Got it, let's tackle this date sorting problem you're facing with SQLite and Python 2.7. The core issue here is that your dates are stored as strings in dd/MM/yyyy format—so sorting them directly as text will give you wrong results (since string comparison checks day first, then month, then year, which doesn't align with actual chronological order). Here are two solid approaches to fix this:

Since SQLite doesn't enforce strict date types, we can reformat the string date into a sortable YYYY-MM-DD format on the fly using string manipulation functions. This is efficient because sorting happens at the database level, which is better for large datasets.

Here's the query you can use (replace your_table with your actual table name and date_col with your date field name):

SELECT * FROM your_table 
ORDER BY SUBSTR(date_col, 7, 4) || '-' || SUBSTR(date_col, 4, 2) || '-' || SUBSTR(date_col, 1, 2) ASC;

Let me break down how this works:

• SUBSTR(date_col, 7, 4) extracts the 4-digit year (since in dd/MM/yyyy, the year starts at the 7th character)
• SUBSTR(date_col, 4, 2) extracts the 2-digit month (starts at the 4th character)
• SUBSTR(date_col, 1, 2) extracts the 2-digit day (starts at the 1st character)
• We concatenate these parts into a YYYY-MM-DD string, which SQLite can sort in proper chronological order.

Note: This will still sort invalid dates like 31/02/2018 as 2018-02-31—SQLite doesn't validate date validity here, but it will follow the string order. If you need to filter out invalid dates, you'd need extra logic, but this works for basic sorting.

If you need to handle invalid dates or want to manipulate the data further in Python, you can convert the string dates into datetime objects, then sort using those objects.

Here's a code example using Python's sqlite3 module and datetime library:

import sqlite3
import datetime

# Connect to your database
conn = sqlite3.connect('your_database.db')
cursor = conn.cursor()

# Fetch all rows from your table
cursor.execute("SELECT * FROM your_table")
rows = cursor.fetchall()

# Define a key function to convert the date string to a datetime object
# Replace `0` with the index of your date column in the fetched rows
def get_sort_key(row):
    try:
        return datetime.datetime.strptime(row[0], '%d/%m/%Y')
    except ValueError:
        # Handle invalid dates—you can return a default value or skip them
        print(f"Skipping invalid date: {row[0]}")
        return datetime.datetime.min  # Push invalid dates to the start

# Sort the rows in ascending order
sorted_rows = sorted(rows, key=get_sort_key)

# If you prefer working with dictionary-like rows:
conn.row_factory = sqlite3.Row
cursor.execute("SELECT * FROM your_table")
dict_rows = cursor.fetchall()
sorted_dict_rows = sorted(dict_rows, key=lambda r: datetime.datetime.strptime(r['date_col'], '%d/%m/%Y'))

# Don't forget to close the connection
conn.close()

This approach gives you more control over invalid dates—you can catch errors, log them, or handle them however you need. The downside is that it's less efficient for very large datasets since you're pulling all data into Python first.

Pick the method that fits your use case best: use the SQL approach for speed with large data, or the Python approach for flexibility with date validation.

内容的提问来源于stack exchange，提问作者macson taylor