[Blog](https://scrapfly.io/blog) / [data-parsing](https://scrapfly.io/blog/tag/data-parsing) / [How to Parse Datetime Strings with Python and Dateparser](https://scrapfly.io/blog/posts/parsing-datetime-strings-with-python-and-dateparser) # How to Parse Datetime Strings with Python and Dateparser by [Bernardas Alisauskas](https://scrapfly.io/blog/author/bernardas) Apr 10, 2026 5 min read [\#data-parsing](https://scrapfly.io/blog/tag/data-parsing) [\#python](https://scrapfly.io/blog/tag/python) [ ](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fparsing-datetime-strings-with-python-and-dateparser "Share on LinkedIn") Parsing datetime strings when web scraping is one of the most commonly encountered challenges as the web is full of different date and time formats. In this article, we'll be taking a look at a Python package called [dateparser](https://pypi.org/project/dateparser/) which can automatically parse datetime strings from almost any text format. In short, we'll be converting Python string to datetime object with the most hands-off approach available in Python. ## Key Takeaways Master Python dateparser for converting string to datetime objects with automatic format detection, timezone handling, and advanced parsing configurations for web scraping data processing. - Use dateparser.parse() for automatic datetime string parsing from various formats without manual format specification - Handle timezone conversion and localization for international web scraping data with proper timezone handling - Configure dateparser settings for specific languages and regions to improve parsing accuracy - Implement error handling and fallback strategies for malformed or ambiguous date strings - Use specialized tools like ScrapFly for automated datetime parsing with anti-blocking features - Configure date validation and normalization for consistent datetime data processing workflows **Get web scraping tips in your inbox**Trusted by 100K+ developers and 30K+ enterprises. Unsubscribe anytime. ## What is Dateparser? Dateparser is a smart date and time text parsing library for Python. It's a popular community package that can extract real `datetime` objects from almost any text containing date or time data. ## How to use Dateparser? The key function of Dateparser is the `dateparser.parse` function. It takes any string as an argument and tries to find any datetime data in it. For example, let's say we scraped a bunch of date strings from a website and let's put them through dateparser: python```python import dateparser # Parsing dates in different formats dates_in_different_formats = [ "2023-06-07", # ISO 8601 format "06/07/2023", # US format "07/06/2023", # European format "June 7, 2023", # Long format "7 Jun 2023", # Another common format "2023-06-07T15:25:10", # ISO 8601 with time "2023-06-07 15:25:10", # Space separated date and time "2023-06-07 15:25:10.555", # Time with milliseconds ] for date_string in dates_in_different_formats: parsed_date = dateparser.parse(date_string) print(f"Original: {date_string}\n Parsed: {parsed_date}") """ Original: 2023-06-07 Parsed: 2023-06-07 00:00:00 Original: 06/07/2023 Parsed: 2023-06-07 00:00:00 Original: 07/06/2023 Parsed: 2023-07-06 00:00:00 Original: June 7, 2023 Parsed: 2023-06-07 00:00:00 Original: 7 Jun 2023 Parsed: 2023-06-07 00:00:00 Original: 2023-06-07T15:25:10 Parsed: 2023-06-07 15:25:10 Original: 2023-06-07 15:25:10 Parsed: 2023-06-07 15:25:10 Original: 2023-06-07 15:25:10.555 Parsed: 2023-06-07 15:25:10.555000 """ ``` Using Dateparser we can parse all of these different formats without having to specify any datetime formats explicitly ourselves which makes date parsing when web scraping much more accessible. ## Common Problems Datetime objects are still complicated and highly contextual. So, not all problems can be solved by Dateparser automatically without specifying parsing preferences. Here are the top problems encountered with Dateearser and how to address them useing dateparser settings. ### Date Object Order The most common issue with parsing datetime strings using Dateparser is that it can't parse dates with ambiguous date object order. For example, if we have a date like `07/06/2023` it's impossible to know if it's the 7th of June or the 6th of July. To address this the `DATE_ORDER` setting can be used: python```python import dateparser # Day first and year first dates dates = [ "13/06/2023", "06/13/2023", "23/06/13", "13/06/23", "2023/06/13", ] # Parsing with 'DMY' order print("Parsing with 'DMY' order") for date_string in dates: parsed_date = dateparser.parse(date_string, settings={'DATE_ORDER': 'DMY'}) print(f"Original: {date_string}, Parsed: {parsed_date}") # Parsing with 'YMD' order print("\nParsing with 'YMD' order") for date_string in dates: parsed_date = dateparser.parse(date_string, settings={'DATE_ORDER': 'YMD'}) print(f"Original: {date_string}, Parsed: {parsed_date}") """ Parsing with 'DMY' order Original: 13/06/2023, Parsed: 2023-06-13 00:00:00 Original: 06/13/2023, Parsed: None Original: 23/06/13, Parsed: 2013-06-23 00:00:00 Original: 13/06/23, Parsed: 2023-06-13 00:00:00 Original: 2023/06/13, Parsed: None Parsing with 'YMD' order Original: 13/06/2023, Parsed: 2023-06-13 00:00:00 Original: 06/13/2023, Parsed: 2023-06-13 00:00:00 Original: 23/06/13, Parsed: 2023-06-13 00:00:00 Original: 13/06/23, Parsed: 2013-06-23 00:00:00 Original: 2023/06/13, Parsed: 2023-06-13 00:00:00 """ ``` The date order can be usually guessed by geolocation or the language of the scraped website. For example, US websites usually use MDY format while the rest of the world uses the DMY or YMD format. ### Handling Implicit Timezones Many scraped websites often use implicit timezones. For example, if we scrape a website that shows content relative to New York, the scraped datetime strings are likely to be in New York time. For this, the timezone can be specified manually using the `TIMEZONE` setting: python```python import dateparser dateparser.parse('January 12, 2012 10:00 PM', settings={'TIMEZONE': 'US/Eastern'}) datetime.datetime(2012, 1, 12, 22, 0) parse('January 12, 2012 10:00 PM', settings={'TIMEZONE': '+0500'}) datetime.datetime(2012, 1, 12, 22, 0) ``` ### Incomplete Dates Some datetime strings can be implicitly incomplete. For example, if we scrape "December 2023" we don't know the exact date. For this, the `PREFER_DAY_OF_MONTH` setting can be used: python```python import dateparser dateparser.parse('December 2023') # default behavior is today's date: datetime.datetime(2023, 12, 16, 0, 0) dateparser.parse('December 2023', settings={'PREFER_DAY_OF_MONTH': 'last'}) datetime.datetime(2023, 12, 31, 0, 0) dateparser.parse('December 2023', settings={'PREFER_DAY_OF_MONTH': 'first'}) datetime.datetime(2023, 12, 1, 0, 0) ``` For cases where the year is implicit the `PREFER_DATES_FROM` setting can be used: python```python import dateparser # default implies the date is from the current year dateparser.parse('March') datetime.datetime(2023, 3, 7, 0, 0) # to imply the date is from the future dateparser.parse('March', settings={'PREFER_DATES_FROM': 'future'}) datetime.datetime(2024, 3, 7, 0, 0) # to imply the date is from the past dateparser.parse('March', settings={'PREFER_DATES_FROM': 'past'}) datetime.datetime(2022, 3, 7, 0, 0) ``` ## FAQ How do I handle date parsing when scraping websites with different locales?When scraping international websites, dateparser can automatically detect languages but you can also specify them explicitly using the `LANGUAGES` setting for better accuracy. Combine this with [Scrapfly's web scraping API](https://scrapfly.io/web-scraping-api) which supports [country-specific proxies](https://scrapfly.io/docs/scrape-api/anti-scraping-protection) to ensure you receive locale-appropriate content, then parse the dates with [your preferred HTML parser](https://scrapfly.io/blog/posts/parsing-html-with-css). ## Summary Dateparser is a powerful library for parsing datetime strings. It can parse dates in many different formats without having to specify any datetime formats ourselves. It also has many settings that can be used to handle common problems like implicit timezones and incomplete dates. To see a real-life example of Dateparser in web scraping see our [how to scrape ebay](https://scrapfly.io/blog/posts/how-to-scrape-ebay#scraping-listings) tutorial where we use Dateparser to parse dates used in Ebay listings. Table of Contents Table of Contents- [Key Takeaways](#key-takeaways) - [What is Dateparser?](#what-is-dateparser) - [How to use Dateparser?](#how-to-use-dateparser) - [Common Problems](#common-problems) - [Date Object Order](#date-object-order) - [Handling Implicit Timezones](#handling-implicit-timezones) - [Incomplete Dates](#incomplete-dates) - [FAQ](#faq) - [Summary](#summary) Join the Newsletter Get monthly web scraping insights Scale Your Web Scraping Anti-bot bypass, browser rendering, and rotating proxies, all in one API. Start with 1,000 free credits. No credit card required 1,000 free API credits Anti-bot bypass included [Start Free](https://scrapfly.io/register) [View Docs](https://scrapfly.io/docs/onboarding) Not ready? 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