snowflake-connector-python
ibis
| snowflake-connector-python | ibis | |
|---|---|---|
| 3 | 23 | |
| 553 | 4,241 | |
| 0.5% | 6.5% | |
| 9.0 | 10.0 | |
| 8 days ago | about 19 hours ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
snowflake-connector-python
- Snowflake Python connector lack of async support
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Connecting Raspberry Pi + Python with Snowflake
Regarding your question, please check the dependencies here.
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Loading a file-like object to Snowflake via Python?
I actually just found a useful comment on https://github.com/snowflakedb/snowflake-connector-python/issues/317 saying that this isn't supported yet. Its fine, I can just go through S3 in the meantime.
ibis
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Show HN: Hashquery, a Python library for defining reusable analysis
I really don't understand the appeal of dbt vs a proper programming language. The templating approach leads to massive spaghetti. I look forward to trying out something like Ibis [0]
0: https://ibis-project.org/
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This Week In Python
ibis – portable Python dataframe library
- Ibis: The portable Python dataframe library
- FLaNK Stack 26 February 2024
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Quarto
The main benefit is that you get a Python (or R, Julia or Rust) interpreter. So you can evaluate code. A good example of the value of this is the Ibis docs which use Quarto: https://ibis-project.org/
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Polars – A bird's eye view of Polars
Ive found polars quite intuitive, though for python, I lean more towards [ibis](https://ibis-project.org/). The interface is nearly identical, but ibis has the benefit if building sql queries before pulling any actual data (like dbplyr) — whereas polars requires the data to be in-memory (at least for rdb’s, though correct me if Im wrong)
this to me seems like a good argument for only using ibis, but Im happy to be convinced otherwise
- Ibis – Universal Interface for Data Wrangling
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Vanna.ai: Chat with your SQL database
Please add Ibis Birdbrain https://ibis-project.github.io/ibis-birdbrain/ to the list. Birdbrain is an AI-powered data bot, built on Ibis and Marvin, supporting more than 18 database backends.
See https://github.com/ibis-project/ibis and https://ibis-project.org for more details.
- Ibis
What are some alternatives?
jaydebeapi - JayDeBeApi module allows you to connect from Python code to databases using Java JDBC. It provides a Python DB-API v2.0 to that database.
PySpark-Boilerplate - A boilerplate for writing PySpark Jobs
PyPika - PyPika is a python SQL query builder that exposes the full richness of the SQL language using a syntax that reflects the resulting query. PyPika excels at all sorts of SQL queries but is especially useful for data analysis.
Apache Impala - Apache Impala
dataset - Easy-to-use data handling for SQL data stores with support for implicit table creation, bulk loading, and transactions.
pangres - SQL upsert using pandas DataFrames for PostgreSQL, SQlite and MySQL with extra features
q - q - Run SQL directly on delimited files and multi-file sqlite databases
sqlite_scanner - DuckDB extension to read and write to SQLite databases
katacoda
nodejs-polars - nodejs front-end of polars
django-clickhouse - This project's goal is to build Yandex ClickHouse database into Django project.
store - PostgreSQL shopping cart