Python SQLite parameter substitution with wildcards in LIKE

Python SQLite parameter substitution with wildcards in LIKE

In SQLite, you can use parameter substitution with wildcards in the LIKE clause by constructing your SQL query with a placeholder and then binding the parameter using the % wildcard character appropriately.

Here's how you can perform parameter substitution with wildcards in a LIKE clause in SQLite:

import sqlite3 # Create a SQLite database connection conn = sqlite3.connect('my_database.db') cursor = conn.cursor() # Define the search pattern with wildcards search_pattern = '%example%' # Use parameter substitution and the LIKE clause in the SQL query query = "SELECT column_name FROM my_table WHERE column_name LIKE ?" cursor.execute(query, (search_pattern,)) # Fetch and print the results results = cursor.fetchall() for row in results: print(row[0]) # Close the database connection conn.close()

In this example:

  1. We create a SQLite database connection and a cursor.
  2. We define the search_pattern with % wildcards on both sides, which means it will match any string containing "example" anywhere in it.
  3. We construct the SQL query using a placeholder ? in the LIKE clause.
  4. We execute the query and provide the search_pattern as a parameter to the execute method.
  5. We fetch and print the results.
  6. Finally, we close the database connection.

This code will perform a LIKE search with the specified pattern containing wildcards, allowing you to search for strings in the database that match the pattern you provide.

Examples

  1. Python SQLite wildcard substitution for exact matches in LIKE

    • Description: Users may be seeking methods to perform wildcard substitution in SQLite queries with precise matches using the LIKE operator in Python.
    • Code:
      import sqlite3 # Connect to the SQLite database conn = sqlite3.connect('example.db') c = conn.cursor() # Query with wildcard substitution for exact matches query = "SELECT * FROM table_name WHERE column_name LIKE ?" search_term = "example" c.execute(query, (f'%{search_term}%',)) result = c.fetchall() # Process the results for row in result: print(row) # Close the connection conn.close()

  2. Python SQLite wildcard substitution for partial matches in LIKE

    • Description: Users might be looking for ways to substitute wildcards in SQLite queries for partial matches using the LIKE operator in Python.
    • Code:
      import sqlite3 # Connect to the SQLite database conn = sqlite3.connect('example.db') c = conn.cursor() # Query with wildcard substitution for partial matches query = "SELECT * FROM table_name WHERE column_name LIKE ?" search_term = "partial" c.execute(query, (f'%{search_term}%',)) result = c.fetchall() # Process the results for row in result: print(row) # Close the connection conn.close()

  3. Python SQLite parameterized query with multiple wildcards in LIKE

    • Description: Users may be interested in constructing parameterized queries in Python for SQLite with multiple wildcard substitutions in LIKE conditions.
    • Code:
      import sqlite3 # Connect to the SQLite database conn = sqlite3.connect('example.db') c = conn.cursor() # Query with multiple wildcard substitutions query = "SELECT * FROM table_name WHERE column_name LIKE ? OR column_name LIKE ?" search_term1 = "wildcard1" search_term2 = "wildcard2" c.execute(query, (f'%{search_term1}%', f'%{search_term2}%')) result = c.fetchall() # Process the results for row in result: print(row) # Close the connection conn.close()

  4. Python SQLite parameterized query with case-insensitive wildcards in LIKE

    • Description: Users may be looking for methods to perform case-insensitive wildcard substitutions in SQLite queries using the LIKE operator in Python.
    • Code:
      import sqlite3 # Connect to the SQLite database conn = sqlite3.connect('example.db') c = conn.cursor() # Query with case-insensitive wildcard substitution query = "SELECT * FROM table_name WHERE column_name LIKE ? COLLATE NOCASE" search_term = "case_insensitive" c.execute(query, (f'%{search_term}%',)) result = c.fetchall() # Process the results for row in result: print(row) # Close the connection conn.close()

  5. Python SQLite parameterized query with wildcard escape in LIKE

    • Description: Users might be interested in constructing parameterized queries in Python for SQLite with wildcard escape sequences in LIKE conditions.
    • Code:
      import sqlite3 # Connect to the SQLite database conn = sqlite3.connect('example.db') c = conn.cursor() # Query with wildcard escape in LIKE condition query = "SELECT * FROM table_name WHERE column_name LIKE ? ESCAPE '/'" search_term = "wild%card" c.execute(query, (f'%{search_term}%',)) result = c.fetchall() # Process the results for row in result: print(row) # Close the connection conn.close()

  6. Python SQLite wildcard substitution for numeric values in LIKE

    • Description: Users may be looking for techniques to substitute wildcards in SQLite queries for numeric values using the LIKE operator in Python.
    • Code:
      import sqlite3 # Connect to the SQLite database conn = sqlite3.connect('example.db') c = conn.cursor() # Query with wildcard substitution for numeric values query = "SELECT * FROM table_name WHERE column_name LIKE ?" search_term = 123 c.execute(query, (f'%{search_term}%',)) result = c.fetchall() # Process the results for row in result: print(row) # Close the connection conn.close()

  7. Python SQLite parameterized query with custom wildcards in LIKE

    • Description: Users may want to construct parameterized queries in Python for SQLite with custom wildcard characters in LIKE conditions.
    • Code:
      import sqlite3 # Connect to the SQLite database conn = sqlite3.connect('example.db') c = conn.cursor() # Query with custom wildcard substitution query = "SELECT * FROM table_name WHERE column_name LIKE ? ESCAPE ?" search_term = "cust%om" escape_char = "%" c.execute(query, (f'{search_term}', escape_char)) result = c.fetchall() # Process the results for row in result: print(row) # Close the connection conn.close()

  8. Python SQLite parameterized query with wildcard in different columns

    • Description: Users may be seeking ways to construct parameterized queries in Python for SQLite with wildcards applied to different columns.
    • Code:
      import sqlite3 # Connect to the SQLite database conn = sqlite3.connect('example.db') c = conn.cursor() # Query with wildcard substitution in different columns query = "SELECT * FROM table_name WHERE column_name1 LIKE ? OR column_name2 LIKE ?" search_term = "wildcard" c.execute(query, (f'%{search_term}%', f'%{search_term}%')) result = c.fetchall() # Process the results for row in result: print(row) # Close the connection conn.close()

  9. Python SQLite parameterized query with multiple wildcards in different conditions

    • Description: Users might be looking for methods to construct parameterized queries in Python for SQLite with multiple wildcards applied to different conditions.
    • Code:
      import sqlite3 # Connect to the SQLite database conn = sqlite3.connect('example.db') c = conn.cursor() # Query with multiple wildcard substitution in different conditions query = "SELECT * FROM table_name WHERE (column_name1 LIKE ? OR column_name2 LIKE ?) AND column_name3 LIKE ?" search_term1 = "wildcard1" search_term2 = "wildcard2" search_term3 = "wildcard3" c.execute(query, (f'%{search_term1}%', f'%{search_term2}%', f'%{search_term3}%')) result = c.fetchall() # Process the results for row in result: print(row) # Close the connection conn.close()

  10. Python SQLite parameterized query with wildcard and other conditions

    • Description: Users may want to construct parameterized queries in Python for SQLite with wildcards alongside other conditions.
    • Code:
      import sqlite3 # Connect to the SQLite database conn = sqlite3.connect('example.db') c = conn.cursor() # Query with wildcard substitution and other conditions query = "SELECT * FROM table_name WHERE column_name1 LIKE ? AND column_name2 = ?" search_term = "wildcard" other_condition = "example" c.execute(query, (f'%{search_term}%', other_condition)) result = c.fetchall() # Process the results for row in result: print(row) # Close the connection conn.close()

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