pendulum: Python Datetimes Made Easy #python github.com/python-pendulum/p…

If you want to implement proper DateTimes, you use Jon Skeet's work and NodaTime as reference and do it in your language of choice. Biggest possible reference with everything needed implemented. For my language i am currently building, NodaTime-like APIs will be used for dates. Of course NodaTime is also not ideal and some stuff from it will be also fixed, but base is really good. Working with Dates/DateTimes and TimeZones is one of the most painful experiences in almost any language, somehow every single one of them does it wrong. nodatime.org/

Datetimes between Earth and Mars on the other hand 💀

I have just spent the last 6 hours trying to save this payload to my database that is 70% made of datetimes. I absolutely detest working with datetime but my stubbornness worked this time around. Funny how I was about giving up. Jenny’s stubbornness 1 - Datetime 0

what if it's just some x employee having fun with datetimes

If you prefer strict typing, I can see Java or Scala being preferred by some users of Spark. The problem is dealing with datetimes and how the input data is processed. PySpark is a lot more forgiving for empty or null values there.

Automate your web scraping workflows with Olostep 'v1/schedules' endpoint! Schedule API calls to run automatically at specified times: > One-time executions at specific datetimes > Recurring tasks using cron expressions > Natural language scheduling ("every Monday at 9am") > Works with any HTTP endpoint Manage everything through a simple API. docs.olostep.com/features/sc…

Want to check if two #Python #Pandas datetimes are in the same month/quarter/year? Convert them to periods, compare with ==: date1.to_period('M') == date2 .to_period('M') # same month? date1.to_period('Q') == date2 .to_period('Q') # same quarter?

Want to turn #Python #Pandas strings into datetimes? Use pd. to_datetime: pd.t o_datetime(df['x']) Notice: It's not a method! It's a top-level pd function. Specify a non-standard "format" with a strftime string: pd. to_datetime(df['x'], format='%d/%m/%Y')

Want to compare two #Python datetimes? Just subtract, getting a timedelta: import datetime start = datetime.datetime.now() end = datetime.datetime.now() delta = end - start str(delta) # '0:00:04.170916' delta.seconds # 4 delta.microseconds # 170916

pendulum: Python Datetimes Made Easy github.com/python-pendulum/p…

@ElonMusk @Grok @PeterBernegger @DataRepublican @data_republican @SidneyPowell1 @PatrickByrne I'm working on getting @Grok to independently validate all of my research findings in various states. I'm starting with NY. My first full test used the data from Jefferson County, based on my analysis of the Spiral algorithm found on my Substack, here: zarkfiles.substack.com/p/coo… This is the result, with a hash for verification: Loaded 59,756 records from Jefferson County SBOEID MIN: 22201832 SBOEID MAX: 22261962 Range size: 60131 === EXACT PARAMETERS COMPUTED FOR JEFFERSON (compare to your Excel) === Power | Repunit | MIN | MAX | COUNT | Remainder | Adjusted next ------|---------|-----------|-----------|-------|-----------|-------------- 0 | 1 | 22201832 | 22201832 | 1 | 0 | 60130 10000 | 11111 | 22210165 | 22259184 | 5 | 4575 | 4575 1000 | 1111 | 22202665 | 22261684 | 4 | 131 | 131 100 | 111 | 22201915 | 22261934 | 1 | 20 | 20 10 | 11 | 22201840 | 22261959 | 1 | 9 | 9 1 | 1 | 22201833 | 22261962 | 9 | 0 | 0 Best proxy match: 99.97% with method no_mod H:\research\states\ny\python\grok_jefferson_spiral.py:114: DeprecationWarning: datetime.datetime.utcnow() is deprecated and scheduled for removal in a future version. Use timezone-aware objects to represent datetimes in UTC: datetime.datetime.now(datetime.UTC). report = f"\n(Run with Grok-provided script on \"{file_path}\" at {datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S UTC')})\n" === GROK JEFFERSON SPIRAL ANALYSIS REPORT (EXACT PARAMETERS DEBUG) === County: Jefferson Total records: 59,756 SBOEID range: 22201832 – 22261962 (60131 records) Best proxy match: 99.97% (no_mod) Parameters above match your Excel formulas exactly. === REPORT END === VERIFICATION HASH: ff0ccff8d09877048811881b7b9c45ab0e2d8fe0873ba1080a8ed7661f6445c8 (Run with Grok-provided script on "H:\RESEARCH\States\NY\Analysis\Category\Algorithm\Spiral\County\Jefferson-ID Only.xlsx" at 2026-03-30 23:31:22 UTC)

When dealing with DateTimes in a client<>server model, you want to decide your server's timezone and stick to it. If you pick UTC, great. If you pick another (God help you), great. Whatever you pick, ensure that your server specifies the timezone in the serialized DateTimes.

Just to play devils advocate, but excel and sqlserver do default datetimes to 1900: learn.microsoft.com/en-us/sq…

Count the unit boundaries crossed between two datetimes with DATEDIFF ( <unit>, <dt1>, <dt2> ) Note it's the boundaries crossed, not the duration e.g. 31-Dec-2025 to 2-Jan-2026 crosses the 1st Jan boundary => the year diff = 1 Added to Oracle SQL in 23.26.1

🚢 We just shipped support for datetime conditions in Knock’s conditions builder. You can now use before, on or after, and between operators across workflows, broadcasts, guides, and dynamic audiences, enabling you to apply conditions that evaluate and compare datetimes. Here's how they work 👇