Python config.debug() Examples
The following are 15
code examples of config.debug().
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Example #1
Source File: csv2db.py From csv2db with Apache License 2.0 | 6 votes |
def generate_table_sql(file_names, column_data_type): """Generates SQL for the table to load data. Parameters ---------- file_names : str The file_names to scan for columns column_data_type : str The column data type to use """ col_list = [] for file_name in file_names: f.debug("Reading file {0}".format(file_name)) with f.open_file(file_name) as file: reader = f.get_csv_reader(file) columns_to_add = f.read_header(reader) f.debug("Columns to add {0}".format(columns_to_add)) # Add columns to list implicitly removing duplicates for when going over multiple files col_list.extend(col for col in columns_to_add if col not in col_list) print_table_and_columns(col_list, column_data_type)
Example #2
Source File: csv2db.py From csv2db with Apache License 2.0 | 6 votes |
def load_files(file_names): """Loads all files into the database. file_names : str All the file names to load into the database """ for file_name in file_names: print() print("Loading file {0}".format(file_name)) f.debug("Opening file handler for '{0}'".format(file_name)) with f.open_file(file_name) as file: try: read_and_load_file(file) print("File loaded.") except StopIteration: print("File is empty: {0}".format(file_name)) except Exception as err: f.error("Error while loading file into table: {0}".format(file.name)) exception, traceback = f.get_exception_details() f.error(exception) f.debug(traceback) cfg.data_loading_error = True print("Skipping file.") print()
Example #3
Source File: ofd.py From bobby_boy with MIT License | 6 votes |
def search(self): print("Search in OFD-YA...") url = self.url_receipt_get.format(self.kkt, self.fiscal_id) request = requests.get(url) if request.status_code == 200 and request.text != '{}': self.raw = json.dumps( request.json(), ensure_ascii=False).encode('utf8') self.receipt_data = json.loads(self.raw) filename = self.get_receipt_file_name() if not os.path.exists(filename): with open(filename, 'w') as outfile: outfile.write(self.receipt_data) return True else: print("Error {} while searching in ofd-ya!".format(request.status_code)) if config.debug: print(request.text) return False
Example #4
Source File: functions.py From csv2db with Apache License 2.0 | 5 votes |
def debug(output): """Print debug output. Parameters ---------- output : Any The output to print """ if cfg.debug: if isinstance(output, list): output = ", ".join(output) elif isinstance(output, dict): output = ", ".join(str(key) + ": " + str(value) for key, value in output.items()) print_color(TerminalColor.YELLOW, "DEBUG: {0}: {1}".format(datetime.datetime.now(), output))
Example #5
Source File: csv2db.py From csv2db with Apache License 2.0 | 5 votes |
def read_and_load_file(file): """Reads and loads file. Parameters ---------- file : file_object The file to load """ reader = f.get_csv_reader(file) col_map = f.read_header(reader) f.debug("Column map: {0}".format(col_map)) for line in reader: load_data(col_map, line) load_data(col_map, None)
Example #6
Source File: loading_tests.py From csv2db with Apache License 2.0 | 5 votes |
def test_load_file_with_insufficient_columns(self): print("test_load_file_with_insufficient_columns") self.assertEqual(f.ExitCodes.SUCCESS.value, csv2db.run( ["load", "-f", "../resources/bad/201811-citibike-tripdata-not-enough-columns.csv", "-u", login["user"], "-p", login["password"], "-d", login["database"], "-t", login["table"], "--debug" ] ) )
Example #7
Source File: loading_tests.py From csv2db with Apache License 2.0 | 5 votes |
def test_exit_code_DATA_LOADING_ERROR(self): print("test_exit_code_DATA_LOADING_ERROR") self.assertEqual(f.ExitCodes.DATA_LOADING_ERROR.value, csv2db.run( ["load", "-f", "../resources/201811-citibike-tripdata.csv", "-u", login["user"], "-p", login["password"], "-d", login["database"], "-t", "DOES_NOT_EXIST", "--debug" ] ) )
Example #8
Source File: functional_tests.py From csv2db with Apache License 2.0 | 5 votes |
def setUp(self): # Set the default column separator for all tests cfg.column_separator = "," cfg.quote_char = '"' cfg.data_loading_error = False cfg.debug = False
Example #9
Source File: threataggregator.py From threataggregator with MIT License | 5 votes |
def __init__(self, old, new): """ :param list old: List of 'old' lines to compare to new :param list new: List of 'new' lines to compare to old :return: """ # Compares best when items are sorted old.sort() new.sort() self.add = [] self.delete = [] self.equal = [] s = difflib.SequenceMatcher(None, old, new) for tag, i1, i2, j1, j2 in s.get_opcodes(): # This helps to understand what we're adding and removing. From difflib documentation if config.debug: print("%7s a[%d:%d] (%s) b[%d:%d] (%s)" % (tag, i1, i2, old[i1:i2], j1, j2, new[j1:j2])) # replace takes out items from list A[i1:i2] and adds from list B[j1:j2] if tag == 'replace': for i in old[i1:i2]: self.delete.append(i) for i in new[j1:j2]: self.add.append(i) # delete records are not seen in list b. Remove items from list a[i1:i2] elif tag == 'delete': for i in old[i1:i2]: self.delete.append(i) # insert records are not seen in list a. Add items from list b. elif tag == 'insert': for i in new[j1:j2]: self.add.append(i) elif tag == 'equal': for i in old[i1:i2]: self.equal.append(i)
Example #10
Source File: test_ofd_taxcom.py From bobby_boy with MIT License | 5 votes |
def setUpClass(cls): """ Setup """ config.debug = False cls.OFD = ofd.OFDProvider(True).detect( "t=20170712T133051&s=32.50&fn=8710000100924702&i=1666&fp=3502055476&n=1")
Example #11
Source File: test_ofd_platforma.py From bobby_boy with MIT License | 5 votes |
def setUpClass(cls): """ Setup """ config.debug = False cls.OFD = ofd.OFDProvider(True).detect( "t=20170714T1311&s=35.00&fn=8710000100837497&i=231&fp=2921685295&n=1")
Example #12
Source File: test_ofd_ya.py From bobby_boy with MIT License | 5 votes |
def setUpClass(cls): """ Setup """ config.debug = False cls.OFD = ofd.OFDProvider(True).detect( "t=20170305T005100&s=140.00&fn=8710000100161943&i=8018&fp=2398195357&n=1", "0000069245023747")
Example #13
Source File: csv2db.py From csv2db with Apache License 2.0 | 4 votes |
def load_data(col_map, data): """Loads the data into the database. Parameters ---------- col_map : [str,] The columns to load the data into data : [str,] The data to load. If data is None the array will be loaded and flushed. """ if data is not None and len(data) > 0: # If the data has more values than the header provided, ignore the end (green data set has that) while len(data) > len(col_map): f.debug("Removing extra row value entry not present in the header.") data.pop() # tuple or dictionary only for SQL Server cfg.input_data.append(tuple(data)) # If batch size has been reached or input array should be flushed if (len(cfg.input_data) == cfg.batch_size) or (data is None and len(cfg.input_data) > 0): f.debug("Executing statement:") stmt = generate_statement(col_map) f.debug(stmt) cur = cfg.conn.cursor() try: f.executemany(cur, stmt) except Exception as err: # Rollback old batch (needed for at least Postgres to finish transaction) cfg.conn.rollback() # If debug output is enabled, find failing record if cfg.debug: for record in cfg.input_data: try: cur.execute(stmt, record) except Exception as err1: f.debug("Error with record: {0}".format(record)) # Rollback old batch (needed for at least Postgres to finish transaction) cfg.conn.rollback() cur.close() cfg.input_data.clear() raise # Debug output is not enabled, clear current batch and raise error else: cur.close() cfg.input_data.clear() raise f.debug("Commit") cfg.conn.commit() cur.close() f.verbose("{0} rows loaded.".format(len(cfg.input_data))) cfg.input_data.clear()
Example #14
Source File: threataggregator.py From threataggregator with MIT License | 4 votes |
def process(db_add, db_del, db_equal): """ Processes RepDB entries in order for syslog, stdout, csv file, etc :param repDB db_add: RepDB entry to show added items :param repDB db_del: RepDB entry to show deleted items :param repDB db_equal: RepDB entry to show unchanged values """ # fun toy for heatmaps later f = open('cache/coords.txt', 'w') count_add = 0 count_del = 0 count_equal = 0 for line in db_add: for i in line: count_add += 1 msg = buildcef('add', i) syslog(msg) if config.debug: printjson('add', i) f.write("%s %s\n" % (i['latitude'], i['longitude'])) for line in db_del: for i in line: count_del += 1 msg = buildcef('delete', i) if config.debug: printjson('delete', i) syslog(msg) for line in db_equal: for i in line: count_equal += 1 msg = buildcef('update', i) syslog(msg) if config.debug: printjson('update', i) f.write("%s %s\n" % (i['latitude'], i['longitude'])) f.close() print("Sent {0} New, {1} deleted, and {2} unchanged entries to {3}:{4}".format( count_add, count_del, count_equal, config.host, config.port)) # Only run code if invoked directly: This allows a user to import modules without having to run through everything
Example #15
Source File: trainer.py From neural-question-generation with MIT License | 4 votes |
def __init__(self, args): # load dictionary and embedding file with open(config.embedding, "rb") as f: embedding = pickle.load(f) embedding = torch.tensor(embedding, dtype=torch.float).to(config.device) with open(config.word2idx_file, "rb") as f: word2idx = pickle.load(f) # train, dev loader print("load train data") self.train_loader = get_loader(config.train_src_file, config.train_trg_file, word2idx, use_tag=True, batch_size=config.batch_size, debug=config.debug) self.dev_loader = get_loader(config.dev_src_file, config.dev_trg_file, word2idx, use_tag=True, batch_size=128, debug=config.debug) train_dir = os.path.join("./save", "seq2seq") self.model_dir = os.path.join( train_dir, "train_%d" % int(time.strftime("%m%d%H%M%S"))) if not os.path.exists(self.model_dir): os.makedirs(self.model_dir) self.model = Seq2seq(embedding) self.model = self.model.to(config.device) if len(args.model_path) > 0: print("load check point from: {}".format(args.model_path)) state_dict = torch.load(args.model_path, map_location="cpu") self.model.load_state_dict(state_dict) params = self.model.parameters() self.lr = config.lr self.optim = optim.SGD(params, self.lr, momentum=0.8) # self.optim = optim.Adam(params) self.criterion = nn.CrossEntropyLoss(ignore_index=0)