ticket , service , renew = renew , require_https = require_https ) attributes = get_attributes ( st . user , st . service ) if pgturl is not None : logger . debug ( "Proxy-granting ticket request received for %s" % pgturl ) pgt = ProxyGrantingTicket . objects . create_ticket ( service , pgturl , user = st . user , granted_by_st = st ) else : pgt = None return st , attributes , pgt | Validate a service ticket string . Return a triplet containing a ServiceTicket and an optional ProxyGrantingTicket or a ValidationError if ticket validation failed . | 216 | 34 |
237,095 | def validate_proxy_ticket ( service , ticket , pgturl = None ) : logger . debug ( "Proxy validation request received for %s" % ticket ) pt = ProxyTicket . objects . validate_ticket ( ticket , service ) attributes = get_attributes ( pt . user , pt . service ) # Build a list of all services that proxied authentication, # in reverse order of which they were traversed proxies = [ pt . service ] prior_pt = pt . granted_by_pgt . granted_by_pt while prior_pt : proxies . append ( prior_pt . service ) prior_pt = prior_pt . granted_by_pgt . granted_by_pt if pgturl is not None : logger . debug ( "Proxy-granting ticket request received for %s" % pgturl ) pgt = ProxyGrantingTicket . objects . create_ticket ( service , pgturl , user = pt . user , granted_by_pt = pt ) else : pgt = None return pt , attributes , pgt , proxies | Validate a proxy ticket string . Return a 4 - tuple containing a ProxyTicket an optional ProxyGrantingTicket and a list of proxies through which authentication proceeded or a ValidationError if ticket validation failed . | 226 | 43 |
237,096 | def validate_proxy_granting_ticket ( pgt , target_service ) : logger . debug ( "Proxy ticket request received for %s using %s" % ( target_service , pgt ) ) pgt = ProxyGrantingTicket . objects . validate_ticket ( pgt , target_service ) pt = ProxyTicket . objects . create_ticket ( service = target_service , user = pgt . user , granted_by_pgt = pgt ) return pt | Validate a proxy granting ticket string . Return an ordered pair containing a ProxyTicket or a ValidationError if ticket validation failed . | 103 | 27 |
237,097 | def get_attributes ( user , service ) : attributes = { } for path in get_callbacks ( service ) : callback = import_string ( path ) attributes . update ( callback ( user , service ) ) return attributes | Return a dictionary of user attributes from the set of configured callback functions . | 47 | 14 |
237,098 | def logout_user ( request ) : logger . debug ( "Logout request received for %s" % request . user ) if is_authenticated ( request . user ) : ServiceTicket . objects . consume_tickets ( request . user ) ProxyTicket . objects . consume_tickets ( request . user ) ProxyGrantingTicket . objects . consume_tickets ( request . user ) ServiceTicket . objects . request_sign_out ( request . user ) logger . info ( "Single sign-on session ended for %s" % request . user ) logout ( request ) messages . success ( request , _ ( 'You have been successfully logged out' ) ) | End a single sign - on session for the current user . | 144 | 12 |
237,099 | def user_name_attributes ( user , service ) : attributes = { } attributes [ 'username' ] = user . get_username ( ) attributes [ 'full_name' ] = user . get_full_name ( ) attributes [ 'short_name' ] = user . get_short_name ( ) return attributes | Return all available user name related fields and methods . | 69 | 10 |
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