https://github.com/jangorecki/logR
Extended logging solution for R
https://github.com/jangorecki/logR
Last synced: 4 months ago
JSON representation
Extended logging solution for R
- Host: GitHub
- URL: https://github.com/jangorecki/logR
- Owner: jangorecki
- Created: 2014-07-06T12:02:46.000Z (almost 11 years ago)
- Default Branch: master
- Last Pushed: 2016-07-05T21:24:54.000Z (almost 9 years ago)
- Last Synced: 2024-11-24T22:23:38.397Z (5 months ago)
- Language: R
- Homepage: http://jangorecki.gitlab.io/logR
- Size: 240 KB
- Stars: 13
- Watchers: 7
- Forks: 1
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Changelog: NEWS.md
Awesome Lists containing this project
- jimsghstars - jangorecki/logR - Extended logging solution for R (R)
README
# logR
Extended logging solution:
- [x] **transactional logging**
- [x] insert log getting sequence id
- [x] evaluate expression with timing and exception handling
- [x] update log with status and metadata
- [x] log to postgres database
- [x] records errors, warnings, messages, interrupts
- [x] log process metadata: in/out nrow, flexible list of custom metadata
- [x] hierarchical logging: parent log id collected in case of nested logging
- [x] high precision timing with optional [microbenchmarkCore](https://github.com/olafmersmann/microbenchmarkCore)
- [x] support parallel processing
- [ ] email notification on alerts
## Installation
```r
install.packages("logR", repos = c("https://jangorecki.gitlab.io/logR", "https://cran.rstudio.com"))
```
For high precision timing install suggested package [microbenchmarkCore](https://github.com/olafmersmann/microbenchmarkCore).
```r
install.packages("microbenchmarkCore", repos = "https://olafmersmann.github.io/drat")
```
## Usage
1. Connect to postgres db with `?logR_connect`, it will use environment variables if available. Connection is assigned to `getOption("logR.conn")` logical value returned, FALSE on failure otherwise TRUE.
2. Create db table with `?logR_schema`.
3. Use `?logR` call as wrapper over your processes.
4. Use `?logR_dump` to dump logs.
An example from [SO answer](http://stackoverflow.com/a/35274622/2490497).
```r
library(logR)
# setup connection, default to env vars: `POSTGRES_DB`, etc.
# if you have docker then: docker run --rm -p 127.0.0.1:5432:5432 -e POSTGRES_PASSWORD=postgres --name pg-logr postgres:9.5
logR_connect()
# [1] TRUE
# create logr table
logR_schema()
# make some logging and calls
logR(1+2) # OK
#[1] 3
logR(log(-1)) # warning
#[1] NaN
f = function() stop("an error")
logR(r <- f()) # stop
#NULL
g = function(n) data.frame(a=sample(letters, n, TRUE))
logR(df <- g(4)) # out rows
# a
#1 u
#2 c
#3 w
#4 p
# try CTRL+C / 'stop' button to interrupt
logR(Sys.sleep(15))
# wrapper to: dbReadTable(conn = getOption("logR.conn"), name = "logr")
logR_dump()
# logr_id logr_start expr status alert logr_end timing in_rows out_rows mail message cond_call cond_message
#1: 1 2016-02-08 16:35:00.148 1 + 2 success FALSE 2016-02-08 16:35:00.157 0.000049163 NA NA FALSE NA NA NA
#2: 2 2016-02-08 16:35:00.164 log(-1) warning TRUE 2016-02-08 16:35:00.171 0.000170801 NA NA FALSE NA log(-1) NaNs produced
#3: 3 2016-02-08 16:35:00.180 r <- f() error TRUE 2016-02-08 16:35:00.187 0.000136896 NA NA FALSE NA f() an error
#4: 4 2016-02-08 16:35:00.197 df <- g(4) success FALSE 2016-02-08 16:35:00.213 0.000696145 NA 4 FALSE NA NA NA
#5: 5 2016-02-08 16:35:00.223 Sys.sleep(15) interrupt TRUE 2016-02-08 16:35:05.434 5.202319000 NA NA FALSE NA NA NA
```
For more details see R scripts in `tests` directory and read manual.
Working examples of logR usage can also be found in [big.data.table](https://gitlab.com/jangorecki/big.data.table) and [pg](https://gitlab.com/jangorecki/pg) packages. logR can be easily located as suggested dependency and works conditionally.
## License
GPL-3