jsonlite
RMySQL
jsonlite | RMySQL | |
---|---|---|
1 | 1 | |
369 | 207 | |
- | 0.5% | |
5.8 | 4.7 | |
18 days ago | 5 months ago | |
C | C | |
GNU General Public License v3.0 or later | - |
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jsonlite
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For fans of Spotify Wrapped, you can download your chronological streaming history for more detailed analysis. No genres or moods, but they provide every song played along with timestamp. [OC]
I read these JSON files with the jsonlite R package and wrangled them using dplyr before plotting with ggplot2.
RMySQL
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How to convert Blob from SQL to string?
Google came up with this, though I can't say it really looks like a likely winner.
What are some alternatives?
dplyr - dplyr: A grammar of data manipulation
mydumper - Official MyDumper project [Moved to: https://github.com/mydumper/mydumper]
writexl - Portable, light-weight data frame to xlsx exporter for R
mydumper - Official MyDumper Project
ssh - Native SSH client in R based on libssh
Collapse Launcher - An Advanced Launcher for miHoYo Games
catboost - A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
qs - Quick serialization of R objects
kunlun - KunlunBase is a distributed relational database management system(RDBMS) with complete NewSQL capabilities and robust transaction ACID guarantees and is compatible with standard SQL. Applications which used PostgreSQL or MySQL can work with KunlunBase as-is without any code change or rebuild because KunlunBase supports both PostgreSQL and MySQL connection protocols and DML SQL grammars. MySQL DBAs can quickly work on a KunlunBase cluster because we use MySQL as storage nodes of KunlunBase. KunlunBase can elastically scale out as needed, and guarantees transaction ACID under error conditions, and KunlunBase fully passes TPC-C, TPC-H and TPC-DS test suites, so it not only support OLTP workloads but also OLAP workloads. Application developers can use KunlunBase to build IT systems that handles terabytes of data, without any effort on their part to implement data sharding, distributed transaction processing, distributed query processing, crash safety, high availability, strong consistency
OHMySQL - Swift + MySQL = ❤️