diff --git a/.env-template b/.env-template new file mode 100644 index 0000000..7c72ba5 --- /dev/null +++ b/.env-template @@ -0,0 +1,5 @@ +DBNAME=neotoma +HOST=localhost +PORT=5432 +USER=postgres +PASSWORD=postgres diff --git a/.githooks/pre-commit b/.githooks/pre-commit new file mode 100755 index 0000000..4752877 --- /dev/null +++ b/.githooks/pre-commit @@ -0,0 +1,47 @@ +#!/bin/bash +# +# Pre-commit hook: refuse to commit secrets. +# 1. Blocks staged .env-style files (allows .env-template / .env.example / .env.sample). +# 2. Blocks staged ADDITIONS that look like a hardcoded credential. +# This hook file is excluded from the scan so it can't flag its own patterns. +# Override in a true emergency with: git commit --no-verify +# +set -euo pipefail + +fail=0 + +# 1) Block staged secret files. +while IFS= read -r f; do + [ -z "$f" ] && continue + base=$(basename "$f") + case "$base" in + .env.template|.env.example|.env.sample) ;; # explicitly allowed + .env|.env.*) + echo "BLOCKED: refusing to commit '$f' (looks like a secrets file)." + fail=1 + ;; + esac +done < <(git diff --cached --name-only --diff-filter=ACM) + +# 2) Scan staged ADDITIONS for hardcoded credentials. Ignore template files, this +# hook itself, and env-indirection (Sys.getenv / process.env / $VAR references). +hits=$(git diff --cached -U0 --diff-filter=ACM -- . \ + ':(exclude).env-template' ':(exclude).env.example' ':(exclude).env.sample' \ + ':(exclude).githooks/pre-commit' \ + | grep -E '^\+' \ + | grep -Ei '(password|pgpassword|secret|token|api_?key)[[:space:]]*[:=]' \ + | grep -viE 'getenv|environ|process\.env|\$|<|xxxxxx|placeholder|example|your_|changeme' \ + | grep -Ei "[:=][[:space:]]*[\"']?[A-Za-z0-9]{6,}" || true) + +if [ -n "$hits" ]; then + echo "BLOCKED: staged changes look like a hardcoded credential:" + printf ' %s\n' "$hits" + echo " Store secrets in .env (gitignored) and read them via environment variables." + fail=1 +fi + +if [ "$fail" -ne 0 ]; then + echo "" + echo "Commit aborted by pre-commit hook. To override (NOT recommended): git commit --no-verify" + exit 1 +fi diff --git a/.gitignore b/.gitignore index 30824a2..655d713 100644 --- a/.gitignore +++ b/.gitignore @@ -1,4 +1,10 @@ connect_remote.json ceiwww/* -.secrets.env +.env +.DS_Store +*.Rproj .buildStats.sh +.Rproj.user + +logs/ +*.md \ No newline at end of file diff --git a/README.md b/README.md index 3f3caa3..5b44df8 100644 --- a/README.md +++ b/README.md @@ -13,6 +13,7 @@ An RMarkdown document used to derive intermediary statistics for the Neotoma dat This project is an open project, and contributions are welcome from any individual. All contributors to this project are bound by a [code of conduct](CODE_OF_CONDUCT.md). Please review and follow this code of conduct as part of your contribution. * [![orcid](https://img.shields.io/badge/orcid-0000--0002--2700--4605-brightgreen.svg)](https://orcid.org/0000-0002-2700-4605) [Simon Goring](http://goring.org) +* [![ORCID](https://img.shields.io/badge/orcid-0000--0002--7926--4935-brightgreen.svg)](https://orcid.org/0000-0002-7926-4935) [Socorro Dominguez](https://ht-data.com/about) ### Tips for Contributing @@ -39,7 +40,15 @@ rm -r ./dbout The above script creates a duplicate of the database locally and then cleans up the `sql` file extracted from the downloaded `tar` archive. -The document expects environment variables (we use defaults here, assuming the Neotoma database has been restored locally): +### Configuration + +The database connection variables are read from a `.env` file in the project root. Copy the provided template and fill in your values: + +```bash +cp .env-template .env +``` + +The `.env` file defines the connection used by the build (defaults shown assume a locally restored Neotoma database): * DBNAME=neotoma * HOST=localhost @@ -47,8 +56,25 @@ The document expects environment variables (we use defaults here, assuming the N * USER=postgres * PASSWORD=postgres -These variables are currently set by hand in the `buildStats.sh` bash script. +### Scripts + +* **`run_cloudwatchquery.sh`** — pulls API and Tilia usage statistics from AWS CloudWatch Logs (the Neotoma/Tilia Elastic Beanstalk nginx access logs) and writes them to the `log_run*.json` files that the report reads for its usage charts. It runs several CloudWatch Logs Insights queries, each of which sleeps ~5 minutes while the query completes, so a full pull takes several minutes and requires working `aws` CLI credentials. It is invoked automatically by `buildStats.sh`. +* **`buildStats.sh`** — the main build script. It first runs `run_cloudwatchquery.sh` to refresh the usage logs, then loads the database connection variables from `.env` and renders `StateoftheDB.Rmd` into HTML. It no longer hardcodes credentials; both the local and remote modes use whatever is in `.env`. + +### Running the build + +To execute and build the RMarkdown file, run: -To execute and build the RMarkdown file, simply run `bash buildStats.sh` and a valid HTML document will be generated and output into the `outputs` folder. +```bash +bash buildStats.sh local +``` + +The `local` argument just renders the report; a valid HTML document is generated and output into the `outputs` folder. + +Running it with no argument renders the report **and then commits and pushes the rebuilt artifacts** (`git add --all && git commit && git push`), which is how the periodic builds are published: + +```bash +bash buildStats.sh +``` ![The rendered Neotoma Stats document.](assets/docScreenshot.png) diff --git a/StateoftheDB.Rmd b/StateoftheDB.Rmd index aabc1e5..17f2058 100644 --- a/StateoftheDB.Rmd +++ b/StateoftheDB.Rmd @@ -2,11 +2,11 @@ title: "State of the Neotoma Paleoecology Database" shorttitle: "Neotoma Status" author: + - name: "Socorro Dominguez" + email: "dominguezvid@wisc.edu" + affiliation: "Department of Geography, University of Wisconsin--Madison" - name: "Simon Goring" - email: "goring@wisc.edu" - - affiliation: - - id: "1" - institution: "Department of Geography, University of Wisconsin--Madison" + affiliation: "Department of Geography, University of Wisconsin--Madison" date: "`r lubridate::today()`" description: | A summary of current Neotoma activity, potential data issues and other summary information. @@ -28,7 +28,7 @@ output: knitr::opts_chunk$set(echo = FALSE, warning=FALSE, message=FALSE) library(pacman) -p_load(lubridate, RPostgreSQL, DT, ggplot2, +p_load(lubridate, RPostgres, DT, ggplot2, ggthemes, svglite, httr, jsonlite, dplyr, leaflet, geojsonsf, sf, purrr, forcats, scales, leaflet.providers, dotenv, snakecase) @@ -37,12 +37,15 @@ load_dot_env() lastdate <- today() - years(1) -con <- dbConnect(dbDriver("PostgreSQL"), - dbname = Sys.getenv("DBNAME"), - host = Sys.getenv("HOST"), - port = Sys.getenv("PORT"), - user= Sys.getenv("USER"), - password= Sys.getenv("PASSWORD")) +con <- dbConnect( + Postgres(), + host = Sys.getenv("HOST"), + port = Sys.getenv("PORT"), + dbname = Sys.getenv("DBNAME"), + user = Sys.getenv("USER"), + password = Sys.getenv("PASSWORD"), + sslmode = "require" +) p <- function(x) format(x, scientific=FALSE, big.mark=',') ``` @@ -68,7 +71,7 @@ Neotoma contains data from `r p(datasets)` datasets and `r p(sites)` unique site colnames(lastyear) = c('Datasets', 'Sites', 'Publications', 'Authors', 'Countries', 'Observations') outtable <- t(lastyear) %>% as.data.frame %>% - rename('Entries'='1') %>% + rename('Entries'='V1') %>% mutate('Entries' = p(`Entries`)) DT::datatable(outtable, caption = htmltools::tags$caption( @@ -231,15 +234,17 @@ Neotoma relies on significant the efforts of a volunteer group of data stewards ### API Calls -```{r pullLogs, echo=FALSE, fig.caption="Volume of API calls to API and Tilia servers, aggregated by day over the last 6 months."} -pullLog <- jsonlite::fromJSON('log_run.json')['results'][[1]] %>% +```{r pullLogs, echo=FALSE, eval=FALSE, fig.caption="- Volume of API calls to API and Tilia servers, aggregated by day over the last 6 months. - Not updated info"} + +# Cannot use for now as logs were not being sent to AWS Cloudwatch Logs +pullLog <- jsonlite::fromJSON('log_run.json')['results']$results %>% purrr::map(function(x) tidyr::pivot_wider(x,names_from=field)) %>% bind_rows() %>% mutate(date = lubridate::date(date), calls = as.integer(calls), volume = as.integer(volume)) -pullCalls <- jsonlite::fromJSON('log_run_calls.json')['results'][[1]] %>% +pullCalls <- jsonlite::fromJSON('log_run_calls.json')['results']$results %>% purrr::map(function(x) tidyr::pivot_wider(x,names_from=field)) %>% bind_rows() %>% mutate(calls = as.integer(calls), @@ -261,13 +266,27 @@ ggplot(pullLog) + ``` -Since the API has been implemented there have been a total of `r p(sum(pullLog$calls))` calls to the Neotoma API. These include calls to the core API ([`api.neotomadb.org`](https://api.neotomadb.org)), calls to support the Neotoma Landing Pages ([`data.neotomadb.org`](https://data.neotomadb.org)) and calls to support Neotoma Explorer ([`apps.neotomadb.org/explorer`](https://data.neotomadb.org)). +```{r pullLogs2, echo=FALSE, fig.caption="- Volume of API calls to API and Tilia servers, aggregated by day over the last 8 months."} -The main APIs delivered a total of `r p(floor(sum(pullLog$volume, na.rm=TRUE) /1000000000))` GB of data to users since `r min(pullLog$date)`. +# Cannot use for now as logs were not being sent to AWS Cloudwatch Logs +pullLog <- jsonlite::fromJSON('log_run_all.json')['results']$results %>% + purrr::map(function(x) tidyr::pivot_wider(x,names_from=field)) %>% + bind_rows() %>% + mutate(date = lubridate::date(date), + calls = as.integer(calls), + calls_2xx = as.integer(calls_2xx)) +``` -#### Specific API Calls +In the last 8 months, there have been a total of `r p(sum(pullLog$calls_2xx))` calls to the Neotoma API. These include calls to the core API ([`api.neotomadb.org`](https://api.neotomadb.org)), calls to support the Neotoma Landing Pages ([`data.neotomadb.org`](https://data.neotomadb.org)) and calls to support Neotoma Explorer ([`apps.neotomadb.org/explorer`](https://data.neotomadb.org)). -```{r callFrequency, echo=FALSE, warning=FALSE} + + + + +```{r callFrequency, echo=FALSE, eval=FALSE, warning=FALSE} +# The main APIs delivered a total of `r p(floor(sum(pullLog$volume, na.rm=TRUE) /1000000000))` GB of data to users since `r min(pullLog$date)`. + +#### Specific API Calls ggplot(pullCalls[1:20,]) + geom_bar(aes(x = 1:20, y=fullcount/1000), stat='identity') + @@ -276,9 +295,9 @@ ggplot(pullCalls[1:20,]) + theme(axis.text.x=element_blank()) ``` -Several API calls are called thousands of times, but these are not necessarily the fastest, or slowest queries. There is no relationship between speed and the number of times an API endpoint is used. The most frequent API calls over the past week are: +```{r freqCall, echo=FALSE, eval=FALSE} -```{r freqCall, echo=FALSE} +# Several API calls are called thousands of times, but these are not necessarily the fastest, or slowest queries. There is no relationship between speed and the number of times an API endpoint is used. The most frequent API calls over the past week are: pullCalls %>% slice_max(fullcount, n = 20) %>% select(path, fullcount) %>% diff --git a/StateoftheDB.html b/StateoftheDB.html index d692ddb..e5ba390 100644 --- a/StateoftheDB.html +++ b/StateoftheDB.html @@ -10,7 +10,7 @@ - + State of the Neotoma Paleoecology Database @@ -2509,7 +2509,7 @@ }; }, renderValue: function(el, data, instance) { - if (el.offsetWidth === 0 || el.offsetHeight === 0) { + if ((el.offsetWidth === 0 || el.offsetHeight === 0) && data.lazyRender !== false) { instance.data = data; return; } @@ -8581,11 +8581,15 @@

State of the Neotoma Paleoecology Database

-

Simon Goring

-goring@wisc.edu +

Socorro Dominguez

+
+Department of Geography, University of +Wisconsin–Madison
dominguezvid@wisc.edu
-

true

-

2025-05-15

+

Simon Goring

+
+Department of Geography, University of +Wisconsin–Madison

2026-07-13

@@ -8596,21 +8600,21 @@

1 Data Summary

1.1 Overall Database Summary

This report details changes to the Neotoma Paleoecology database since -2024-05-15, and is current up to -2025-05-15. Full documentation of the database can be +2025-07-13, and is current up to +2026-07-13. Full documentation of the database can be found in the Neotoma Database Manual. Recent snapshots of the database can be obtained from the Neotoma Snapshot website. This report is generated automatically from an RMarkdown document hosted on GitHub.

-

Neotoma contains data from 53,715 datasets and 26,042 unique sites. +

Neotoma contains data from 61883 datasets and 31572 unique sites. This represents a considerable contribution from members of the -scientific community, including 4,358 primary investigators, 1,348 -analysts, and stewards for all 41 constituent databases. There are also +scientific community, including 4981 primary investigators, 1392 +analysts, and stewards for all 44 constituent databases. There are also invaluable and incalculable contributions from the members of the Neotoma Paleoecology Database Community.

-
- +
+

1.1.1 Recent Data Updates

@@ -8618,8 +8622,8 @@

1.1.1 Recent Data

1.1.1.1 Site Additions

-
- +
+

Figure 1. Locations of newly added sites in Neotoma during the past year. The map is interactive and supports zoom/pan @@ -8628,8 +8632,8 @@

1.1.1.1 Site Explorer.

-

Of the 3,749 sites added, 50 have been entered as polygons, while -3,699 are entered as single coordinate points. In general polygons +

Of the 5,189 sites added, 96 have been entered as polygons, while +5,093 are entered as single coordinate points. In general polygons provide more complete information about the site, often representing the particular shape of the depositional environment (lake, archaeological site).

@@ -8638,17 +8642,17 @@

1.1.1.1 Site

1.1.2 Dataset Additions

-
- +
+

Of the datasets added to Neotoma over the past year, there have been -contributions to 15 constituent databases, with the majority from North -American Pollen Database. This pattern of contribution is reflected in -contributions to dataset types, where we see contributions to 24 dataset -types.

-
- +contributions to 18 constituent databases, with the majority from +Nonmarine Ostracod Distribution in Europe Database. This pattern of +contribution is reflected in contributions to dataset types, where we +see contributions to 24 dataset types.

+
+
-Dataset contributions to Neotoma over the previous 18 months. The large number of Neotoma dataset types makes color coding difficult, however results are detailed specifically in Table 1. +Dataset contributions to Neotoma over the previous 18 months. The large number of Neotoma dataset types makes color coding difficult, however results are detailed specifically in Table 1.

Dataset contributions to Neotoma over the previous 18 months. The large number of Neotoma dataset types makes color coding difficult, however @@ -8659,38 +8663,24 @@

1.1.2 Dataset

1.1.3 Constituent Databases

-

Neotoma consists of 41 constituent databases. At any one time some +

Neotoma consists of 44 constituent databases. At any one time some databases may be more active than others.

1.1.4 Contributors

-
- +
+

Neotoma relies on significant the efforts of a volunteer group of -data stewards and data contributors. Over the last 12 months 24 stewards -have contributed data to Neotoma, across a range of constituent +data stewards and data contributors. Over the last 12 months 328 +stewards have contributed data to Neotoma, across a range of constituent databases.

1.1.5 API Calls

-

-

Since the API has been implemented there have been a total of 432,370 -calls to the Neotoma API. These include calls to the core API (api.neotomadb.org), +

In the last 8 months, there have been a total of 4,270,195 calls to +the Neotoma API. These include calls to the core API (api.neotomadb.org), calls to support the Neotoma Landing Pages (data.neotomadb.org) and calls to support Neotoma Explorer (apps.neotomadb.org/explorer).

-

The main APIs delivered a total of 1 GB of data to users since -2025-05-08.

-
-

1.1.5.1 Specific API -Calls

-

-

Several API calls are called thousands of times, but these are not -necessarily the fastest, or slowest queries. There is no relationship -between speed and the number of times an API endpoint is used. The most -frequent API calls over the past week are:

-
- -

@@ -8698,17 +8688,17 @@

1.2 Data Overview

1.2.1 Site Spatial Types

-

Sites can be added as either points or polygons. Of the 3,749 sites -added, 50 of those are entered as site polygons, while 3,699 are entered +

Sites can be added as either points or polygons. Of the 5,189 sites +added, 96 of those are entered as site polygons, while 5,093 are entered as single coordinate points. In general polygons provide more complete information about the site, often representing the particular shape of the depositional environment (lake, archaeological site).

1.2.2 Site Metadata

-
- -

Among the 3,749 sites added to the Neotoma Paleoecology Database in +

+ +

Among the 5,189 sites added to the Neotoma Paleoecology Database in the past year, not all sites were entered with complete metadata. Complete metadata is critical for better understanding data context, particularly when site notes & descriptions are required to better @@ -8716,13 +8706,13 @@

1.2.2 Site Metadata

1.2.2.1 Dataset Metadata

-
- +
+

1.2.3 Taxon Overview

-

There are 47,682 taxa recorded in the Neotoma Taxonomy table. These +

There are 58988 taxa recorded in the Neotoma Taxonomy table. These are not exclusively taxonomic records, but include other variables, such as laboratory measurements and other detected features within samples.

@@ -8742,8 +8732,8 @@
1.2.3.1.1 Highest-Level

The highest-level taxa can be identified because they have taxonid==highertaxonid. Within the database there are 29 highest level taxa:

-
- +
+

This table is provided largely for information, to help identify records that are identified as “highest level”, that should be otherwise grouped.

@@ -8751,24 +8741,24 @@
1.2.3.1.1 Highest-Level
1.2.3.1.2 Taxa with no relationships
-

There are 38,831 taxa that represent “leaves” in the Neotoma taxon -tree. Of these, 10,406 have no recorded observations within the database +

There are 47,507 taxa that represent “leaves” in the Neotoma taxon +tree. Of these, 17,761 have no recorded observations within the database (the taxonid does not appear in the ndb.variables table). These are taxa that are not part of a morpohotaxonomic hierarchy (so there are no dependent taxa), and also have no associated sample records:

-
- +
+
1.2.3.1.3 Taxa with Undefined Higher Taxa

Some taxa do not have defined highertaxonid values. -Currently there is a count of 2837 taxa without defined higher taxon +Currently there is a count of 2913 taxa without defined higher taxon IDs. It is unclear why these taxa do not have related higher taxonomic elements.

-
- +
+
@@ -8777,11 +8767,11 @@

1.2.3.2 Duplicated

Taxa are identified by taxonname and taxagroupid. There are instances of duplicate taxonname, but these should be represented by distinct -taxagroupid values. There are 78 taxa where the +taxagroupid values. There are 86 taxa where the taxonname is duplicated (and the taxon is valid).

-
- +
+
1.2.3.2.1 Duplicated Taxon Codes
@@ -8790,8 +8780,8 @@
1.2.3.2.1 Duplicated instances where a taxon code is repeated within the same group. The following taxon identifiers are repeated multiple times within an ecological group:

-
- +
+

@@ -8813,15 +8803,15 @@

1.2.3.3 Taxon validtaxonid and invalidtaxonid in ndb.synonyms to the taxonid and reftaxonid of ndb.synonymy.

-

The database currently contains 10,479 datasets with synonymys, and a -total of 2,825 attributed synonyms. Of the synonyms with associated -datastids, there are 853 synonymys without links in the synonyms table. +

The database currently contains 12602 datasets with synonymys, and a +total of 2909 attributed synonyms. Of the synonyms with associated +datastids, there are 854 synonymys without links in the synonyms table. There are 1 synonyms where there is no attributed contactid or publication.

There are 214 synonymys where multiple different publications are -used to attribute the synonymy. There are also 532 where multiple +used to attribute the synonymy. There are also 539 where multiple different individuals are identified as assigning the synonym. There are -1,466 synonyms without any associated publication.

+1,505 synonyms without any associated publication.

1.2.3.4 Duplicated @@ -8831,13 +8821,13 @@

1.2.3.4 Duplicated expect that these should ever be duplicated, since we can use the same variable ID over and over again, for the given combination. Having said that, we do see replication, and it’s not clear why.

-
- -

In 0 variables we see that there is duplication of the keys in the -variableids. Interestingly it seems that this is an issue -that primarily affects the mammal records:

-
- +
+ +

In 5,829 variables we see that there is duplication of the keys in +the variableids. Interestingly it seems that this is an +issue that primarily affects the mammal records:

+
+

The ground sloth Paramylodon harlani seems to have the biggest issues. Some possible reasons for this larger issue may be associated with the ways “specimens” are added to the database, @@ -8850,11 +8840,11 @@

1.2.4 Sites and Datasets

Issues with sites include sites with no associated datasets, duplicated sites and, potentially, sites with missing data.

-

When we examine sites, we find that there are 902 sites with +

When we examine sites, we find that there are 1,288 sites with exactly duplicated site geometries. These sites are distributed globally, and distributed across constituent databases.

-
- +
+

1.2.4.1 Sites without CollectionUnits or Datasets

@@ -8874,8 +8864,8 @@

1.2.4.2 Sites without analysis units

Some sites appear to have been submitted, with collection units but no registered analysis units associated with them:

-
- +
+

This is also likely the result of failed uploads during the Tilia upload process. To ensure that these records are properly cleaned we need to validate that there are collection units and datasets associated @@ -8887,7 +8877,7 @@

1.2.4.2 Sites without

1.2.5 Stewards & Tilia Usage

-

+

A total of 2,029 calls to the Tilia API were made since 2025-05-13.

diff --git a/buildStats.sh b/buildStats.sh index f6dc854..e8ca909 100644 --- a/buildStats.sh +++ b/buildStats.sh @@ -1,25 +1,28 @@ #!/bin/bash -bash run_cloudwatchquery.sh +# Need to run after I fix api_nodetest to send the logs to cloudwatch +# bash run_cloudwatchquery.sh +#bash run cloudwatchquery_partial.sh + +# Load the database connection variables (DBNAME, HOST, PORT, USER, PASSWORD) +# from the .env file rather than hardcoding them here. +if [ -f .env ]; then + set -a + source .env + set +a +else + echo "No .env file found. Copy .env-template to .env and set your values." >&2 + exit 1 +fi if [ "$1" == "local" ]; then - echo Running against the local DB. - export DBNAME=neotoma - export HOST=localhost - export PORT=5435 - export USER=postgres - export PASSWORD=postgres + echo "Running against the local DB ($USER@$HOST:$PORT/$DBNAME)." Rscript -e "rmarkdown::render('StateoftheDB.Rmd')" else - echo Running against the remote. - export DBNAME=neotoma - export HOST=localhost - export PORT=5555 - export USER=neotomaAdmin - export PASSWORD=REDACTED + echo "Running against the remote ($USER@$HOST:$PORT/$DBNAME)." Rscript -e "rmarkdown::render('StateoftheDB.Rmd')" git add --all git commit -m "Running the build" git push fi -echo Done. \ No newline at end of file +echo Done. diff --git a/log_run_all.json b/log_run_all.json new file mode 100644 index 0000000..1a29a86 --- /dev/null +++ b/log_run_all.json @@ -0,0 +1,8861 @@ +{ + "results": [ + [ + { + "field": "date", + "value": "2025-11-09" + }, + { + "field": "calls", + "value": "385" + }, + { + "field": "calls_2xx", + "value": "227" + }, + { + "field": "service", + "value": "neoapi-prod" + } + ], + [ + { + "field": "date", + "value": "2025-11-10" + }, + { + "field": "calls", + "value": "20882" + }, + { + "field": "calls_2xx", + "value": "17393" + }, + { + "field": "service", + "value": "neoapi-prod" + } + ], + [ + { + "field": "date", + "value": "2025-11-10" + }, + { + "field": "calls", + "value": "4901" + }, + { + "field": "calls_2xx", + "value": "4857" + }, + { + "field": "service", + "value": "neoapi-tprod" + } + ], + [ + { + "field": "date", + "value": "2025-11-11" + }, + { + "field": "calls", + "value": "12428" + }, + { + "field": "calls_2xx", + "value": "10958" + }, + { + "field": "service", + "value": "neoapi-prod" + } + ], + [ + { + "field": "date", + "value": "2025-11-11" + }, + { + "field": "calls", + "value": "5692" + }, + { + "field": "calls_2xx", + "value": "5326" + }, + { + "field": "service", + "value": "neoapi-tprod" + } + ], + [ + { + "field": "date", + "value": "2025-11-12" + }, + { + "field": "calls", + "value": "10545" + }, + { + "field": "calls_2xx", + "value": "8804" + }, + { + "field": "service", + "value": "neoapi-prod" + } + ], + [ + { + "field": "date", + "value": "2025-11-12" + }, + { + "field": "calls", + "value": "2084" + }, + { + "field": "calls_2xx", + "value": "2054" + }, + { + "field": "service", + "value": "neoapi-tprod" + } + ], + [ + { + "field": "date", + "value": "2025-11-13" + }, + { + "field": "calls", + "value": "13755" + }, + { + "field": "calls_2xx", + "value": "11721" + }, + { + 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"calls", + "value": "14976" + }, + { + "field": "calls_2xx", + "value": "11706" + }, + { + "field": "service", + "value": "neoapi-prod" + } + ], + [ + { + "field": "date", + "value": "2026-07-08" + }, + { + "field": "calls", + "value": "1486" + }, + { + "field": "calls_2xx", + "value": "1086" + }, + { + "field": "service", + "value": "neoapi-tprod" + } + ], + [ + { + "field": "date", + "value": "2026-07-09" + }, + { + "field": "calls", + "value": "12129" + }, + { + "field": "calls_2xx", + "value": "9180" + }, + { + "field": "service", + "value": "neoapi-prod" + } + ], + [ + { + "field": "date", + "value": "2026-07-09" + }, + { + "field": "calls", + "value": "1573" + }, + { + "field": "calls_2xx", + "value": "1379" + }, + { + "field": "service", + "value": "neoapi-tprod" + } + ], + [ + { + "field": "date", + "value": "2026-07-10" + }, + { + "field": "calls", + "value": "10031" + }, + { + "field": "calls_2xx", + "value": "6895" + }, + { + "field": "service", + "value": "neoapi-prod" + } + ], + [ + { + "field": "date", + "value": "2026-07-10" + }, + { + "field": "calls", + "value": "107" + }, + { + "field": "calls_2xx", + "value": "79" + }, + { + "field": "service", + "value": "neoapi-tprod" + } + ], + [ + { + "field": "date", + "value": "2026-07-11" + }, + { + "field": "calls", + "value": "8589" + }, + { + "field": "calls_2xx", + "value": "7241" + }, + { + "field": "service", + "value": "neoapi-prod" + } + ], + [ + { + "field": "date", + "value": "2026-07-11" + }, + { + "field": "calls", + "value": "927" + }, + { + "field": "calls_2xx", + "value": "908" + }, + { + "field": "service", + "value": "neoapi-tprod" + } + ], + [ + { + "field": "date", + "value": "2026-07-12" + }, + { + "field": "calls", + "value": "29165" + }, + { + "field": "calls_2xx", + "value": "22949" + }, + { + "field": "service", + "value": "neoapi-prod" + } + ], + [ + { + "field": "date", + "value": "2026-07-12" + }, + { + "field": "calls", + "value": "6345" + }, + { + "field": "calls_2xx", + "value": "5904" + }, + { + "field": "service", + "value": "neoapi-tprod" + } + ], + [ + { + "field": "date", + "value": "2026-07-13" + }, + { + "field": "calls", + "value": "25" + }, + { + "field": "calls_2xx", + "value": "23" + }, + { + "field": "service", + "value": "neoapi-prod" + } + ] + ], + "status": "Complete" +} diff --git a/outputs/datasetsPerMonth.png b/outputs/datasetsPerMonth.png index 6f65f0e..b19e480 100644 Binary files a/outputs/datasetsPerMonth.png and b/outputs/datasetsPerMonth.png differ diff --git a/outputs/datasetsPerMonth.svg b/outputs/datasetsPerMonth.svg index 0bbbc45..c19807d 100644 --- a/outputs/datasetsPerMonth.svg +++ b/outputs/datasetsPerMonth.svg @@ -1,5 +1,6 @@ - + + @@ -23,236 +28,257 @@ - - + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + -0 -500 -1000 -1500 - - - - - - - -Jan 2024 -Jul 2024 -Jan 2025 -Month -Number of Datasets Uploaded -Dataset Type - - - - - - - - - - - - - - - - - - -biomarker -charcoal -chironomid -diatom -geochemistry -geochronologic -insect -Lead210 -LOI -macroinvertebrate -ostracode -sedimentology -plant macrofossil -pollen -stable isotope -testate amoebae -vertebrate fauna -water chemistry +0 +2000 +4000 + + + + + + + +Jan 2025 +Jul 2025 +Jan 2026 +Jul 2026 +Month +Number of Datasets Uploaded +Dataset Type + + + + + + + + + + + + + + + + + + + + +biomarker +charcoal +chironomid +diatom +diatom bottom sample +diatom top-bottom +geochemistry +geochronologic +insect +Lead210 +LOI +ostracode +sedimentology +plant macrofossil +pollen +speleothem +stable isotope +testate amoebae +vertebrate fauna +water chemistry + diff --git a/requirements-src.R b/requirements-src.R index 18fe6f6..1c97085 100644 --- a/requirements-src.R +++ b/requirements-src.R @@ -3,7 +3,7 @@ pacman::p_load( forcats, rmarkdown, purrr, - RPostgreSQL, + RPostgres, DT, ggplot2, ggthemes, diff --git a/run_cloudwatchquery_partial.sh b/run_cloudwatchquery_partial.sh new file mode 100644 index 0000000..52a463b --- /dev/null +++ b/run_cloudwatchquery_partial.sh @@ -0,0 +1,45 @@ +#!/bin/bash +## API calls per day, per service (Neotoma API prod and Tilia prod). +## The API moved to App Runner, which does not emit the nginx access logs the +## other queries parse, so this uses the AWS/AppRunner "Requests" metric (total) +## and "2xxStatusResponses" (successful calls, comparable to the old status=200 +## filter) instead. + +start=`date -u -v-1y +"%Y-%m-%dT%H:%M:%SZ"` +end=`date -u +"%Y-%m-%dT%H:%M:%SZ"` + +points='[]' +for svc in neoapi-prod neoapi-tprod; do + svcId=$(aws apprunner list-services \ + --query "ServiceSummaryList[?ServiceName=='$svc'].ServiceId" --output text) + req=$(aws cloudwatch get-metric-statistics \ + --namespace AWS/AppRunner \ + --metric-name Requests \ + --dimensions Name=ServiceName,Value=$svc Name=ServiceID,Value=$svcId \ + --start-time $start --end-time $end --period 86400 --statistics Sum \ + --query 'Datapoints[].{date:Timestamp, calls:Sum}' --output json) + ok=$(aws cloudwatch get-metric-statistics \ + --namespace AWS/AppRunner \ + --metric-name 2xxStatusResponses \ + --dimensions Name=ServiceName,Value=$svc Name=ServiceID,Value=$svcId \ + --start-time $start --end-time $end --period 86400 --statistics Sum \ + --query 'Datapoints[].{date:Timestamp, calls_2xx:Sum}' --output json) + svcpoints=$(jq -s --arg svc "$svc" '(.[0] + .[1]) | map(. + {service: $svc})' \ + <(printf '%s' "$req") <(printf '%s' "$ok")) + points=$(jq -s '.[0] + .[1]' <(printf '%s' "$points") <(printf '%s' "$svcpoints")) +done + +## One row per day and service, written in the same format as the other +## log_run*.json files (fields: date, calls, calls_2xx, service). +printf '%s' "$points" | jq ' + group_by([.date[0:10], .service]) + | map({date: .[0].date[0:10], + service: .[0].service, + calls: (map(.calls // 0) | add | floor), + calls_2xx: (map(.calls_2xx // 0) | add | floor)}) + | sort_by([.date, .service]) + | {results: map([{field: "date", value: .date}, + {field: "calls", value: (.calls | tostring)}, + {field: "calls_2xx", value: (.calls_2xx | tostring)}, + {field: "service", value: .service}]), + status: "Complete"}' > log_run_all.json