python-oracledb
q
| python-oracledb | q | |
|---|---|---|
| 3 | 46 | |
| 284 | 10,122 | |
| 4.6% | - | |
| 9.4 | 2.1 | |
| 7 days ago | 10 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 only |
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.
python-oracledb
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OracleDB anyone?
Might this be even doable? Eg with some https://oracle.github.io/python-oracledb/ client? (not that i'm capable of doing that :P)
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How would you connect to an Oracle database that's hosted on a on premise server?
Now you just need a suitable database driver. Fortunately there's one from Oracle itself: python-oracledb
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Open Source Python Thin Driver for Oracle Database
Source code: https://github.com/oracle/python-oracledb
q
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I wrote this iCalendar (.ics) command-line utility to turn common calendar exports into more broadly compatible CSV files.
CSV utilities (still haven't pick a favorite one...): https://github.com/harelba/q https://github.com/BurntSushi/xsv https://github.com/wireservice/csvkit https://github.com/johnkerl/miller
- Segítség kérés Excel automatizáláshoz
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Show HN: ClickHouse-local – a small tool for serverless data analytics
I think they're talking about https://github.com/harelba/q, which is not very fast.
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sqly - execute SQL against CSV / JSON with shell
Apparently, there were many who thought the same thing; Tools to execute SQL against CSV were trdsql, q, csvq, TextQL. They were highly functional, hoewver, had many options and no input completion. I found it just a little difficult to use.
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Q – Run SQL Directly on CSV or TSV Files
Hi, author of q here.
Regarding the error you got, q currently does not autodetect headers, so you'd need to add -H as a flag in order to use the "country" column name. You're absolutely correct on failing-fast here - It's a bug which i'll fix.
In general regarding speed - q supports automatic caching of the CSV files (through the "-C readwrite" flag). Once it's activated, it will write the data into another file (with a .qsql extension), and will use it automatically in further queries in order to speed things considerably.
Effectively, the .qsql files are regular sqlite3 files (with some metadata), and q can be used to query them directly (or any regular sqlite3 file), including the ability to seamlessly join between multiple sqlite3 files.
http://harelba.github.io/q/#auto-caching-examples
- PostgreSQL alternative for Large amounts of data
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q VS trdsql - a user suggested alternative
2 projects | 25 Jun 2022
- One-liner for running queries against CSV files with SQLite
What are some alternatives?
textql - Execute SQL against structured text like CSV or TSV
csvq - SQL-like query language for csv
octosql - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.
InquirerPy - :snake: Python port of Inquirer.js (A collection of common interactive command-line user interfaces)
xsv - A fast CSV command line toolkit written in Rust.
ledger - Double-entry accounting system with a command-line reporting interface
simdjson - Parsing gigabytes of JSON per second : used by Facebook/Meta Velox, the Node.js runtime, ClickHouse, WatermelonDB, Apache Doris, Milvus, StarRocks
sqlitebrowser - Official home of the DB Browser for SQLite (DB4S) project. Previously known as "SQLite Database Browser" and "Database Browser for SQLite". Website at:
siuba - Python library for using dplyr like syntax with pandas and SQL
emacs-edbi - Database Interface for Emacs Lisp
sqlite-utils - Python CLI utility and library for manipulating SQLite databases
dsq - Commandline tool for running SQL queries against JSON, CSV, Excel, Parquet, and more.