STY: Whitespaces

src/doc/tutorials/single_file.rst

@@ -15,13 +15,13 @@ This tutorial is based on the following simple data model:
    Fish:
      recommended_properties:
        date:
-         datatype: DATETIME
+	 datatype: DATETIME
        number:
-         datatype: INTEGER
+	 datatype: INTEGER
        weight:
-         datatype: DOUBLE
+	 datatype: DOUBLE
        species:
-         datatype: TEXT
+	 datatype: TEXT
 
 You can insert this model with the following command:
 
@@ -51,48 +51,48 @@ And we will use the following crawler configuration.
   metadata:
     crawler-version: 0.9.1
   ---
-  
+
   fish_data_file:
     type: CSVTableConverter
     match: "^fish_data_.*.csv$"  # CSV file with a name that starts with "fish_data_"
     sep: ";"
     subtree:
       table_row:  # Eine Zeile in der Datei
-        type: DictElement
-        match_name: .* # we want to treat every row
-        match_value: .*
-        records:
-          Fish:  # Record for the current row; information from statements below
-                 # are added to this Record
-        subtree:
-          date:  # Spalte mit Art der Maßnahme
-            type: TextElement
-            match_name: date  # Name of the column in the table file
-            match_value: (?P<column_value>.*)
-            records:  # Records edited for each cell
-              Fish:
-                date: $column_value
-          species:
-            type: TextElement
-            match_name: species 
-            match_value: (?P<column_value>.*)
-            records: 
-              Fish:
-                species: $column_value
-          number:
-            type: TextElement
-            match_name: identifier 
-            match_value: (?P<column_value>.*)
-            records: 
-              Fish:
-                number: $column_value
-          weight:
-            type: TextElement
-            match_name: weight
-            match_value: (?P<column_value>.*)
-            records:  
-              Fish:
-                weight: $column_value
+	type: DictElement
+	match_name: .* # we want to treat every row
+	match_value: .*
+	records:
+	  Fish:  # Record for the current row; information from statements below
+		 # are added to this Record
+	subtree:
+	  date:  # Spalte mit Art der Maßnahme
+	    type: TextElement
+	    match_name: date  # Name of the column in the table file
+	    match_value: (?P<column_value>.*)
+	    records:  # Records edited for each cell
+	      Fish:
+		date: $column_value
+	  species:
+	    type: TextElement
+	    match_name: species
+	    match_value: (?P<column_value>.*)
+	    records:
+	      Fish:
+		species: $column_value
+	  number:
+	    type: TextElement
+	    match_name: identifier
+	    match_value: (?P<column_value>.*)
+	    records:
+	      Fish:
+		number: $column_value
+	  weight:
+	    type: TextElement
+	    match_name: weight
+	    match_value: (?P<column_value>.*)
+	    records:
+	      Fish:
+		weight: $column_value
 
 
 
@@ -105,7 +105,7 @@ Records and synchronize those with LinkAhead.
 .. code-block:: python
 
   #!/usr/bin/env python3
-  
+
   # Copyright (C) 2023-2024 IndiScale GmbH <info@indiscale.com>
   #
   # This program is free software: you can redistribute it and/or modify
@@ -120,28 +120,28 @@ Records and synchronize those with LinkAhead.
   #
   # You should have received a copy of the GNU Affero General Public License
   # along with this program. If not, see <https://www.gnu.org/licenses/>.
-  
+
   """Crawler for fish data"""
-  
+
   import os
   import argparse
   import sys
   import logging
-  
+
   from caoscrawler.scanner import load_definition, create_converter_registry, scan_structure_elements
   from caoscrawler.structure_elements import File
   from caoscrawler import Crawler, SecurityMode
   from caoscrawler.identifiable_adapters import CaosDBIdentifiableAdapter
-  
-  
+
+
   def crawl_file(filename: str, dry_run: bool = False):
       """Read a CSV file into a LinkAhead container.
-  
+
   Parameters
   ----------
   filename : str
     The name of the CSV file.
-  
+
   dry_run : bool
     If True, do not modify the database.
       """
@@ -149,44 +149,44 @@ Records and synchronize those with LinkAhead.
       logger = logging.getLogger("caoscrawler")
       logger.setLevel(level=(logging.DEBUG))
       logger.addHandler(logging.StreamHandler(stream=sys.stdout))
-  
+
       # load crawler configuration
       definition = load_definition("cfood.yml")
       converter_registry = create_converter_registry(definition)
-  
+
       # crawl the CSV file
       records = scan_structure_elements(items=File(name= os.path.basename(filename), path=filename),
-                                        crawler_definition=definition,
-                                        converter_registry=converter_registry)
+					crawler_definition=definition,
+					converter_registry=converter_registry)
       logger.debug(records)
-  
+
       crawler = Crawler(securityMode=SecurityMode.UPDATE)
       # This defines how Records on the server are identified with the ones we have locally
       ident = CaosDBIdentifiableAdapter()
       ident.load_from_yaml_definition("identifiables.yml")
       crawler.identifiableAdapter = ident
-  
+
       # Here we synchronize the data
       inserts, updates = crawler.synchronize(commit_changes=True, unique_names=True,
-                                             crawled_data=records)
-  
+					     crawled_data=records)
+
       #from IPython import embed
       #embed()
-  
+
   def _parse_arguments():
       """Parse the arguments."""
       parser = argparse.ArgumentParser(description='Crawler for fish data')
       parser.add_argument('-n', '--dry-run', help="Do not modify the database.", action="store_true")
       parser.add_argument('csv_file', metavar="csv file", help="The csv file to be crawled.")
       return parser.parse_args()
-  
-  
+
+
   def main():
       """Main function."""
       args = _parse_arguments()
       crawl_file(args.csv_file, dry_run=args.dry_run)
-  
-  
+
+
   if __name__ == '__main__':
       main()
 
@@ -212,7 +212,7 @@ If you have created all the files, you can run:
    python3 crawl.py fish_data_2.csv
 
 Note, that you can run the same script again and you will not see any changes
-being done to the data in LinkAhead. 
+being done to the data in LinkAhead.
 
 
 You may play around with changing data in the data table. Changes will