pg_cron
NumPy
pg_cron | NumPy | |
---|---|---|
20 | 272 | |
2,558 | 26,413 | |
2.4% | 1.1% | |
5.8 | 10.0 | |
10 days ago | 1 day ago | |
C | Python | |
PostgreSQL License | GNU General Public License v3.0 or later |
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pg_cron
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Supabase Beta May 2023
[Postgres Extensions] pg_cron 1.5.2 (new projects only) now supports sub-minute schedules. PR
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🏺Database Architecture - History Over State
(Your PostgreSQL installation might already have pg_cron available, but if not, you would need to install it)
- Edge Functions or Database Functions?
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Upgrading to PostgreSQL 15 on Mac OS
I’d set up citusdata/pg_cron in 14, so I’ll need to set that up in 15 as well.
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PostgreSQL Functions in Typescript
Functions can be executed via a database query or on a regular schedule. Trigger functions are a special type of function that are covered in a previous article. They provide a way to execute an action based on a database event.
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Pulling Cloud API data to PostgreSQL server (Supabase)
* extraction and loading: the psql-http PostgreSQL extension which is available in Supabase (but not all services like AWS RDS). Not sure how it works with OAuth but something to look into. * automation: use pg_cron to automate the ingest. * transformation: leverage Postgresql JSON functions.
- How to : trigger a MV refresh after another MV refreshed ?
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Is it conventional to use Redis in an authentication service?
A low-level alternative is using a PostgreSQL-side facility like https://github.com/citusdata/pg_cron - this, however, requires installing a PostgreSQL extension.
- Como agendar execução de consultas e comandos pelo PostgreSQL no RDS
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Do you know of a robust library that handles persistent job scheduling and queuing using PostgreSQL
If you just want scheduling queries, you can use this https://github.com/citusdata/pg_cron
NumPy
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In NumPy with @, dot() or matmul():
- NumPy 2.0.0 Beta1
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Element-wise vs Matrix vs Dot multiplication
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication.
- JSON dans les projets data science : Trucs & Astuces
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JSON in data science projects: tips & tricks
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:
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Introducing Flama for Robust Machine Learning APIs
numpy: A library for scientific computing in Python
- help with installing numpy, please
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A Comprehensive Guide to NumPy Arrays
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy.
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Why do all the popular projects use relative imports in __init__ files if PEP 8 recommends absolute?
I was looking at all the big projects like numpy, pytorch, flask, etc.
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NumPy 2.0 development status & announcements: major C-API and Python API cleanup
I wish the NumPy devs would more thoroughly consider adding full fluent API support, e.g. x.sqrt().ceil(). [Issue #24081]
What are some alternatives?
pg_timetable - pg_timetable: Advanced scheduling for PostgreSQL
SymPy - A computer algebra system written in pure Python
pg_dbms_job
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
pg_background - pg_background
blaze - NumPy and Pandas interface to Big Data
Spring Boot - Spring Boot
SciPy - SciPy library main repository
docker-pg-cron - Dockerfile with extension pg_cron
Numba - NumPy aware dynamic Python compiler using LLVM
Express - Fast, unopinionated, minimalist web framework for node.
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).