From bb0ef4a11c5006737ba22c9ce601148bfc5c4ed1 Mon Sep 17 00:00:00 2001 From: Jesse Mortenson Date: Wed, 18 Sep 2024 17:33:48 -0500 Subject: [PATCH 1/5] Add doc on querying scraper output using DuckDB --- .python-version | 1 + .../contributing/query-scraper-output-data.md | 230 ++++++++++++++++++ docs/contributing/scrapers.md | 4 + 3 files changed, 235 insertions(+) create mode 100644 .python-version create mode 100644 docs/contributing/query-scraper-output-data.md diff --git a/.python-version b/.python-version new file mode 100644 index 0000000..475ba51 --- /dev/null +++ b/.python-version @@ -0,0 +1 @@ +3.7 diff --git a/docs/contributing/query-scraper-output-data.md b/docs/contributing/query-scraper-output-data.md new file mode 100644 index 0000000..c0635a2 --- /dev/null +++ b/docs/contributing/query-scraper-output-data.md @@ -0,0 +1,230 @@ +# How to query and examine data file output created by scrapers + +This document is aimed to help with scraper development and data debugging. + +Open States scrapers typically produce a set of output data files in the JSON format. Each file represents a primary +entity that the scraper has produced, such as a Bill, an Event or a Vote Event. When working on scraper code, it can +be really helpful to examine this output for data quality issues. + +## Simple examination + +The JSON format is relatively easy to view in any text editor or Integrated Development Environment (IDE). This makes +it easy to examine a specific output file. + +And you can take it a step further by using a tool like [jq](https://jqlang.github.io/jq/) to query the JSON document +so that you only see the attributes that are relevant to you. For example: + +```shell +cat vote_event_ff4ae3ef-656f-11ef-8b4c-732c295f582c.json | jq .counts +``` + +## Querying a full set of scraper output files + +But what if you want to check data quality issues that might be distributed across the output, which may consist of +thousands of data points? You can put together shell scripts/commands that iterate through and find certian files, +then parse them with `jq`. But this can be tricky, especially if you are not familiar with advanced shell scripting. + +The good news is that, if you are familiar with SQL, there is a way to treat a set of scraper output files like a +database and use SQL to query that database. A tool called [DuckDB](https://duckdb.org/) makes this possible. + +Let's assume I've run one or more scrapers for Delaware. I open my terminal and look at the scraper output directory, +`_data/de`. There are over 3000 JSON files in that folder, so it would be painful to spot check lots of files: + +``` +jesse@work:~/repo/openstates/openstates-scrapers/scrapers/_data/de$ ls -alh | grep ".json" | wc -l +3760 +``` + +However, installing the DuckDB tool allows me to use it inside that folder to query the Bills data: + +``` +jesse@work:~/repo/openstates/openstates-scrapers/scrapers/_data/de$ duckdb +v0.10.2 1601d94f94 +Enter ".help" for usage hints. +Connected to a transient in-memory database. +Use ".open FILENAME" to reopen on a persistent database. +D SELECT * FROM read_json('bill_*.json'); +``` + +Running `duckdb` in this way opens a "transient" database, meaning that anything you do will be gone once you close +the `duckdb` terminal (by using the `ctrl+d` keystroke). If you want to save anything you create in your session, +instead open it with a file that will save those Views/Tables: `duckdb scraper_output.db` + +You can see the data schema that DuckDB has identified from the JSON files by using `DESCRIBE`: + +``` +D DESCRIBE SELECT * FROM read_json('bill_*.json'); +┌─────────────────────┬──────────────────────────────────────────────────────────────────────────────────────────────┬─────────┬─────────┬─────────┬─────────┐ +│ column_name │ column_type │ null │ key │ default │ extra │ +│ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ +├─────────────────────┼──────────────────────────────────────────────────────────────────────────────────────────────┼─────────┼─────────┼─────────┼─────────┤ +│ legislative_session │ VARCHAR │ YES │ │ │ │ +│ identifier │ VARCHAR │ YES │ │ │ │ +│ title │ VARCHAR │ YES │ │ │ │ +│ from_organization │ VARCHAR │ YES │ │ │ │ +│ classification │ VARCHAR[] │ YES │ │ │ │ +│ subject │ JSON[] │ YES │ │ │ │ +│ abstracts │ STRUCT(note VARCHAR, abstract VARCHAR)[] │ YES │ │ │ │ +│ other_titles │ STRUCT(note VARCHAR, title VARCHAR)[] │ YES │ │ │ │ +│ other_identifiers │ JSON[] │ YES │ │ │ │ +│ actions │ STRUCT(description VARCHAR, date DATE, organization_id VARCHAR, classification VARCHAR[], … │ YES │ │ │ │ +│ sponsorships │ STRUCT("name" VARCHAR, classification VARCHAR, entity_type VARCHAR, "primary" BOOLEAN, per… │ YES │ │ │ │ +│ related_bills │ JSON[] │ YES │ │ │ │ +│ versions │ STRUCT(note VARCHAR, links STRUCT(url VARCHAR, media_type VARCHAR)[], date VARCHAR, classi… │ YES │ │ │ │ +│ documents │ STRUCT(note VARCHAR, links STRUCT(url VARCHAR, media_type VARCHAR)[], date VARCHAR, classi… │ YES │ │ │ │ +│ citations │ STRUCT("publication" VARCHAR, citation VARCHAR, citation_type VARCHAR, effective JSON, exp… │ YES │ │ │ │ +│ sources │ STRUCT(url VARCHAR, note VARCHAR)[] │ YES │ │ │ │ +│ extras │ JSON │ YES │ │ │ │ +│ _id │ UUID │ YES │ │ │ │ +├─────────────────────┴──────────────────────────────────────────────────────────────────────────────────────────────┴─────────┴─────────┴─────────┴─────────┤ +│ 18 rows 6 columns │ +└────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘ +``` + +You'll notice that related entities like Bill Actions, Bill Sponsorships, etc... are embedded in the data as `STRUCT` +data, usually as a list (`STRUCT(property_a VARCHAR, property_b VARCHAR)[]`). We can drill down into those. + +### Use views to drill into the data + +To make this data structure simpler to reason about, we can use Views. Here's a set of recommended views you can try: + +```sql +-- Bills +CREATE VIEW bills AS +SELECT * +FROM read_json('bill_*.json'); +CREATE VIEW bill_actions AS +SELECT legislative_session, identifier AS bill_identifier, _id AS bill_id, unnest(actions, recursive := true) +FROM bills; +CREATE VIEW bill_action_classifications AS +SELECT legislative_session, bill_identifier, bill_id, unnest(classification) AS classification +FROM bill_actions; +CREATE VIEW bill_sponsorships AS +SELECT legislative_session, identifier AS bill_identifier, _id AS bill_id, unnest(sponsorships, recursive := true) +FROM bills; +CREATE VIEW bill_versions AS +SELECT legislative_session, identifier AS bill_identifier, _id AS bill_id, unnest(versions, recursive := true) +FROM bills; +CREATE VIEW bill_version_links AS +SELECT legislative_session, bill_identifier, bill_id, unnest(links, recursive := true) +FROM bill_versions; + +-- Vote Events +CREATE VIEW vote_events AS +SELECT * +FROM read_json('vote_event_*.json'); +CREATE VIEW vote_event_votes AS +SELECT legislative_session, + bill_identifier, + identifier AS vote_identifier, + _id AS vote_id, + unnest(votes, recursive := true) +FROM vote_events; +CREATE VIEW vote_event_counts AS +SELECT legislative_session, + bill_identifier, + identifier AS vote_identifier, + _id AS vote_id, + unnest(counts, recursive := true) +FROM vote_events; +``` + +To view Views in your DuckDB database: `SHOW TABLES;` + +### Useful queries + +These queries will assume you've created the views listed above. + +General utility: describe the shape of a given dataset: + +```sql +DESCRIBE SELECT * FROM bills; +DESCRIBE SELECT * FROM vote_events; +``` + +### Bills + +#### Bills that are missing a property that is a list (abstracts, actions, sponsorships, etc.) + +```sql +SELECT (len(abstracts) > 0) AS has_abstract, COUNT(*) +FROM bills +GROUP BY 1; +SELECT (len(sponsorships) > 0) AS has_sponsorship, COUNT(*) +FROM bills +GROUP BY 1; +SELECT (len(related_bills) > 0) AS has_related_bills, COUNT(*) +FROM bills +GROUP BY 1; +``` + +#### Distribution of bill classifications + +```sql +SELECT classification, COUNT(*) +FROM bills +GROUP BY classification; +``` + +#### Distribution of bill action classifications + +```sql +SELECT classification, COUNT(*) +FROM bill_action_classifications +GROUP BY 1; +``` + +#### Bill actions that are unclassified + +```sql +SELECT (classification = []) AS action_is_unclassified, COUNT(*) +FROM bill_actions +GROUP BY 1; +``` + +#### Bill version media type distribution + +```sql +SELECT media_type, COUNT(*) +FROM bill_version_links +GROUP BY 1; +``` + +### Vote Events + +#### Vote Events over time (by month) + +```sql +SELECT date_trunc('month', start_date), COUNT(*) +FROM vote_events +GROUP BY 1, +ORDER BY 1; +``` + +#### Vote events with zero or unexpected number of votes + +```sql +SELECT len(votes) AS num_votes, COUNT(*) AS events_with_this_number +FROM vote_events +GROUP BY 1 +ORDER BY 1 DESC; +``` + +or check via count values for vote events where all counts are zero + +```sql +SELECT vote_id, SUM(value) +FROM vote_event_counts +GROUP BY 1 +HAVING SUM(value) = 0; +``` + +#### Vote event counts check distribution for anomalies + +```sql +SELECT +option, value, COUNT (*) +FROM vote_event_counts +GROUP BY 1, 2 +ORDER BY 1, 2 DESC; +``` \ No newline at end of file diff --git a/docs/contributing/scrapers.md b/docs/contributing/scrapers.md index 1a2ea07..a17c63a 100644 --- a/docs/contributing/scrapers.md +++ b/docs/contributing/scrapers.md @@ -149,6 +149,10 @@ directory and inspect the JSON files. If you're trying to make a small fix this is often sufficient, you can confirm that the scraped data looks correct and move on. +Please see our document on [Querying Scraper Output Data](./query-scraper-output-data.md) +for tools you can use to investigate data issues across a set of many +scraped data output files. + !!! note It is of course possible that the scrape fails. If so, there's a good From b98be143d4cf5a14b3b3d9529d47e5a5ff777c93 Mon Sep 17 00:00:00 2001 From: Jesse Mortenson Date: Wed, 18 Sep 2024 17:50:26 -0500 Subject: [PATCH 2/5] Pin github workflow python version to fix install issue (old dependency) --- .github/workflows/main.yml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml index 48b7e46..881d105 100644 --- a/.github/workflows/main.yml +++ b/.github/workflows/main.yml @@ -16,6 +16,8 @@ jobs: submodules: true - name: setup Python uses: actions/setup-python@v2 + with: + python-version: '3.7' - name: install Poetry uses: snok/install-poetry@v1.2.1 - name: set poetry config path From e864d25fcd976ef86f28f94fc0f7c9d63af4f848 Mon Sep 17 00:00:00 2001 From: Jesse Mortenson Date: Wed, 18 Sep 2024 18:04:18 -0500 Subject: [PATCH 3/5] Attempt to upgrade env and github build somewhat --- .github/workflows/main.yml | 6 +- .python-version | 2 +- docs/contributing/scrapers.md | 2 +- .../query-scraper-output-data.md | 0 mkdocs.yml | 1 + poetry.lock | 798 +++++++++++------- pyproject.toml | 8 +- 7 files changed, 506 insertions(+), 311 deletions(-) rename docs/{contributing => data}/query-scraper-output-data.md (100%) diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml index 881d105..84ea8ef 100644 --- a/.github/workflows/main.yml +++ b/.github/workflows/main.yml @@ -11,15 +11,15 @@ jobs: build: steps: # Python & dependency installation - - uses: actions/checkout@v2 + - uses: actions/checkout@v4 with: submodules: true - name: setup Python uses: actions/setup-python@v2 with: - python-version: '3.7' + python-version: '3.9' - name: install Poetry - uses: snok/install-poetry@v1.2.1 + uses: snok/install-poetry@v1.4.1 - name: set poetry config path run: poetry config virtualenvs.path ~/.virtualenvs - name: install dependencies diff --git a/.python-version b/.python-version index 475ba51..bd28b9c 100644 --- a/.python-version +++ b/.python-version @@ -1 +1 @@ -3.7 +3.9 diff --git a/docs/contributing/scrapers.md b/docs/contributing/scrapers.md index a17c63a..62cec2d 100644 --- a/docs/contributing/scrapers.md +++ b/docs/contributing/scrapers.md @@ -149,7 +149,7 @@ directory and inspect the JSON files. If you're trying to make a small fix this is often sufficient, you can confirm that the scraped data looks correct and move on. -Please see our document on [Querying Scraper Output Data](./query-scraper-output-data.md) +Please see our document on [Querying Scraper Output Data](../data/query-scraper-output-data.md) for tools you can use to investigate data issues across a set of many scraped data output files. diff --git a/docs/contributing/query-scraper-output-data.md b/docs/data/query-scraper-output-data.md similarity index 100% rename from docs/contributing/query-scraper-output-data.md rename to docs/data/query-scraper-output-data.md diff --git a/mkdocs.yml b/mkdocs.yml index 91b931c..1a5131d 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -76,6 +76,7 @@ nav: - 'contributing/documentation.md' - Data: - 'data/index.md' + - 'data/query-scraper-output-data.md' - 'data/categorization.md' - 'data/session-naming.md' - Enhancement Proposals: diff --git a/poetry.lock b/poetry.lock index f54fb1e..e6d2a16 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,61 +1,204 @@ +# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand. + +[[package]] +name = "certifi" +version = "2024.8.30" +description = "Python package for providing Mozilla's CA Bundle." +optional = false +python-versions = ">=3.6" +files = [ + {file = "certifi-2024.8.30-py3-none-any.whl", hash = "sha256:922820b53db7a7257ffbda3f597266d435245903d80737e34f8a45ff3e3230d8"}, + {file = "certifi-2024.8.30.tar.gz", hash = "sha256:bec941d2aa8195e248a60b31ff9f0558284cf01a52591ceda73ea9afffd69fd9"}, +] + +[[package]] +name = "charset-normalizer" +version = "3.3.2" +description = "The Real First Universal Charset Detector. 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authors = ["James Turk "] [tool.poetry.dependencies] -python = "^3.7" -mkdocs-material = "^8.0.1" +python = "^3.9" +mkdocs-material = "^8.5.11" [tool.poetry.dev-dependencies] [build-system] -requires = ["poetry>=0.12"] -build-backend = "poetry.masonry.api" +requires = ["poetry-core>=1.0.0"] +build-backend = "poetry.core.masonry.api" From 06feb7e390b2eceb46646f3b2c71ac5f8c03c8d3 Mon Sep 17 00:00:00 2001 From: Jesse Mortenson Date: Thu, 26 Sep 2024 16:45:29 -0500 Subject: [PATCH 4/5] Emphasize need to create the View before using it in queries --- docs/data/query-scraper-output-data.md | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/docs/data/query-scraper-output-data.md b/docs/data/query-scraper-output-data.md index c0635a2..2f74232 100644 --- a/docs/data/query-scraper-output-data.md +++ b/docs/data/query-scraper-output-data.md @@ -86,7 +86,9 @@ data, usually as a list (`STRUCT(property_a VARCHAR, property_b VARCHAR)[]`). We ### Use views to drill into the data -To make this data structure simpler to reason about, we can use Views. Here's a set of recommended views you can try: +To make this data structure simpler to reason about, we can use Views. Here's a set of recommended views you can try. +Please note that these views are used in many of the suggested queries below. In order to execute a query that uses +a view, you need to create the view first! ```sql -- Bills @@ -133,7 +135,7 @@ To view Views in your DuckDB database: `SHOW TABLES;` ### Useful queries -These queries will assume you've created the views listed above. +These queries will assume you've created the Views listed above! Execute the Views queries above before trying these! General utility: describe the shape of a given dataset: From e7ae8dc76fb3af016a7b6fcb5df3714d3223b399 Mon Sep 17 00:00:00 2001 From: Jesse Mortenson Date: Thu, 26 Sep 2024 18:02:30 -0500 Subject: [PATCH 5/5] Querying data: clarify properties that are sub-entities --- docs/data/query-scraper-output-data.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/docs/data/query-scraper-output-data.md b/docs/data/query-scraper-output-data.md index 2f74232..199a1a8 100644 --- a/docs/data/query-scraper-output-data.md +++ b/docs/data/query-scraper-output-data.md @@ -82,7 +82,8 @@ D DESCRIBE SELECT * FROM read_json('bill_*.json'); ``` You'll notice that related entities like Bill Actions, Bill Sponsorships, etc... are embedded in the data as `STRUCT` -data, usually as a list (`STRUCT(property_a VARCHAR, property_b VARCHAR)[]`). We can drill down into those. +data: `actions`, `sponsorships`, etc.. This is typically structured as a list of `STRUCT` data, which is like a dict +or object (`STRUCT(property_a VARCHAR, property_b VARCHAR)[]`). We can drill down into those. ### Use views to drill into the data