Converting Text-Based Dates in Non-Standard Format for SQLite Queries

Parsing and Querying Dates Stored as "DayName, Month Day, Year" Strings

Issue Overview: Challenges with Non-Standard Date Formats in SQLite Queries

The core problem revolves around querying date values stored as text in a non-sortable, human-readable format: Friday, February 18, 2022. This format includes redundant information (the day of the week) and uses month names instead of numerical representations. SQLite’s date/time functions and comparison operators cannot directly interpret this format, leading to failed or incorrect query results when attempting to filter records between two dates (date1 and date2).

Key Obstacles:

1. Non-Sortable String Structure: The date string’s components (day name, month name, day number, year) are not ordered in a way that allows lexical comparisons. For example, February 18, 2022 (stored as a substring) would lexicographically follow March 1, 2021 due to the alphabetical order of month names, even though the latter is chronologically earlier.
2. Inconsistent Tokenization: The presence of commas, spaces, and variable-length components (e.g., February vs. April) complicates parsing. Extracting the day, month, and year requires precise string manipulation.
3. Missing Time Components: While not required for basic date comparisons, the lack of a time component (e.g., 00:00:00) prevents direct use of SQLite’s datetime() or julianday() functions unless explicitly appended.
4. Case Sensitivity: Month names may not be uniformly capitalized (e.g., may vs. MAY), necessitating normalization for reliable parsing.

Real-World Impact:

• Queries using BETWEEN, >=, or <= on the raw date strings will return incorrect results because the lexical order does not match chronological order.
• Workarounds like strftime() or substr() must be embedded within queries, increasing complexity and potential for errors.

Root Causes: Why the Date Format Breaks Query Logic

1. Storage of Dates as Unprocessed Text Strings
The decision to store dates as DayName, MonthName Day, Year strings introduces three critical issues:

• Lexical vs. Chronological Order: SQLite compares strings character by character. For example, February 18, 2022 (F ASCII 70) is lexically “greater” than April 30, 2023 (A ASCII 65), even though April 2023 is later chronologically.
• Variable-Length Components: Month names vary in length (e.g., May vs. September), making it impossible to use fixed offsets with substr() without preprocessing.
• Redundant Day-of-Week Data: The leading day name (e.g., Friday, ) adds no value for comparisons but complicates parsing by introducing an extra comma and variable-length prefix.

2. Absence of Native Support for Month Name Conversions
SQLite’s built-in date/time functions (date(), datetime(), julianday(), strftime()) do not inherently recognize month names. While strftime('%m', 'February') might seem intuitive, it will fail because these functions expect numeric or ISO-8601 formatted inputs.

3. Case Sensitivity in String Matching
Queries that attempt to parse month names using exact string matches (e.g., 'February') will fail if the stored data includes variations like 'february' or 'FEBRUARY'.

4. Lack of Padding in Day Numbers
Days represented as single-digit numbers (e.g., 4 instead of 04) cause misalignment when reconstructing ISO-8601 dates (e.g., 2022-02-4 is invalid; it must be 2022-02-04).

Solutions: Converting and Querying Dates in SQLite

Step 1: Deconstruct the Date String
The first task is to isolate the month, day, and year from the string. This involves:

• Removing the day name prefix.
• Splitting the remaining string into tokens.

Example Input: Friday, February 18, 2022
Approach:

WITH input AS (SELECT 'Friday, February 18, 2022' AS raw_date)
SELECT 
  substr(raw_date, instr(raw_date, ', ') + 2) AS trimmed_date 
FROM input;
-- Result: "February 18, 2022"

Step 2: Extract Month, Day, and Year
Use nested substr() and instr() calls to split the trimmed string:

WITH input AS (SELECT 'Friday, February 18, 2022' AS raw_date),
trimmed AS (
  SELECT 
    substr(raw_date, instr(raw_date, ', ') + 2) AS trimmed_date 
  FROM input
)
SELECT
  trim(substr(trimmed_date, 1, instr(trimmed_date, ' ') - 1)) AS month,
  trim(substr(trimmed_date, instr(trimmed_date, ' ') + 1, 2)) AS day,
  trim(substr(trimmed_date, instr(trimmed_date, ', ') + 2)) AS year
FROM trimmed;
-- Result: month="February", day="18", year="2022"

Step 3: Map Month Names to Numbers
Create a lookup mechanism to convert month names to two-digit numbers. Use CASE or replace() chains:

CASE upper(month)
  WHEN 'JANUARY' THEN '01'
  WHEN 'FEBRUARY' THEN '02'
  ...
  WHEN 'DECEMBER' THEN '12'
END AS month_num

Step 4: Pad Single-Digit Days
Ensure days are two digits using printf() or string concatenation:

printf('%02d', day) AS day_padded

Step 5: Reconstruct as ISO-8601 Date
Combine the year, month number, and padded day:

year || '-' || month_num || '-' || day_padded AS iso_date

Full Conversion Query:

WITH input AS (SELECT 'Friday, February 18, 2022' AS raw_date),
trimmed AS (
  SELECT 
    substr(raw_date, instr(raw_date, ', ') + 2) AS trimmed_date 
  FROM input
),
components AS (
  SELECT
    trim(substr(trimmed_date, 1, instr(trimmed_date, ' ') - 1)) AS month,
    trim(substr(trimmed_date, instr(trimmed_date, ' ') + 1, 2)) AS day,
    trim(substr(trimmed_date, instr(trimmed_date, ', ') + 2)) AS year
  FROM trimmed
),
month_lookup AS (
  SELECT
    CASE upper(month)
      WHEN 'JANUARY' THEN '01'
      WHEN 'FEBRUARY' THEN '02'
      WHEN 'MARCH' THEN '03'
      WHEN 'APRIL' THEN '04'
      WHEN 'MAY' THEN '05'
      WHEN 'JUNE' THEN '06'
      WHEN 'JULY' THEN '07'
      WHEN 'AUGUST' THEN '08'
      WHEN 'SEPTEMBER' THEN '09'
      WHEN 'OCTOBER' THEN '10'
      WHEN 'NOVEMBER' THEN '11'
      WHEN 'DECEMBER' THEN '12'
    END AS month_num,
    printf('%02d', day) AS day_padded,
    year
  FROM components
)
SELECT year || '-' || month_num || '-' || day_padded AS iso_date 
FROM month_lookup;
-- Result: "2022-02-18"

Step 6: Integrate into a Filtering Query
Use the conversion logic in a WHERE clause to compare dates:

SELECT RiseBG, PeakBG 
FROM MealData
WHERE (
  -- Conversion logic applied to MealData.Date
  year || '-' || month_num || '-' || day_padded
) BETWEEN '2022-02-01' AND '2022-02-28';

Optimization: Precompute ISO Dates
For frequent queries, create a view or temporary table with precomputed ISO dates:

CREATE VIEW MealDataWithISODate AS
SELECT 
  RiseBG, 
  PeakBG, 
  -- Insert full conversion logic here as "iso_date"
FROM MealData;

Handling Edge Cases:

• Mixed Case Month Names: Normalize with upper(month).
• Single-Digit Days: Use printf('%02d', day).
• Malformed Dates: Add CHECK constraints or WHERE filters to exclude invalid data.

Final Query Example:

WITH date_components AS (
  SELECT
    RiseBG,
    PeakBG,
    substr(Date, instr(Date, ', ') + 2) AS trimmed_date
  FROM MealData
),
parsed AS (
  SELECT
    RiseBG,
    PeakBG,
    trim(substr(trimmed_date, 1, instr(trimmed_date, ' ') - 1)) AS month,
    trim(substr(trimmed_date, instr(trimmed_date, ' ') + 1, 2)) AS day,
    trim(substr(trimmed_date, instr(trimmed_date, ', ') + 2)) AS year
  FROM date_components
),
converted AS (
  SELECT
    RiseBG,
    PeakBG,
    year || '-' || 
    CASE upper(month)
      WHEN 'JANUARY' THEN '01'
      WHEN 'FEBRUARY' THEN '02'
      WHEN 'MARCH' THEN '03'
      WHEN 'APRIL' THEN '04'
      WHEN 'MAY' THEN '05'
      WHEN 'JUNE' THEN '06'
      WHEN 'JULY' THEN '07'
      WHEN 'AUGUST' THEN '08'
      WHEN 'SEPTEMBER' THEN '09'
      WHEN 'OCTOBER' THEN '10'
      WHEN 'NOVEMBER' THEN '11'
      WHEN 'DECEMBER' THEN '12'
    END || '-' || 
    printf('%02d', day) AS iso_date
  FROM parsed
)
SELECT RiseBG, PeakBG 
FROM converted
WHERE iso_date BETWEEN '2022-02-01' AND '2022-02-28';

Performance Considerations:

• Indexing: Without an index on the computed ISO date, queries will perform full table scans. If schema modifications are allowed, create a generated column:

  ALTER TABLE MealData ADD COLUMN iso_date TEXT 
    GENERATED ALWAYS AS (/* conversion logic */);
  CREATE INDEX idx_mealdata_iso_date ON MealData(iso_date);
  

• Caching: Use materialized views or temporary tables to store precomputed dates during batch operations.

Alternative Approaches:

• Regular Expressions: SQLite’s REGEXP extension (if available) can simplify parsing:

  SELECT regexp_replace(raw_date, '^.*, (\w+) (\d+), (\d+)$', '\3-\1-\2');
  

• External Scripts: Export data, process it with a scripting language (Python, Perl), and reimport.

Conclusion:
While SQLite’s limited string manipulation functions make date conversions cumbersome, a systematic approach using substr(), instr(), and CASE expressions can reliably transform DayName, Month Day, Year strings into query-friendly ISO dates. For long-term usability, advocate for storing dates in ISO-8601 format or as Julian Day numbers.