mirror of
https://github.com/harvard-lil/data-vault.git
synced 2025-03-15 07:31:21 +00:00
initial commit
This commit is contained in:
Jack Cushman
commit
404c3627f7
26 changed files with 2534 additions and 0 deletions
7
.gitignore
vendored
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7
.gitignore
vendored
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|||
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||||
/data/*
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||||
!/data/README.md
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||||
*.pyc
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||||
__pycache__
|
||||
.DS_Store
|
||||
|
||||
50
README.md
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50
README.md
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|
@ -0,0 +1,50 @@
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|||
This repository collects scripts to support the Library Innovation Lab's
|
||||
[public data preservation project](https://lil.law.harvard.edu/blog/2025/01/30/preserving-public-u-s-federal-data/).
|
||||
|
||||
These scripts are used as part of internal pipelines, so may not be usable
|
||||
for others as is, but are available for reference about the creation of our
|
||||
data and for remix. We also welcome contributions if they fit our internal
|
||||
pipelines and goals.
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|
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## Scripts
|
||||
|
||||
Scripts are organized into subfolders for general categories of tasks:
|
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|
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### collection
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||||
|
||||
Scripts for working with a "collection," meaning a set of files stored on
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cloud storage that were all gathered with a similar collection strategy.
|
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This folder is for scripts that apply to multiple collections rather than
|
||||
a single collection.
|
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|
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* sync.py: copy static files from collections/ to configure the collections.
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* render.py: generate static indexes of files in a collection.
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||||
* verify_upload.py: fetch and verify integrity of a BagIt archive in a collection.
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* cloudflare_tools.py: manage Cloudflare R2 buckets.
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||||
* s3_tools.py: manage S3 buckets.
|
||||
|
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### helpers
|
||||
|
||||
Util libraries used by other scripts.
|
||||
|
||||
* parallel.py: run tasks in parallel.
|
||||
* config.py: load configuration from the user's home dir.
|
||||
|
||||
### data_gov
|
||||
|
||||
Scripts for working with the [data.gov](https://data.gov) collection.
|
||||
|
||||
* fetch_jsonl.py: fetch a jsonl file of the full API.
|
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* fetch_index.py: fetch the full API and store updates in a sqlite database.
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* models.py: database models for the sqlite database.
|
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* fetch_data.py: use the sqlite database to fetch any datasets that require updating,
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package with nabit, and upload to cloud storage.
|
||||
* models.py: database models for the sqlite database.
|
||||
* data_gov_diff/: scripts for identifying changes in past data created by fetch_jsonl.py or fetch_index.py (WIP).
|
||||
|
||||
### github
|
||||
|
||||
Scripts for working with the [github](https://github.com) collection.
|
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|
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* download_git.py: use [gitspoke](https://github.com/harvard-lil/gitspoke) to download all repositories listed in a CSV.
|
||||
|
||||
1
collections/README.md
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1
collections/README.md
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|
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|
|||
Static files to be added to individual collections.
|
||||
7
collections/collections.json
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7
collections/collections.json
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|
|||
[
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||||
{
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"directory": "data_gov",
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"aws_profile": "sc",
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"s3_path": "us-west-2.opendata.source.coop/harvard-lil/gov-data"
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||||
}
|
||||
]
|
||||
119
collections/data_gov/README.md
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119
collections/data_gov/README.md
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|
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|
|||
<img src="https://data.source.coop/harvard-lil/gov-data/docs/LIL_HLSL_logos.png" alt="Harvard Law School Library Innovation Lab logo"/>
|
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|
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This is a regularly updated mirror of all data files linked from [data.gov](https://data.gov).
|
||||
|
||||
The repository is maintained by the Harvard Law School Library Innovation Lab as part
|
||||
of our [project to preserve U.S. federal public data](https://lil.law.harvard.edu/blog/2025/01/30/preserving-public-u-s-federal-data/).
|
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|
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Collection Format
|
||||
-----------------
|
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|
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Each dataset on data.gov has a unique slug known as its `name`. We store each dataset
|
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in this repository as:
|
||||
|
||||
```
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collections/data_gov/<name>/<version>.zip
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||||
```
|
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|
||||
We also store a metadata file for each dataset in the `metadata` directory:
|
||||
|
||||
```
|
||||
metadata/data_gov/<name>/<version>.json
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||||
```
|
||||
|
||||
`<version>` is a `v` followed by the number of times we have downloaded the dataset
|
||||
(v1, v2, etc.)
|
||||
|
||||
For example, the data.gov dataset [https://catalog.data.gov/dataset/fruit-and-vegetable-prices](https://catalog.data.gov/dataset/fruit-and-vegetable-prices)
|
||||
is stored in this repository as:
|
||||
|
||||
* [collections/data_gov/fruit-and-vegetable-prices/v1.zip](https://source.coop/harvard-lil/gov-data/collections/data_gov/fruit-and-vegetable-prices)
|
||||
* [metadata/data_gov/fruit-and-vegetable-prices/v1.json](https://source.coop/harvard-lil/gov-data/metadata/data_gov/fruit-and-vegetable-prices)
|
||||
|
||||
|
||||
Dataset Format
|
||||
--------------
|
||||
|
||||
Each dataset zip file is a BagIt package created by our [bag-nabit](https://github.com/harvard-lil/bag-nabit) tool.
|
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|
||||
[BagIt](https://en.wikipedia.org/wiki/BagIt) is a simple file format, established by the
|
||||
Library of Congress, consisting of a folder of metadata and text files. Our BagIt
|
||||
files follow this directory structure:
|
||||
|
||||
* `data/`
|
||||
* `files/`:
|
||||
* `...`: these are the actual files you likely want to use as a researcher,
|
||||
downloaded from the data.gov listing.
|
||||
* `headers.warc`: request and response headers from HTTP fetches for files in `files/`
|
||||
* `signed-metadata.json`: metadata including data.gov's API description of the dataset
|
||||
|
||||
The bags also contain these files, which are useful for authenticating the
|
||||
provenance of the data:
|
||||
|
||||
* `bagit.txt`: standard BagIt file
|
||||
* `bag-info.txt`: standard BagIt file
|
||||
* `manifest-sha256.txt`: standard BagIt file
|
||||
* `tagmanifest-sha256.txt`: standard BagIt file
|
||||
* `signatures/`: directory of signature files
|
||||
|
||||
Metadata File Format
|
||||
--------------------
|
||||
|
||||
Each metadata JSON file contains three main sections:
|
||||
|
||||
1. `bag_info`: Contains the BagIt metadata including:
|
||||
- Bag-Software-Agent: The version of nabit used to create the archive
|
||||
- Bagging-Date: When the archive was created
|
||||
|
||||
2. `signed_metadata`: Contains detailed information about the dataset including:
|
||||
- `id`: A UUID for this specific archive
|
||||
- `url`: The data.gov URL for the dataset
|
||||
- `description`: A brief description including the dataset title and creating organization
|
||||
- `data_gov_metadata`: The complete metadata from data.gov's API, including:
|
||||
- Dataset details (title, description, etc.)
|
||||
- Organization information
|
||||
- Resource listings
|
||||
- Tags and other metadata
|
||||
- `collection_tasks`: Records of the HTTP requests made to collect the dataset
|
||||
|
||||
3. `zip_entries`: Listing of each entry in the collection zip file, which can be used to fetch individual files from the zip file via range request without downloading the entire archive.
|
||||
|
||||
Rollup files
|
||||
------------
|
||||
|
||||
There are several rollup files at the top level to help with finding datasets
|
||||
of interest:
|
||||
|
||||
* `metadata.jsonl.zip`: zipped JSON lines file of all files contained in metadata/
|
||||
* `file_listing.jsonl.zip`: zipped JSON lines file showing the s3 listing of all files in the repository
|
||||
* `collections.html`: human-readable HTML file showing the title and link to each dataset (warning, very large file that may not load in some browsers)
|
||||
|
||||
Downloading data
|
||||
----------------
|
||||
|
||||
To download an individual dataset by name you can construct its URL, such as:
|
||||
|
||||
```
|
||||
https://source.coop/harvard-lil/gov-data/collections/data_gov/fruit-and-vegetable-prices/v1.zip
|
||||
https://source.coop/harvard-lil/gov-data/metadata/data_gov/fruit-and-vegetable-prices/v1.json
|
||||
```
|
||||
|
||||
To download large numbers of files, we recommend the `aws` or `rclone` command line tools:
|
||||
|
||||
```
|
||||
aws s3 cp s3://us-west-2.opendata.source.coop/harvard-lil/gov-data/collections/data_gov/<name>/v1.zip --no-sign-request
|
||||
```
|
||||
|
||||
Data Limitations
|
||||
----------------
|
||||
|
||||
data.gov includes multiple kinds of datasets, including some that link to actual data
|
||||
files, such as CSV files, and some that link to HTML landing pages. Our process
|
||||
runs a "shallow crawl" that collects only the directly linked files. Datasets
|
||||
that link only to a landing page will need to be collected separately.
|
||||
|
||||
Source code
|
||||
-----------
|
||||
|
||||
The source code used to generate this and other repositories is available at [https://github.com/harvard-lil/data-mirror](https://github.com/harvard-lil/data-mirror).
|
||||
We welcome conversation and collaboration in the issue tracker for that project.
|
||||
BIN
collections/data_gov/docs/LIL_HLSL_logos.png
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BIN
collections/data_gov/docs/LIL_HLSL_logos.png
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2
data/README.md
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2
data/README.md
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|
|
@ -0,0 +1,2 @@
|
|||
Directory for local data files. Files in this directory are not tracked by git,
|
||||
but may be used by scripts.
|
||||
35
pyproject.toml
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35
pyproject.toml
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|
|
@ -0,0 +1,35 @@
|
|||
[project]
|
||||
name = "data-vault"
|
||||
version = "0.1.0"
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.12"
|
||||
dependencies = [
|
||||
"httpx>=0.27.2",
|
||||
"tqdm>=4.67.0",
|
||||
"pyarrow>=18.0.0",
|
||||
"aiosqlite>=0.20.0",
|
||||
"publicsuffixlist>=1.0.2.20241121",
|
||||
"bagit>=1.8.1",
|
||||
"boto3>=1.35.80",
|
||||
"jsondiff>=2.2.1",
|
||||
"peewee>=3.17.8",
|
||||
"nabit",
|
||||
"gitspoke",
|
||||
"cloudflare>=4.0.0",
|
||||
]
|
||||
|
||||
[build-system]
|
||||
requires = ["hatchling"]
|
||||
build-backend = "hatchling.build"
|
||||
|
||||
[tool.uv]
|
||||
dev-dependencies = [
|
||||
"memray>=1.15.0",
|
||||
]
|
||||
|
||||
[tool.uv.sources]
|
||||
nabit = { git = "https://github.com/harvard-lil/bag-nabit" }
|
||||
gitspoke = { git = "https://github.com/harvard-lil/gitspoke" }
|
||||
|
||||
[tool.hatch.build.targets.wheel]
|
||||
packages = ["scripts"]
|
||||
2
scripts/__init__.py
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2
scripts/__init__.py
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|
|
@ -0,0 +1,2 @@
|
|||
def hello() -> str:
|
||||
return "Hello from data-mirror!"
|
||||
2
scripts/collection/__init__.py
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2
scripts/collection/__init__.py
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|
|
@ -0,0 +1,2 @@
|
|||
def hello() -> str:
|
||||
return "Hello from data-mirror!"
|
||||
100
scripts/collection/cloudflare_tools.py
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100
scripts/collection/cloudflare_tools.py
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|
|
@ -0,0 +1,100 @@
|
|||
import logging
|
||||
from pathlib import Path
|
||||
import click
|
||||
from cloudflare import Cloudflare
|
||||
import os
|
||||
from scripts.helpers.config import load_config
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
def generate_temp_key(account_id: str, bucket: str, parent_access_key_id: str, token: str,
|
||||
permission: str = "object-read-write", ttl_seconds: int = 3600,
|
||||
prefixes: list[str] | None = None, objects: list[str] | None = None):
|
||||
"""Generate a temporary R2 access key using the Cloudflare API.
|
||||
|
||||
Args:
|
||||
account_id: Cloudflare account ID
|
||||
bucket: R2 bucket name
|
||||
parent_access_key_id: Parent access key ID
|
||||
token: Cloudflare API token
|
||||
permission: Permission level ('object-read-write' or 'object-read')
|
||||
ttl_seconds: Time-to-live in seconds
|
||||
prefixes: Optional list of key prefixes to restrict access to
|
||||
objects: Optional list of specific object keys to restrict access to
|
||||
"""
|
||||
params = {
|
||||
"account_id": account_id,
|
||||
"bucket": bucket,
|
||||
"parent_access_key_id": parent_access_key_id,
|
||||
"permission": permission,
|
||||
"ttl_seconds": ttl_seconds,
|
||||
}
|
||||
|
||||
if prefixes:
|
||||
params["prefixes"] = prefixes
|
||||
if objects:
|
||||
params["objects"] = objects
|
||||
|
||||
return Cloudflare(api_token=token).r2.temporary_credentials.create(**params)
|
||||
|
||||
@click.group()
|
||||
def cli():
|
||||
"""Cloudflare R2 utility commands."""
|
||||
pass
|
||||
|
||||
@cli.command()
|
||||
@click.option('--bucket', '-b', type=str, required=True,
|
||||
help='R2 bucket name.')
|
||||
@click.option('--permission', '-p', type=click.Choice(['object-read-write', 'object-read']),
|
||||
default='object-read-write',
|
||||
help='Permission level for the temporary key.')
|
||||
@click.option('--ttl', '-t', type=int, default=1,
|
||||
help='Time-to-live in hours for the temporary key.')
|
||||
@click.option('--prefixes', '-x', multiple=True,
|
||||
help='Key prefixes to restrict access to. Can be specified multiple times.')
|
||||
@click.option('--objects', '-o', multiple=True,
|
||||
help='Specific object keys to restrict access to. Can be specified multiple times.')
|
||||
@click.option('--log-level', '-l',
|
||||
type=click.Choice(['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL']),
|
||||
default='INFO',
|
||||
help='Logging level.')
|
||||
def generate_key(bucket: str, permission: str, ttl: int, prefixes: tuple[str, ...],
|
||||
objects: tuple[str, ...], log_level: str):
|
||||
"""Generate temporary Cloudflare R2 access credentials."""
|
||||
# Setup logging
|
||||
logging.basicConfig(level=log_level)
|
||||
|
||||
# Load config
|
||||
config = load_config().get("temp_tokens", {})
|
||||
|
||||
if not config or any(key not in config for key in ['parent_access_key_id', 'account_id', 'token']):
|
||||
raise click.ClickException("Config file must have 'temp_tokens' dict with 'parent_access_key_id', 'account_id', and 'token' keys")
|
||||
|
||||
# Generate temporary key
|
||||
temp_cred = generate_temp_key(
|
||||
account_id=config['account_id'],
|
||||
bucket=bucket,
|
||||
parent_access_key_id=config['parent_access_key_id'],
|
||||
token=config['token'],
|
||||
permission=permission,
|
||||
ttl_seconds=ttl * 3600,
|
||||
prefixes=list(prefixes) if prefixes else None,
|
||||
objects=list(objects) if objects else None
|
||||
)
|
||||
|
||||
# Output AWS config format
|
||||
click.echo("\n# Add this to ~/.aws/config:")
|
||||
click.echo("[profile r2-temp]")
|
||||
click.echo(f"aws_access_key_id = {temp_cred.access_key_id}")
|
||||
click.echo(f"aws_secret_access_key = {temp_cred.secret_access_key}")
|
||||
click.echo(f"aws_session_token = {temp_cred.session_token}")
|
||||
click.echo("region = auto")
|
||||
click.echo(f"endpoint_url = https://{config['account_id']}.r2.cloudflarestorage.com")
|
||||
|
||||
# Output sample command using first prefix if available
|
||||
click.echo("\n# Sample upload command:")
|
||||
sample_path = objects[0] if objects else f"{prefixes[0].strip('/')}/" if prefixes else ""
|
||||
click.echo(f"aws s3 cp local-file.txt s3://{bucket}/{sample_path} --profile r2-temp")
|
||||
|
||||
if __name__ == "__main__":
|
||||
cli()
|
||||
109
scripts/collection/render.py
Normal file
109
scripts/collection/render.py
Normal file
|
|
@ -0,0 +1,109 @@
|
|||
import click
|
||||
from pathlib import Path
|
||||
from scripts.data_gov.models import db, Dataset
|
||||
import logging
|
||||
from tqdm import tqdm
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
# Header template with styles
|
||||
HEADER_TEMPLATE = '''<!DOCTYPE html>
|
||||
<html>
|
||||
<head>
|
||||
<title>Data.gov Dataset Mirror</title>
|
||||
<link rel="stylesheet" href="style.css">
|
||||
</head>
|
||||
<body>
|
||||
<h1>Data.gov Dataset Mirror</h1>
|
||||
'''
|
||||
|
||||
TABLE_START = ''' <table>
|
||||
<thead>
|
||||
<tr>
|
||||
<th>Name</th>
|
||||
<th>Organization</th>
|
||||
<th>Description</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
'''
|
||||
|
||||
ROW_TEMPLATE = ''' <tr>
|
||||
<td>{name}</td>
|
||||
<td>{org}</td>
|
||||
<td>{title}</td>
|
||||
</tr>
|
||||
'''
|
||||
|
||||
TABLE_END = ''' </tbody>
|
||||
</table>
|
||||
</body>
|
||||
</html>
|
||||
'''
|
||||
|
||||
def render_html(datasets_query, output_path: Path) -> None:
|
||||
"""Render the datasets to an HTML file, streaming content."""
|
||||
with open(output_path / 'index.html', 'w', encoding='utf-8') as f:
|
||||
# Write header
|
||||
f.write(HEADER_TEMPLATE)
|
||||
|
||||
# Write table start
|
||||
f.write(TABLE_START)
|
||||
|
||||
# Stream each dataset row
|
||||
rows = []
|
||||
for dataset in tqdm(datasets_query.iterator(), desc="Rendering datasets"):
|
||||
org_title = dataset.organization.get('title') if dataset.organization else 'N/A'
|
||||
row = ROW_TEMPLATE.format(
|
||||
name=dataset.name or '',
|
||||
org=org_title,
|
||||
title=dataset.title,
|
||||
)
|
||||
rows.append(row)
|
||||
if len(rows) >= 1000:
|
||||
f.write('\n'.join(rows))
|
||||
rows = []
|
||||
|
||||
if rows:
|
||||
f.write('\n'.join(rows))
|
||||
|
||||
# Write table end
|
||||
f.write(TABLE_END)
|
||||
|
||||
@click.command()
|
||||
@click.argument('db_path', type=click.Path(path_type=Path), default='data/data.db')
|
||||
@click.argument('output_path', type=click.Path(path_type=Path), default='data/processed/web')
|
||||
@click.option('--log-level', '-l',
|
||||
type=click.Choice(['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL']),
|
||||
default='INFO',
|
||||
help='Logging level.')
|
||||
@click.option('--limit', '-n', type=int, default=None,
|
||||
help='Maximum number of rows to display. Default: all rows.')
|
||||
def main(db_path: Path, output_path: Path, log_level: str, limit: int | None):
|
||||
"""Render the Dataset table to an HTML file."""
|
||||
logging.basicConfig(
|
||||
level=getattr(logging, log_level),
|
||||
format='%(asctime)s - %(levelname)s - %(message)s'
|
||||
)
|
||||
|
||||
logger.info(f"Connecting to database at {db_path}")
|
||||
db.init(db_path)
|
||||
db.connect()
|
||||
|
||||
try:
|
||||
logger.info("Starting HTML generation...")
|
||||
datasets_query = Dataset.select().order_by(Dataset.id)
|
||||
if limit:
|
||||
datasets_query = datasets_query.limit(limit)
|
||||
logger.info(f"Limited to {limit} rows")
|
||||
|
||||
logger.info(f"Rendering HTML to {output_path}")
|
||||
render_html(datasets_query, output_path)
|
||||
logger.info("Done!")
|
||||
|
||||
finally:
|
||||
db.close()
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
118
scripts/collection/s3_tools.py
Normal file
118
scripts/collection/s3_tools.py
Normal file
|
|
@ -0,0 +1,118 @@
|
|||
import boto3
|
||||
import click
|
||||
from tqdm import tqdm
|
||||
import logging
|
||||
from itertools import islice
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
def get_delete_markers(s3_client, bucket: str, prefix: str):
|
||||
"""Get all delete markers for objects with the given prefix."""
|
||||
paginator = s3_client.get_paginator('list_object_versions')
|
||||
for page in tqdm(paginator.paginate(Bucket=bucket, Prefix=prefix), desc="pages"):
|
||||
if 'DeleteMarkers' in page:
|
||||
yield [
|
||||
{
|
||||
'Key': marker['Key'],
|
||||
'VersionId': marker['VersionId']
|
||||
}
|
||||
for marker in page['DeleteMarkers']
|
||||
if marker['IsLatest']
|
||||
]
|
||||
|
||||
def remove_delete_markers(s3_client, bucket: str, prefix: str, dry_run: bool = False):
|
||||
"""Remove all delete markers for objects with the given prefix."""
|
||||
for marker_batch in get_delete_markers(s3_client, bucket, prefix):
|
||||
response = s3_client.delete_objects(
|
||||
Bucket=bucket,
|
||||
Delete={
|
||||
'Objects': marker_batch,
|
||||
'Quiet': True
|
||||
}
|
||||
)
|
||||
|
||||
# Log any errors
|
||||
if 'Errors' in response:
|
||||
for error in response['Errors']:
|
||||
logger.error(f"Failed to remove marker for {error['Key']}: {error['Message']}")
|
||||
|
||||
def get_empty_files(s3_client, bucket: str, prefix: str):
|
||||
"""Get all objects with size zero under the given prefix."""
|
||||
paginator = s3_client.get_paginator('list_objects_v2')
|
||||
for page in tqdm(paginator.paginate(Bucket=bucket, Prefix=prefix), desc="pages"):
|
||||
if 'Contents' in page:
|
||||
yield [
|
||||
{'Key': obj['Key']}
|
||||
for obj in page['Contents']
|
||||
if obj['Size'] == 0
|
||||
]
|
||||
|
||||
def delete_empty_files(s3_client, bucket: str, prefix: str, dry_run: bool = False):
|
||||
"""Delete all zero-size objects under the given prefix."""
|
||||
pbar = tqdm(desc="deleted")
|
||||
for empty_batch in get_empty_files(s3_client, bucket, prefix):
|
||||
if not empty_batch:
|
||||
continue
|
||||
|
||||
if dry_run:
|
||||
for obj in empty_batch:
|
||||
logger.info(f"Would delete empty file: {obj['Key']}")
|
||||
continue
|
||||
|
||||
pbar.update(len(empty_batch))
|
||||
|
||||
response = s3_client.delete_objects(
|
||||
Bucket=bucket,
|
||||
Delete={
|
||||
'Objects': empty_batch,
|
||||
'Quiet': True
|
||||
}
|
||||
)
|
||||
|
||||
# Log any errors
|
||||
if 'Errors' in response:
|
||||
for error in response['Errors']:
|
||||
logger.error(f"Failed to delete {error['Key']}: {error['Message']}")
|
||||
|
||||
pbar.close()
|
||||
|
||||
@click.group()
|
||||
def cli():
|
||||
"""S3 object management commands."""
|
||||
pass
|
||||
|
||||
@cli.command()
|
||||
@click.argument('s3_path')
|
||||
@click.option('--profile', help='AWS profile name', default='sc-direct')
|
||||
@click.option('--dry-run', is_flag=True, help='Show what would be done without actually doing it')
|
||||
@click.option('--log-level', type=click.Choice(['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL']),
|
||||
default='INFO', help='Set logging level')
|
||||
def undelete(s3_path: str, profile: str = None, dry_run: bool = False, log_level: str = 'INFO'):
|
||||
"""Remove delete markers from versioned S3 objects, effectively undeleting them."""
|
||||
logging.basicConfig(level=log_level)
|
||||
bucket, prefix = s3_path.split('/', 1)
|
||||
|
||||
session = boto3.Session(profile_name=profile)
|
||||
s3_client = session.client('s3')
|
||||
|
||||
remove_delete_markers(s3_client, bucket, prefix, dry_run)
|
||||
|
||||
@cli.command()
|
||||
@click.argument('s3_path')
|
||||
@click.option('--profile', help='AWS profile name', default='sc-direct')
|
||||
@click.option('--dry-run', is_flag=True, help='Show what would be done without actually doing it')
|
||||
@click.option('--log-level', type=click.Choice(['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL']),
|
||||
default='INFO', help='Set logging level')
|
||||
def delete_empty(s3_path: str, profile: str = None, dry_run: bool = False, log_level: str = 'INFO'):
|
||||
"""Delete all zero-size objects under the given prefix."""
|
||||
logging.basicConfig(level=log_level)
|
||||
bucket, prefix = s3_path.split('/', 1)
|
||||
|
||||
session = boto3.Session(profile_name=profile)
|
||||
s3_client = session.client('s3')
|
||||
|
||||
delete_empty_files(s3_client, bucket, prefix, dry_run)
|
||||
|
||||
if __name__ == '__main__':
|
||||
cli()
|
||||
|
||||
31
scripts/collection/sync.py
Normal file
31
scripts/collection/sync.py
Normal file
|
|
@ -0,0 +1,31 @@
|
|||
import boto3
|
||||
import click
|
||||
import json
|
||||
from pathlib import Path
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
@click.command()
|
||||
@click.option('--collections-file', '-c', type=click.Path(exists=True, path_type=Path),
|
||||
default='collections/collections.json',
|
||||
help='Path to collections configuration file.')
|
||||
def main(collections_file: Path):
|
||||
# Load collections config
|
||||
collections = json.loads(collections_file.read_text())
|
||||
collections_dir = collections_file.parent
|
||||
|
||||
for collection in collections:
|
||||
s3 = boto3.Session(profile_name=collection['aws_profile']).client('s3')
|
||||
collection_path = collections_dir / collection['directory']
|
||||
bucket_name, s3_prefix = collection['s3_path'].split('/', 1)
|
||||
|
||||
for file_path in collection_path.rglob('*'):
|
||||
if file_path.is_file():
|
||||
relative_path = file_path.relative_to(collection_path)
|
||||
s3_key = f"{s3_prefix}/{relative_path}"
|
||||
print(f"Uploading {file_path} to s3://{bucket_name}/{s3_key}")
|
||||
s3.upload_file(str(file_path), bucket_name, s3_key)
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
91
scripts/collection/verify_upload.py
Normal file
91
scripts/collection/verify_upload.py
Normal file
|
|
@ -0,0 +1,91 @@
|
|||
from pathlib import Path
|
||||
import json
|
||||
import zipfile
|
||||
import tempfile
|
||||
import requests
|
||||
import click
|
||||
import logging
|
||||
from nabit.bin.utils import cli_validate
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
def download_file(url: str, target_path: Path):
|
||||
"""Download a file from URL to target path"""
|
||||
response = requests.get(url, stream=True)
|
||||
response.raise_for_status()
|
||||
with target_path.open('wb') as f:
|
||||
for chunk in response.iter_content(chunk_size=2**20):
|
||||
f.write(chunk)
|
||||
|
||||
def verify_dataset(json_url: str, zip_url: str, output_dir: Path | None = None):
|
||||
"""
|
||||
Verify a dataset by downloading and checking its JSON metadata and ZIP contents.
|
||||
If output_dir is provided, write the uncompressed contents there.
|
||||
"""
|
||||
with tempfile.TemporaryDirectory() as tmpdir:
|
||||
tmpdir = Path(tmpdir)
|
||||
|
||||
# Download files
|
||||
logger.info(f"Downloading metadata from {json_url}...")
|
||||
json_path = tmpdir / "metadata.json"
|
||||
download_file(json_url, json_path)
|
||||
|
||||
logger.info(f"Downloading archive from {zip_url}...")
|
||||
zip_path = tmpdir / "data.zip"
|
||||
download_file(zip_url, zip_path)
|
||||
|
||||
# Load metadata
|
||||
metadata = json.loads(json_path.read_text())
|
||||
|
||||
# Create output directory
|
||||
if not output_dir:
|
||||
output_dir = tmpdir / "output"
|
||||
output_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
# Verify file contents
|
||||
logger.info("Verifying file contents...")
|
||||
with zip_path.open('rb') as f:
|
||||
for entry in metadata['zip_entries']:
|
||||
logger.info(f"Checking {entry['filename']}...")
|
||||
f.seek(entry['data_offset'])
|
||||
zip_data = f.read(entry['compress_size'])
|
||||
|
||||
if entry['compress_type'] == zipfile.ZIP_STORED:
|
||||
uncompressed = zip_data
|
||||
else:
|
||||
decompressor = zipfile._get_decompressor(entry['compress_type'])
|
||||
uncompressed = decompressor.decompress(zip_data)
|
||||
|
||||
# write the file
|
||||
output_file = output_dir / entry['filename']
|
||||
output_file.parent.mkdir(parents=True, exist_ok=True)
|
||||
output_file.write_bytes(uncompressed)
|
||||
|
||||
logger.info("All files extracted successfully")
|
||||
|
||||
# verify dataset with nabit
|
||||
cli_validate(output_dir)
|
||||
|
||||
# Return metadata for potential further use
|
||||
return metadata
|
||||
|
||||
@click.command()
|
||||
@click.argument('json_url', type=str)
|
||||
@click.argument('zip_url', type=str)
|
||||
@click.option('--output', '-o', type=click.Path(path_type=Path),
|
||||
help='Directory to write uncompressed files')
|
||||
@click.option('--log-level', '-l',
|
||||
type=click.Choice(['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL']),
|
||||
default='INFO',
|
||||
help='Logging level.')
|
||||
def main(json_url: str, zip_url: str, output: Path = None, log_level: str = 'INFO'):
|
||||
"""Verify dataset from JSON and ZIP URLs"""
|
||||
# Set up logging
|
||||
logging.basicConfig(
|
||||
level=getattr(logging, log_level),
|
||||
format='%(asctime)s - %(levelname)s - %(message)s'
|
||||
)
|
||||
|
||||
verify_dataset(json_url, zip_url, output)
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
127
scripts/data_gov/diff/diff.py
Normal file
127
scripts/data_gov/diff/diff.py
Normal file
|
|
@ -0,0 +1,127 @@
|
|||
import json
|
||||
import click
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Set, Tuple
|
||||
import logging
|
||||
from tqdm import tqdm
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def load_jsonl_data(jsonl_path: Path, keep_fields=None, compare_by: str = 'id') -> Dict[str, dict]:
|
||||
"""
|
||||
Load data from JSONL file into a dictionary keyed by id.
|
||||
Only includes fields that match the CSV format.
|
||||
|
||||
Args:
|
||||
jsonl_path: Path to the JSONL file
|
||||
|
||||
Returns:
|
||||
Dictionary mapping id to filtered record data
|
||||
"""
|
||||
# Fields to keep from JSONL records
|
||||
|
||||
data = {}
|
||||
with open(jsonl_path, 'r', encoding='utf-8') as f:
|
||||
for line in tqdm(f, desc="Loading JSONL"):
|
||||
if line.strip(): # Skip empty lines
|
||||
record = json.loads(line)
|
||||
if keep_fields:
|
||||
record = {k: v for k, v in record.items() if k in keep_fields}
|
||||
data[record[compare_by]] = record
|
||||
|
||||
return data
|
||||
|
||||
def find_differences(csv_data: Dict[str, dict],
|
||||
jsonl_data: Dict[str, dict]) -> Tuple[Set[str], Set[str], Set[str]]:
|
||||
"""
|
||||
Find records that differ between CSV and JSONL data.
|
||||
|
||||
Args:
|
||||
csv_data: Dictionary of CSV records keyed by id
|
||||
jsonl_data: Dictionary of JSONL records keyed by id
|
||||
|
||||
Returns:
|
||||
Tuple of (csv_only_ids, jsonl_only_ids, different_ids)
|
||||
"""
|
||||
csv_ids = set(csv_data.keys())
|
||||
jsonl_ids = set(jsonl_data.keys())
|
||||
|
||||
# Find records only in CSV
|
||||
csv_only = csv_ids - jsonl_ids
|
||||
|
||||
# Find records only in JSONL
|
||||
jsonl_only = jsonl_ids - csv_ids
|
||||
|
||||
return csv_only, jsonl_only
|
||||
|
||||
@click.command()
|
||||
@click.argument('old_path', type=click.Path(exists=True, path_type=Path))
|
||||
@click.argument('new_path', type=click.Path(exists=True, path_type=Path))
|
||||
@click.option('--compare-by', '-c',
|
||||
default='id',
|
||||
help='Field to compare by.')
|
||||
@click.option('--log-level', '-l',
|
||||
type=click.Choice(['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL']),
|
||||
default='INFO',
|
||||
help='Logging level.')
|
||||
def main(old_path: Path, new_path: Path, compare_by: str, log_level: str):
|
||||
"""Compare records between CSV and JSONL files."""
|
||||
logging.basicConfig(
|
||||
level=getattr(logging, log_level),
|
||||
format='%(asctime)s - %(levelname)s - %(message)s'
|
||||
)
|
||||
|
||||
old_data = load_jsonl_data(old_path, compare_by=compare_by)
|
||||
new_data = load_jsonl_data(new_path, compare_by=compare_by)
|
||||
|
||||
# Find differences
|
||||
old_only, new_only = find_differences(old_data, new_data)
|
||||
|
||||
old_only_path = old_path.with_suffix(f'.only_{compare_by}.jsonl')
|
||||
new_only_path = new_path.with_suffix(f'.only_{compare_by}.jsonl')
|
||||
|
||||
logger.info(f"Writing {len(old_only)} records to {old_only_path}")
|
||||
with open(old_only_path, 'w', encoding='utf-8') as f:
|
||||
for id in old_only:
|
||||
f.write(json.dumps(old_data[id]) + '\n')
|
||||
|
||||
logger.info(f"Writing {len(new_only)} records to {new_only_path}")
|
||||
with open(new_only_path, 'w', encoding='utf-8') as f:
|
||||
for id in new_only:
|
||||
f.write(json.dumps(new_data[id]) + '\n')
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
|
||||
|
||||
|
||||
# import sqlite3
|
||||
# import json
|
||||
|
||||
# # Connect to the database
|
||||
# conn = sqlite3.connect('data/data.db')
|
||||
# conn.row_factory = sqlite3.Row # This allows us to access columns by name
|
||||
|
||||
# # Open the output file
|
||||
# with open('data/data_db_dump_20250130.jsonl', 'w') as f:
|
||||
# # Execute the query and fetch rows in chunks
|
||||
# cursor = conn.execute('''
|
||||
# SELECT *
|
||||
# FROM dataset
|
||||
# ''')
|
||||
|
||||
# written = 0
|
||||
# while True:
|
||||
# rows = cursor.fetchmany(1000) # Fetch 1000 rows at a time
|
||||
# if not rows:
|
||||
# break
|
||||
# written += len(rows)
|
||||
# # Write each row as a JSON line
|
||||
# for row in rows:
|
||||
# # Convert row to dict and write to file
|
||||
# json_line = json.dumps(dict(row))
|
||||
# f.write(json_line + '\n')
|
||||
# print(f"Wrote {written} rows")
|
||||
|
||||
# conn.close()
|
||||
38
scripts/data_gov/diff/diff_analyze.py
Normal file
38
scripts/data_gov/diff/diff_analyze.py
Normal file
|
|
@ -0,0 +1,38 @@
|
|||
import json
|
||||
from collections import Counter, defaultdict
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
# Read the JSONL file and count crawler_identified_date values
|
||||
downloaded_counts = Counter()
|
||||
identified_counts = Counter()
|
||||
titles_by_org = defaultdict(list)
|
||||
with open('data/data_db_dump_20250130.only_name.jsonl', 'r') as f:
|
||||
for line in f:
|
||||
data = json.loads(line)
|
||||
org = json.loads(data.get('organization', '{}'))
|
||||
identified_counts[(data.get('crawler_identified_date') or '')[:10]] += 1
|
||||
titles_by_org[org['title']].append(data["title"])
|
||||
|
||||
# Print the counts sorted by date
|
||||
for date, count in sorted(identified_counts.items()):
|
||||
print(f"{date}: {count}")
|
||||
|
||||
# sort each list of titles by org
|
||||
for org, titles in titles_by_org.items():
|
||||
titles_by_org[org].sort()
|
||||
Path('data/titles_by_org.json').write_text(json.dumps(titles_by_org, indent=2))
|
||||
|
||||
|
||||
# print urls
|
||||
for path in Path('data/').glob('glass*'):
|
||||
print(path)
|
||||
with open(path, 'r') as f:
|
||||
for line in f:
|
||||
data = json.loads(line)
|
||||
print("* " + data['name'])
|
||||
resources = data.get('resources', [])
|
||||
if type(resources) == str:
|
||||
resources = json.loads(resources)
|
||||
for resource in resources:
|
||||
print(' * ' + resource['url'])
|
||||
318
scripts/data_gov/fetch_data.py
Normal file
318
scripts/data_gov/fetch_data.py
Normal file
|
|
@ -0,0 +1,318 @@
|
|||
from nabit.lib.archive import package
|
||||
from nabit.lib.sign import KNOWN_TSAS, is_encrypted_key
|
||||
from nabit.lib.backends.url import UrlCollectionTask
|
||||
from pathlib import Path
|
||||
import json
|
||||
import uuid
|
||||
import tempfile
|
||||
import click
|
||||
import os
|
||||
from urllib.parse import urlparse
|
||||
import re
|
||||
from scripts.helpers.parallel import run_parallel
|
||||
import zipfile
|
||||
import struct
|
||||
import boto3
|
||||
import logging
|
||||
from scripts.data_gov.models import db, Dataset
|
||||
from playhouse.shortcuts import model_to_dict
|
||||
from tqdm import tqdm
|
||||
from datetime import datetime
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
## download data.gov datasets, create nabit archives, and upload to S3
|
||||
|
||||
# File extensions that are already compressed or wouldn't benefit from additional compression
|
||||
UNCOMPRESSED_EXTENSIONS = {
|
||||
# Already compressed archives
|
||||
'zip', 'gz', 'tgz', 'bz2', '7z', 'rar', 'xz',
|
||||
# Compressed images
|
||||
'jpg', 'jpeg', 'png', 'gif', 'webp',
|
||||
# Compressed video/audio
|
||||
'mp4', 'mov', 'avi', 'wmv', 'ogv', 'mp3', 'm4a',
|
||||
# Other compressed/binary formats
|
||||
'pdf', 'docx', 'xlsx', 'pptx',
|
||||
}
|
||||
|
||||
stats_counter = {}
|
||||
|
||||
def is_valid_url(url):
|
||||
parsed = urlparse(url)
|
||||
return parsed.scheme in ['http', 'https'] and re.search(r'[^\.]\.[^\.]', parsed.netloc)
|
||||
|
||||
def extract_urls(data, urls = None):
|
||||
urls = set() if urls is None else urls
|
||||
if isinstance(data, dict):
|
||||
for key, value in data.items():
|
||||
if isinstance(value, str):
|
||||
if is_valid_url(value):
|
||||
urls.add(value)
|
||||
elif isinstance(value, (dict, list)):
|
||||
extract_urls(value, urls)
|
||||
elif isinstance(data, list):
|
||||
for item in data:
|
||||
extract_urls(item, urls)
|
||||
return urls
|
||||
|
||||
def create_archive(bag_dir, dataset: Dataset, signatures):
|
||||
data_dict = model_to_dict(dataset)
|
||||
for key, value in data_dict.items():
|
||||
if isinstance(value, datetime):
|
||||
data_dict[key] = value.isoformat()
|
||||
data_gov_url = f'https://catalog.data.gov/dataset/{dataset.name}'
|
||||
collect = [
|
||||
*[UrlCollectionTask(url=url) for url in extract_urls(data_dict)],
|
||||
]
|
||||
logger.info(f" - Downloading {len(collect)} files")
|
||||
|
||||
# sort fields from dataset
|
||||
data_gov_metadata = {k: v for k, v in data_dict.items() if not k.startswith('crawler_')}
|
||||
crawler_metadata = {k: v for k, v in data_dict.items() if k.startswith('crawler_')}
|
||||
|
||||
# Create the archive
|
||||
package(
|
||||
output_path=bag_dir,
|
||||
collect=collect,
|
||||
collect_errors='ignore',
|
||||
signed_metadata={
|
||||
'id': str(uuid.uuid4()),
|
||||
'url': data_gov_url,
|
||||
'description': f'Archive of data.gov dataset "{dataset.title}" created by {dataset.organization["title"]}. Full metadata stored in data_gov_metadata key.',
|
||||
'data_gov_metadata': data_gov_metadata,
|
||||
'crawler_metadata': crawler_metadata,
|
||||
},
|
||||
signatures=signatures,
|
||||
)
|
||||
|
||||
def zip_archive(bag_dir, archive_path):
|
||||
# Create zip archive
|
||||
with zipfile.ZipFile(archive_path, 'w', zipfile.ZIP_DEFLATED) as zf:
|
||||
for file_path in bag_dir.rglob('*'):
|
||||
if file_path.is_file():
|
||||
arc_path = file_path.relative_to(bag_dir)
|
||||
compression = (zipfile.ZIP_STORED
|
||||
if file_path.suffix.lower().lstrip('.') in UNCOMPRESSED_EXTENSIONS
|
||||
else zipfile.ZIP_DEFLATED)
|
||||
zf.write(file_path, arc_path, compress_type=compression)
|
||||
|
||||
# Create metadata file
|
||||
zip_info = []
|
||||
with zipfile.ZipFile(archive_path, 'r') as zf:
|
||||
for info in zf.filelist:
|
||||
header_offset = info.header_offset
|
||||
|
||||
# Read header to calculate data offset
|
||||
zf.fp.seek(header_offset)
|
||||
header = zf.fp.read(zipfile.sizeFileHeader)
|
||||
fheader = struct.unpack(zipfile.structFileHeader, header)
|
||||
fname_length = fheader[zipfile._FH_FILENAME_LENGTH]
|
||||
extra_length = fheader[zipfile._FH_EXTRA_FIELD_LENGTH]
|
||||
data_offset = header_offset + zipfile.sizeFileHeader + fname_length + extra_length
|
||||
|
||||
zip_info.append({
|
||||
'filename': info.filename,
|
||||
'file_size': info.file_size,
|
||||
'compress_size': info.compress_size,
|
||||
'compress_type': info.compress_type,
|
||||
'header_offset': header_offset,
|
||||
'data_offset': data_offset,
|
||||
})
|
||||
|
||||
# Read the bag-info.txt and signed-metadata.json
|
||||
bag_info = (bag_dir / 'bag-info.txt').read_text()
|
||||
signed_metadata = json.loads((bag_dir / 'data/signed-metadata.json').read_text())
|
||||
|
||||
return {
|
||||
'bag_info': bag_info,
|
||||
'signed_metadata': signed_metadata,
|
||||
'zip_entries': zip_info
|
||||
}
|
||||
|
||||
def upload_archive(output_path, collection_path, metadata_path, s3_path, session_args):
|
||||
s3 = boto3.Session(**session_args).client('s3')
|
||||
bucket_name, s3_path = s3_path.split('/', 1)
|
||||
|
||||
# Upload zip file
|
||||
s3_collection_key = os.path.join(s3_path, str(collection_path.relative_to(output_path)))
|
||||
s3.upload_file(str(collection_path), bucket_name, s3_collection_key)
|
||||
logger.info(f" - Uploaded {collection_path.relative_to(output_path)} to {s3_collection_key}")
|
||||
|
||||
# Upload metadata file
|
||||
s3_metadata_key = os.path.join(s3_path, str(metadata_path.relative_to(output_path)))
|
||||
s3.upload_file(str(metadata_path), bucket_name, s3_metadata_key)
|
||||
logger.info(f" - Uploaded {metadata_path.relative_to(output_path)} to {s3_metadata_key}")
|
||||
|
||||
|
||||
def run_pipeline(
|
||||
dataset: Dataset,
|
||||
output_path: Path,
|
||||
metadata_path: Path,
|
||||
collection_path: Path,
|
||||
signatures: list = None,
|
||||
session_args: dict = None,
|
||||
s3_path: str = None,
|
||||
no_delete: bool = False,
|
||||
):
|
||||
logger.info(f"Processing dataset: {dataset.name}")
|
||||
|
||||
# we have a db forked from the main process, so we need to close it and reopen if needed
|
||||
db.close()
|
||||
|
||||
# set this here so it makes it into the metadata
|
||||
dataset.crawler_downloaded_date = datetime.now()
|
||||
|
||||
with tempfile.TemporaryDirectory(dir=str(output_path)) as temp_dir:
|
||||
logger.info("- Creating archive...")
|
||||
# set up paths
|
||||
temp_dir = Path(temp_dir)
|
||||
bag_dir = temp_dir / 'bag'
|
||||
archive_path = temp_dir / 'archive.zip'
|
||||
|
||||
# download data with nabit
|
||||
create_archive(bag_dir, dataset, signatures)
|
||||
|
||||
logger.info("- Zipping archive...")
|
||||
# zip up data and create metadata
|
||||
output_metadata = zip_archive(bag_dir, archive_path)
|
||||
|
||||
logger.info("- Moving files to final location...")
|
||||
# Move files to final location
|
||||
collection_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
metadata_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
os.rename(str(archive_path), collection_path)
|
||||
metadata_path.write_text(json.dumps(output_metadata) + '\n')
|
||||
|
||||
if s3_path:
|
||||
logger.info("Uploading to S3...")
|
||||
upload_archive(output_path, collection_path, metadata_path, s3_path, session_args)
|
||||
|
||||
if not no_delete:
|
||||
logger.info("- Deleting zip archive...")
|
||||
os.remove(collection_path)
|
||||
if collection_path.parent.exists() and not os.listdir(collection_path.parent):
|
||||
os.rmdir(collection_path.parent)
|
||||
|
||||
logger.info("- Setting crawler_downloaded_date...")
|
||||
db.connect()
|
||||
dataset.save()
|
||||
|
||||
logger.info("Processing complete")
|
||||
|
||||
def get_unprocessed_datasets(output_path: Path, collection: str, min_size: int = 0, dataset_name: str = None):
|
||||
"""Get datasets from SQLite that don't have metadata files yet."""
|
||||
query = Dataset.select()
|
||||
|
||||
if dataset_name:
|
||||
query = query.where(Dataset.name == dataset_name)
|
||||
if min_size:
|
||||
query = query.where(Dataset.size >= min_size)
|
||||
|
||||
# Initialize progress bars
|
||||
stats_counter['total'] = tqdm(desc="Total records", unit="pkg")
|
||||
stats_counter['skipped'] = tqdm(desc="Already processed", unit="pkg")
|
||||
stats_counter['yielded'] = tqdm(desc="Processing", unit="pkg")
|
||||
|
||||
for dataset in query:
|
||||
stats_counter['total'].update(1)
|
||||
|
||||
# Check if metadata file exists
|
||||
name = dataset.name
|
||||
metadata_path = output_path / 'metadata' / collection / name / 'v1.json'
|
||||
|
||||
if metadata_path.exists():
|
||||
stats_counter['skipped'].update(1)
|
||||
continue
|
||||
|
||||
stats_counter['yielded'].update(1)
|
||||
yield dataset
|
||||
|
||||
|
||||
@click.command()
|
||||
@click.option('--db-path', '-d', type=click.Path(exists=True, path_type=Path), default='data/data.db')
|
||||
@click.option('--output-path', '-o', type=click.Path(path_type=Path), default='data/processed',
|
||||
help='Output path.')
|
||||
@click.option('--collection', '-c', type=str, default='data_gov',
|
||||
help='Collection name.')
|
||||
@click.option('--workers', '-w', type=int, default=None,
|
||||
help='Number of worker processes. Defaults to CPU count.')
|
||||
@click.option('--min-size', '-s', type=int, default=0,
|
||||
help='Minimum size of dataset to process.')
|
||||
@click.option('--dataset-name', help='Dataset name to process.')
|
||||
@click.option('--if-exists', '-e', type=click.Choice(['skip', 'replace', 'version']), default='skip',
|
||||
help='Whether to skip, replace, or add a version if dataset already exists.')
|
||||
@click.option('--signatures', help='JSON string of signature configuration.')
|
||||
@click.option('--profile', '-p', help='AWS profile name')
|
||||
@click.option('--s3-path', '-s', help='S3 path for uploads, e.g. "<bucket_name>/<path>"')
|
||||
@click.option('--log-level', '-l', type=click.Choice(['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL']), default=None,
|
||||
help='Logging level.')
|
||||
@click.option('--stop-after', help='Stop after processing this many collections', type=int)
|
||||
@click.option('--no-delete', is_flag=True, help='Set to preserve zipped data on disk as well as metadata')
|
||||
def main(db_path: Path, output_path: Path, collection: str, workers=None, min_size=0, dataset_name=None,
|
||||
if_exists='skip', signatures=None, profile=None, s3_path=None, log_level=None, stop_after=None, no_delete=False):
|
||||
|
||||
if dataset_name:
|
||||
workers = 1
|
||||
stop_after = 1
|
||||
|
||||
if signatures:
|
||||
signatures = json.loads(signatures)
|
||||
for signature in signatures:
|
||||
if signature['action'] == 'sign':
|
||||
if is_encrypted_key(signature['params']['key']):
|
||||
signature['params']['password'] = click.prompt(
|
||||
f"Enter password for {signature['params']['key']}: ",
|
||||
hide_input=True
|
||||
)
|
||||
elif signature['action'] == 'timestamp':
|
||||
if known_tsa := signature.pop('known_tsa', None):
|
||||
signature['params'] = KNOWN_TSAS[known_tsa]
|
||||
|
||||
session_args = {}
|
||||
if profile:
|
||||
session_args['profile_name'] = profile
|
||||
|
||||
# Initialize database connection
|
||||
db.init(db_path)
|
||||
db.connect()
|
||||
|
||||
def get_tasks():
|
||||
processed = 0
|
||||
for dataset in get_unprocessed_datasets(output_path, collection, min_size, dataset_name):
|
||||
# handle existing datasets
|
||||
name = dataset.name
|
||||
collection_path = output_path / 'collections' / collection / name / 'v1.zip'
|
||||
metadata_path = output_path / 'metadata' / collection / name / 'v1.json'
|
||||
|
||||
if metadata_path.exists():
|
||||
if if_exists == 'skip':
|
||||
continue
|
||||
elif if_exists == 'replace':
|
||||
metadata_path.unlink()
|
||||
if collection_path.exists():
|
||||
collection_path.unlink()
|
||||
elif if_exists == 'version':
|
||||
version = 2
|
||||
while True:
|
||||
collection_path = output_path / 'collections' / collection / name / f'v{version}.zip'
|
||||
metadata_path = output_path / 'metadata' / collection / name / f'v{version}.json'
|
||||
if not metadata_path.exists():
|
||||
break
|
||||
version += 1
|
||||
|
||||
yield dataset, output_path, metadata_path, collection_path, signatures, session_args, s3_path, no_delete
|
||||
|
||||
processed += 1
|
||||
if stop_after and processed >= stop_after:
|
||||
break
|
||||
|
||||
try:
|
||||
run_parallel(run_pipeline, get_tasks(), workers, log_level=log_level, catch_errors=False)
|
||||
finally:
|
||||
# Close progress bars
|
||||
for counter in stats_counter.values():
|
||||
counter.close()
|
||||
db.close()
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
299
scripts/data_gov/fetch_index.py
Normal file
299
scripts/data_gov/fetch_index.py
Normal file
|
|
@ -0,0 +1,299 @@
|
|||
import httpx
|
||||
from typing import Iterator, Dict, Any, List
|
||||
import time
|
||||
import click
|
||||
from pathlib import Path
|
||||
import logging
|
||||
from datetime import datetime
|
||||
from scripts.data_gov.models import db, Dataset, DatasetHistory
|
||||
from tqdm import tqdm
|
||||
from playhouse.shortcuts import model_to_dict
|
||||
from jsondiff import diff
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
stats_counter = {}
|
||||
|
||||
def init_database(db_path: Path) -> None:
|
||||
"""Initialize the database connection and create tables."""
|
||||
db.init(db_path)
|
||||
db.connect()
|
||||
db.create_tables([Dataset, DatasetHistory])
|
||||
|
||||
def save_to_database(results: List[Dict[str, Any]]) -> None:
|
||||
"""
|
||||
Save a batch of packages to the database using Peewee.
|
||||
"""
|
||||
if not results:
|
||||
return
|
||||
|
||||
# Process datetime fields in incoming records
|
||||
for package in results:
|
||||
for field in ['metadata_created', 'metadata_modified']:
|
||||
if package.get(field):
|
||||
try:
|
||||
package[field] = datetime.fromisoformat(
|
||||
package[field].replace('Z', '+00:00')
|
||||
)
|
||||
except ValueError:
|
||||
package[field] = None
|
||||
|
||||
# Get all IDs from incoming packages
|
||||
incoming_ids = [pkg['id'] for pkg in results]
|
||||
|
||||
# Fetch existing records as model instances
|
||||
existing_records = {
|
||||
record.id: record
|
||||
for record in Dataset.select().where(Dataset.id << incoming_ids)
|
||||
}
|
||||
|
||||
# Prepare bulk operations
|
||||
history_records = []
|
||||
new_records = []
|
||||
|
||||
# Compare records and prepare operations
|
||||
for package_data in results:
|
||||
# Create a new model instance from the package data
|
||||
new_package = Dataset(**package_data)
|
||||
existing = existing_records.get(package_data['id'])
|
||||
|
||||
if existing:
|
||||
# Compare model instances using their dict representations
|
||||
if diff(model_to_dict(existing), model_to_dict(new_package)):
|
||||
# Record changed - add to history and update
|
||||
history_records.append(existing)
|
||||
new_records.append(new_package)
|
||||
stats_counter['updated'].update(1)
|
||||
else:
|
||||
# Record unchanged - skip
|
||||
stats_counter['skipped'].update(1)
|
||||
continue
|
||||
else:
|
||||
# New record - just add it
|
||||
new_records.append(new_package)
|
||||
stats_counter['new'].update(1)
|
||||
|
||||
with db.atomic():
|
||||
# Bulk move history records if any exist
|
||||
if history_records:
|
||||
DatasetHistory.bulk_create(history_records)
|
||||
Dataset.delete().where(Dataset.id << [h.id for h in history_records]).execute()
|
||||
|
||||
# Bulk insert new records
|
||||
if new_records:
|
||||
Dataset.bulk_create(new_records)
|
||||
|
||||
def save_packages_to_database(output_path: Path, rows_per_page: int = 1000, start_date: str | None = None) -> None:
|
||||
"""
|
||||
Save fetched data to the database, resuming from last position if needed.
|
||||
|
||||
Args:
|
||||
output_path: Path to save the database
|
||||
rows_per_page: Number of results to fetch per page
|
||||
start_date: Optional date to start fetching from
|
||||
"""
|
||||
stats_counter['new'] = tqdm(desc="New records", unit="pkg")
|
||||
stats_counter['updated'] = tqdm(desc="Updated records", unit="pkg")
|
||||
stats_counter['skipped'] = tqdm(desc="Unchanged records", unit="pkg")
|
||||
|
||||
init_database(output_path)
|
||||
|
||||
try:
|
||||
for results in tqdm(fetch_data_gov_packages(rows_per_page=rows_per_page, start_date=start_date, max_retries=10)):
|
||||
save_to_database(results)
|
||||
finally:
|
||||
db.close()
|
||||
|
||||
def fetch_data_gov_packages(rows_per_page: int = 1000, start_date: str = None, max_retries: int = 3) -> Iterator[Dict[str, Any]]:
|
||||
"""
|
||||
Fetch package data from data.gov API using date-based pagination.
|
||||
|
||||
Args:
|
||||
rows_per_page: Number of results to fetch per page
|
||||
start_date: Optional date to start fetching from (format: YYYY-MM-DDTHH:MM:SS.mmmmmm)
|
||||
max_retries: Maximum number of retry attempts for 5xx errors
|
||||
|
||||
Yields:
|
||||
Dict containing package data for each result
|
||||
"""
|
||||
|
||||
base_url = "https://catalog.data.gov/api/3/action/package_search"
|
||||
current_date = start_date
|
||||
total_records = 0
|
||||
|
||||
while True:
|
||||
logger.info(f"Current date offset: {current_date}")
|
||||
|
||||
# Build date filter query
|
||||
url = f"{base_url}?rows={rows_per_page}&sort=metadata_modified+desc"
|
||||
if current_date:
|
||||
# Format date to match Solr's expected format (dropping microseconds)
|
||||
formatted_date = current_date.split('.')[0] + 'Z'
|
||||
date_filter = f"+metadata_modified:[* TO {formatted_date}]"
|
||||
url += f"&fq={date_filter}"
|
||||
|
||||
for attempt in range(max_retries):
|
||||
try:
|
||||
start_time = time.time()
|
||||
response = httpx.get(url, timeout=60.0)
|
||||
request_time = time.time() - start_time
|
||||
|
||||
response.raise_for_status()
|
||||
break # Success, exit retry loop
|
||||
|
||||
except httpx.HTTPStatusError as e:
|
||||
if e.response.status_code >= 500 and attempt < max_retries - 1:
|
||||
retry_wait = 2 ** attempt # Exponential backoff
|
||||
logger.warning(f"Got {e.response.status_code}, retrying in {retry_wait}s... (attempt {attempt + 1}/{max_retries})")
|
||||
logger.warning(f"Error URL: {url}")
|
||||
time.sleep(retry_wait)
|
||||
continue
|
||||
# If not a 5xx error or we're out of retries, re-raise
|
||||
logger.error(f"Error URL: {url}")
|
||||
logger.error(f"Response content: {response.text}")
|
||||
raise
|
||||
|
||||
data = response.json()
|
||||
results = data["result"]["results"]
|
||||
|
||||
if not results:
|
||||
break
|
||||
|
||||
# Get date of last result for next query
|
||||
current_date = results[-1]["metadata_modified"]
|
||||
|
||||
total_records += len(results)
|
||||
logger.info(f"Request took {request_time:.2f}s. Total records: {total_records}")
|
||||
|
||||
yield results
|
||||
|
||||
time.sleep(1)
|
||||
|
||||
def get_dataset_history(dataset_name: str) -> None:
|
||||
"""
|
||||
Fetch and display all versions of a dataset with the given ID,
|
||||
from oldest to newest, showing only changed fields between versions.
|
||||
"""
|
||||
# Get all versions including current
|
||||
versions = [
|
||||
model_to_dict(record, recurse=True)
|
||||
for record in (DatasetHistory
|
||||
.select()
|
||||
.where(DatasetHistory.name == dataset_name)
|
||||
.order_by(DatasetHistory.metadata_modified))
|
||||
]
|
||||
current_record = Dataset.select().where(Dataset.name == dataset_name).first()
|
||||
if current_record:
|
||||
versions.append(model_to_dict(current_record, recurse=True))
|
||||
|
||||
if not versions:
|
||||
print(f"No dataset found with name: {dataset_name}")
|
||||
return
|
||||
|
||||
# Print each version with changed fields
|
||||
prev = None
|
||||
for curr in versions:
|
||||
history_id = curr.pop('history_id', None)
|
||||
if prev:
|
||||
diff_fields = diff(prev, curr)
|
||||
else:
|
||||
diff_fields = curr
|
||||
|
||||
print(f"*** Version: {curr.get('metadata_modified')} ***")
|
||||
for k, v in diff_fields.items():
|
||||
print(f"- {k}: {v}")
|
||||
print("\n")
|
||||
prev = curr
|
||||
|
||||
@click.group()
|
||||
def cli():
|
||||
"""Data.gov dataset mirroring tools."""
|
||||
pass
|
||||
|
||||
# Modify the existing main function to be a command in the group
|
||||
@cli.command()
|
||||
@click.argument('output_path', type=click.Path(path_type=Path), default='data/data.db')
|
||||
@click.option('--rows-per-page', '-r', type=int, default=1000,
|
||||
help='Number of results to fetch per page.')
|
||||
@click.option('--start-date', '-s', type=str, default=None,
|
||||
help='Date to start fetching from (format: YYYY-MM-DDTHH:MM:SS.mmmmmm)')
|
||||
@click.option('--log-level', '-l',
|
||||
type=click.Choice(['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL']),
|
||||
default='WARNING',
|
||||
help='Logging level.')
|
||||
def fetch(output_path: Path, rows_per_page: int, start_date: str, log_level: str):
|
||||
"""Fetch package data from data.gov API and save to database."""
|
||||
logging.basicConfig(
|
||||
level=getattr(logging, log_level),
|
||||
format='%(asctime)s - %(levelname)s - %(message)s'
|
||||
)
|
||||
|
||||
save_packages_to_database(output_path, rows_per_page, start_date)
|
||||
|
||||
@cli.command()
|
||||
@click.argument('dataset_name')
|
||||
@click.argument('db_path', type=click.Path(path_type=Path), default='data/data.db')
|
||||
def history(dataset_name: str, db_path: Path):
|
||||
"""Show version history for a dataset with the given ID."""
|
||||
init_database(db_path)
|
||||
try:
|
||||
get_dataset_history(dataset_name)
|
||||
finally:
|
||||
db.close()
|
||||
|
||||
@cli.command()
|
||||
@click.argument('db_path', type=click.Path(path_type=Path), default='data/data.db')
|
||||
def delete_duplicate_history(db_path: Path):
|
||||
"""Delete duplicate history records."""
|
||||
init_database(db_path)
|
||||
try:
|
||||
# Get all unique dataset names in history
|
||||
unique_names = (DatasetHistory
|
||||
.select(DatasetHistory.name)
|
||||
.distinct()
|
||||
.tuples())
|
||||
|
||||
total_deleted = 0
|
||||
for (name,) in tqdm(unique_names, desc="Processing datasets"):
|
||||
# Get all versions for this dataset ordered by modification date
|
||||
versions = [
|
||||
model_to_dict(record)
|
||||
for record in (DatasetHistory
|
||||
.select()
|
||||
.where(DatasetHistory.name == name)
|
||||
.order_by(DatasetHistory.metadata_modified))
|
||||
]
|
||||
current_record = Dataset.select().where(Dataset.name == name).first()
|
||||
if current_record:
|
||||
versions.append(model_to_dict(current_record))
|
||||
|
||||
# Track IDs of duplicate records to delete
|
||||
to_delete = []
|
||||
|
||||
# Compare adjacent versions
|
||||
prev = versions[0]
|
||||
prev_id = prev.pop('history_id')
|
||||
for curr in versions[1:]:
|
||||
curr_id = curr.pop('history_id', None)
|
||||
|
||||
# If versions are identical, mark current version for deletion
|
||||
if not diff(prev, curr):
|
||||
to_delete.append(prev_id)
|
||||
prev = curr
|
||||
prev_id = curr_id
|
||||
|
||||
# Bulk delete duplicate records
|
||||
if to_delete:
|
||||
deleted = (DatasetHistory
|
||||
.delete()
|
||||
.where(DatasetHistory.history_id << to_delete)
|
||||
.execute())
|
||||
total_deleted += deleted
|
||||
|
||||
click.echo(f"Deleted {total_deleted} duplicate history records")
|
||||
finally:
|
||||
db.close()
|
||||
|
||||
if __name__ == "__main__":
|
||||
cli()
|
||||
|
||||
35
scripts/data_gov/fetch_jsonl.py
Normal file
35
scripts/data_gov/fetch_jsonl.py
Normal file
|
|
@ -0,0 +1,35 @@
|
|||
import httpx
|
||||
import json
|
||||
import time
|
||||
import logging
|
||||
from pathlib import Path
|
||||
from typing import Iterator, Dict, Any, List
|
||||
import click
|
||||
from scripts.data_gov.fetch_index import fetch_data_gov_packages
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
@click.command()
|
||||
@click.argument('output_path', type=click.Path(path_type=Path), default='data/data_20250130.jsonl')
|
||||
@click.option('--rows-per-page', '-r', type=int, default=1000,
|
||||
help='Number of results to fetch per page.')
|
||||
@click.option('--log-level', '-l',
|
||||
type=click.Choice(['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL']),
|
||||
default='INFO',
|
||||
help='Logging level.')
|
||||
@click.option('--start-date', '-s', type=str, default=None,
|
||||
help='Start date for fetching packages in YYYY-MM-DD format.')
|
||||
def main(output_path: Path, rows_per_page: int, log_level: str, start_date: str):
|
||||
"""Fetch all package data from data.gov API and save to JSONL file."""
|
||||
logging.basicConfig(
|
||||
level=getattr(logging, log_level),
|
||||
format='%(asctime)s - %(levelname)s - %(message)s'
|
||||
)
|
||||
|
||||
with open(output_path, 'a') as f:
|
||||
for results in fetch_data_gov_packages(rows_per_page=rows_per_page, start_date=start_date):
|
||||
for package in results:
|
||||
f.write(json.dumps(package) + '\n')
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
18
scripts/data_gov/migrate.py
Normal file
18
scripts/data_gov/migrate.py
Normal file
|
|
@ -0,0 +1,18 @@
|
|||
from playhouse.migrate import *
|
||||
from scripts.data_gov.models import db
|
||||
|
||||
migrator = SqliteMigrator(db)
|
||||
|
||||
def do_migrate():
|
||||
crawler_identified_date = DateTimeField(null=True)
|
||||
crawler_downloaded_date = DateTimeField(null=True)
|
||||
with db.atomic():
|
||||
migrate(
|
||||
# migrator.add_column('dataset', 'crawler_identified_date', crawler_identified_date),
|
||||
# migrator.add_column('dataset', 'crawler_downloaded_date', crawler_downloaded_date),
|
||||
# migrator.add_column('datasethistory', 'crawler_identified_date', crawler_identified_date),
|
||||
# migrator.add_column('datasethistory', 'crawler_downloaded_date', crawler_downloaded_date),
|
||||
)
|
||||
|
||||
if __name__ == '__main__':
|
||||
do_migrate()
|
||||
61
scripts/data_gov/models.py
Normal file
61
scripts/data_gov/models.py
Normal file
|
|
@ -0,0 +1,61 @@
|
|||
from peewee import *
|
||||
from playhouse.sqlite_ext import JSONField
|
||||
from pathlib import Path
|
||||
from datetime import datetime
|
||||
|
||||
db = SqliteDatabase(Path(__file__).parent.parent.parent / 'data/data.db', pragmas={
|
||||
# tuning suggested by Claude:
|
||||
'journal_mode': 'wal', # Write-Ahead Logging for better concurrency
|
||||
'cache_size': -1024 * 64, # 64MB cache (negative number means kibibytes)
|
||||
'synchronous': 'normal', # Good balance between safety and speed
|
||||
'busy_timeout': 30000, # Wait up to 30 seconds when database is locked
|
||||
'temp_store': 'memory', # Store temp tables in memory
|
||||
'mmap_size': 268435456, # Memory-mapped I/O (256MB)
|
||||
'page_size': 4096, # Optimal for most systems
|
||||
})
|
||||
|
||||
class BaseModel(Model):
|
||||
class Meta:
|
||||
database = db
|
||||
|
||||
class Dataset(BaseModel):
|
||||
# fields from data.gov
|
||||
id = CharField(primary_key=True)
|
||||
name = CharField(null=True)
|
||||
title = CharField(null=True)
|
||||
notes = TextField(null=True)
|
||||
metadata_created = DateTimeField(null=True)
|
||||
metadata_modified = DateTimeField(null=True)
|
||||
private = BooleanField(null=True)
|
||||
state = CharField(null=True)
|
||||
version = CharField(null=True)
|
||||
type = CharField(null=True)
|
||||
num_resources = IntegerField(null=True)
|
||||
num_tags = IntegerField(null=True)
|
||||
isopen = BooleanField(null=True)
|
||||
author = CharField(null=True)
|
||||
author_email = CharField(null=True)
|
||||
creator_user_id = CharField(null=True)
|
||||
license_id = CharField(null=True)
|
||||
license_url = CharField(null=True)
|
||||
license_title = CharField(null=True)
|
||||
maintainer = CharField(null=True)
|
||||
maintainer_email = CharField(null=True)
|
||||
owner_org = CharField(null=True)
|
||||
url = CharField(null=True)
|
||||
organization = JSONField(null=True)
|
||||
extras = JSONField(null=True)
|
||||
resources = JSONField(null=True)
|
||||
tags = JSONField(null=True)
|
||||
groups = JSONField(null=True)
|
||||
relationships_as_subject = JSONField(null=True)
|
||||
relationships_as_object = JSONField(null=True)
|
||||
|
||||
# fields starting with crawler_ are added by our crawler
|
||||
crawler_identified_date = DateTimeField(null=True, default=datetime.now)
|
||||
crawler_downloaded_date = DateTimeField(null=True)
|
||||
|
||||
class DatasetHistory(Dataset):
|
||||
history_id = AutoField(primary_key=True)
|
||||
id = CharField() # Regular CharField, not primary key
|
||||
#deleted_by_date = DateTimeField(null=True) # New field to track deletion date
|
||||
141
scripts/github/download_git.py
Normal file
141
scripts/github/download_git.py
Normal file
|
|
@ -0,0 +1,141 @@
|
|||
import csv
|
||||
import logging
|
||||
from pathlib import Path
|
||||
from scripts.helpers.parallel import run_parallel
|
||||
import click
|
||||
from tqdm import tqdm
|
||||
from gitspoke import Downloader, GitHubAPI
|
||||
from gitspoke.cli import valid_include_items, get_token
|
||||
import os
|
||||
import json
|
||||
import requests
|
||||
from scripts.helpers.config import load_config
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
stats_counter = {}
|
||||
|
||||
CONFIG_PATH = (os.environ.get("XDG_CONFIG_HOME") or (Path.home() / ".config")) / "data-mirror" / "config.json"
|
||||
|
||||
def check_repo_exists(org_name, repo_name, token, output_path=None):
|
||||
"""Check if a repository still exists on GitHub."""
|
||||
exists = True
|
||||
try:
|
||||
GitHubAPI(token).request(f"repos/{org_name}/{repo_name}", method="HEAD")
|
||||
except requests.exceptions.HTTPError as e:
|
||||
if e.response.status_code == 404:
|
||||
exists = False
|
||||
else:
|
||||
raise e
|
||||
if not exists:
|
||||
repo_link = f"https://github.com/{org_name}/{repo_name}"
|
||||
print(repo_link)
|
||||
if output_path:
|
||||
with open(output_path, 'a') as output_file:
|
||||
output_file.write(f"{repo_link}\n")
|
||||
return exists
|
||||
|
||||
def run_pipeline(org_name, repo_name, collection_path, include, token, check_exists=False, output_path=None):
|
||||
"""Process a single repository."""
|
||||
if check_exists:
|
||||
return check_repo_exists(org_name, repo_name, token, output_path)
|
||||
|
||||
logger.info(f"Processing repository: {org_name}/{repo_name}")
|
||||
Downloader(org_name, repo_name, token, max_retries=20).download_repo(collection_path, include=include)
|
||||
logger.info("Processing complete")
|
||||
|
||||
def get_tasks(csv_path: Path, output_path: Path, collection: str, skip_rows: int = 0, skip_existing: bool = False, stop_after: int = None, include: str = None,
|
||||
check_exists: bool = False):
|
||||
"""Get repositories from CSV that haven't been processed yet."""
|
||||
# Initialize progress bars
|
||||
if not check_exists:
|
||||
stats_counter['total'] = tqdm(desc="Total records", unit="repo")
|
||||
if skip_existing:
|
||||
stats_counter['skipped'] = tqdm(desc="Skipped", unit="repo")
|
||||
stats_counter['yielded'] = tqdm(desc="Processing", unit="repo")
|
||||
|
||||
# handle --include
|
||||
if include:
|
||||
include = include.split(',')
|
||||
else:
|
||||
include = ['repo_info']
|
||||
|
||||
# import token or tokens
|
||||
config = load_config()
|
||||
if config.get('tokens'):
|
||||
tokens = config['tokens']
|
||||
else:
|
||||
tokens = [get_token(None)]
|
||||
if tokens != [None]:
|
||||
logger.warning(f"Using {len(tokens)} tokens")
|
||||
else:
|
||||
logger.warning("Using unauthenticated rate limits")
|
||||
|
||||
with open(csv_path, 'r') as file:
|
||||
reader = csv.DictReader(file)
|
||||
# Skip specified number of rows
|
||||
for _ in range(skip_rows):
|
||||
next(reader)
|
||||
|
||||
processed = 0
|
||||
for row in reader:
|
||||
if not check_exists:
|
||||
stats_counter['total'].update(1)
|
||||
|
||||
if not row['html_url']: # Skip empty rows
|
||||
continue
|
||||
|
||||
org_name, repo_name = row['html_url'].split('/')[-2:]
|
||||
collection_path = output_path / 'collections' / collection / org_name / repo_name
|
||||
|
||||
if skip_existing:
|
||||
if collection_path.exists():
|
||||
stats_counter['skipped'].update(1)
|
||||
continue
|
||||
else:
|
||||
stats_counter['yielded'].update(1)
|
||||
|
||||
# use tokens round robin
|
||||
token = tokens[processed % len(tokens)]
|
||||
|
||||
yield org_name, repo_name, collection_path, include, token, check_exists, output_path
|
||||
|
||||
processed += 1
|
||||
if stop_after and processed >= stop_after:
|
||||
break
|
||||
|
||||
# Close progress bars
|
||||
for counter in stats_counter.values():
|
||||
counter.close()
|
||||
|
||||
@click.command()
|
||||
@click.option('--output-path', '-o', type=click.Path(path_type=Path), default='data/processed',
|
||||
help='Output path.')
|
||||
@click.option('--collection', '-c', type=str, default='github_raw',
|
||||
help='Collection name.')
|
||||
@click.option('--workers', '-w', type=int, default=None,
|
||||
help='Number of worker processes. Defaults to CPU count.')
|
||||
@click.option('--skip-rows', type=int, default=0,
|
||||
help='Number of rows to skip in the CSV.')
|
||||
@click.option('--include',
|
||||
help='Comma-separated list of elements to include: ' + ', '.join(valid_include_items))
|
||||
@click.option('--csv-path', '-csv', type=click.Path(path_type=Path), default='data/repos_by_cumulative_popularity.csv',
|
||||
help='Path to the CSV file.')
|
||||
@click.option('--log-level', '-l',
|
||||
type=click.Choice(['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL']),
|
||||
default=None,
|
||||
help='Logging level.')
|
||||
@click.option('--stop-after', help='Stop after processing this many repositories', type=int)
|
||||
@click.option('--skip-existing', is_flag=True, help='Set to skip existing repositories')
|
||||
@click.option('--check-exists', is_flag=True, help='Only check if repositories still exist on GitHub')
|
||||
def main(csv_path: Path, output_path: Path, collection: str, workers=None, skip_rows=0, include=None,
|
||||
log_level=None, stop_after=None, skip_existing=False, check_exists=False):
|
||||
|
||||
run_parallel(
|
||||
run_pipeline,
|
||||
get_tasks(csv_path, output_path, collection, skip_rows, skip_existing, stop_after, include, check_exists),
|
||||
workers,
|
||||
log_level=log_level
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
13
scripts/helpers/config.py
Normal file
13
scripts/helpers/config.py
Normal file
|
|
@ -0,0 +1,13 @@
|
|||
import json
|
||||
import os
|
||||
from pathlib import Path
|
||||
|
||||
CONFIG_PATH = (os.environ.get("XDG_CONFIG_HOME") or (Path.home() / ".config")) / "data-mirror" / "config.json"
|
||||
|
||||
def load_config():
|
||||
"""Load configuration from config file."""
|
||||
if CONFIG_PATH.exists():
|
||||
config = json.loads(CONFIG_PATH.read_text())
|
||||
else:
|
||||
config = {}
|
||||
return config
|
||||
65
scripts/helpers/parallel.py
Normal file
65
scripts/helpers/parallel.py
Normal file
|
|
@ -0,0 +1,65 @@
|
|||
from multiprocessing import Queue, Process
|
||||
from queue import Empty
|
||||
import os
|
||||
from tqdm import tqdm
|
||||
from typing import Callable, Iterable
|
||||
import logging
|
||||
|
||||
# Set up logger
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
def worker(task_queue, task, catch_errors: bool = True):
|
||||
while True:
|
||||
try:
|
||||
args = task_queue.get(timeout=1)
|
||||
if args is None:
|
||||
break
|
||||
logger.debug(f"[PID {os.getpid()}] Processing task")
|
||||
task(*args)
|
||||
except Empty:
|
||||
continue
|
||||
except Exception as e:
|
||||
if catch_errors:
|
||||
logger.error(f"[PID {os.getpid()}] Worker error: {e}")
|
||||
else:
|
||||
raise e
|
||||
|
||||
|
||||
def run_parallel(processor: Callable, tasks: Iterable, workers = None, catch_errors: bool = True, log_level: str | None = None, task_count: int | None = None):
|
||||
workers = workers or os.cpu_count() or 4
|
||||
|
||||
# Configure logging based on whether we're running in parallel or not
|
||||
if log_level is None:
|
||||
log_level = 'INFO' if workers == 1 else 'WARNING'
|
||||
logging.basicConfig(
|
||||
level=log_level,
|
||||
format='[%(process)d] %(message)s'
|
||||
)
|
||||
|
||||
logger.debug(f"Starting processing with {workers} workers")
|
||||
|
||||
if workers > 1:
|
||||
task_queue = Queue(maxsize=100)
|
||||
|
||||
# Start worker processes
|
||||
processes = []
|
||||
for _ in range(workers):
|
||||
p = Process(target=worker, args=(task_queue, processor, catch_errors))
|
||||
p.start()
|
||||
processes.append(p)
|
||||
|
||||
# Load tasks into queue
|
||||
for task_item in tqdm(tasks, total=task_count):
|
||||
if workers > 1:
|
||||
task_queue.put(task_item)
|
||||
else:
|
||||
processor(*task_item)
|
||||
|
||||
if workers > 1:
|
||||
# Signal workers to exit
|
||||
for _ in range(workers):
|
||||
task_queue.put(None)
|
||||
|
||||
# Wait for all processes to complete
|
||||
for p in processes:
|
||||
p.join()
|
||||
745
uv.lock
generated
Normal file
745
uv.lock
generated
Normal file
|
|
@ -0,0 +1,745 @@
|
|||
version = 1
|
||||
requires-python = ">=3.12"
|
||||
|
||||
[[package]]
|
||||
name = "aiosqlite"
|
||||
version = "0.20.0"
|
||||
source = { registry = "https://pypi.org/simple" }
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dependencies = [
|
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{ name = "typing-extensions" },
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]
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wheels = [
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]
|
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|
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[[package]]
|
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name = "annotated-types"
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wheels = [
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]
|
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|
||||
[[package]]
|
||||
name = "anyio"
|
||||
version = "4.7.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "idna" },
|
||||
{ name = "sniffio" },
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{ name = "typing-extensions", marker = "python_full_version < '3.13'" },
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wheels = [
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|
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[[package]]
|
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name = "bagit"
|
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|
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source = { registry = "https://pypi.org/simple" }
|
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|
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[[package]]
|
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|
||||
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|
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|
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|
||||
{ name = "botocore" },
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|
||||
[[package]]
|
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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[[package]]
|
||||
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|
||||
[[package]]
|
||||
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|
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|
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version = "1.0.3"
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source = { registry = "https://pypi.org/simple" }
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/37/87/1f677586e8ac487e29672e4b17455758fce261de06a0d086167bb760361a/uc_micro_py-1.0.3-py3-none-any.whl", hash = "sha256:db1dffff340817673d7b466ec86114a9dc0e9d4d9b5ba229d9d60e5c12600cd5", size = 6229 },
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[[package]]
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||||
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version = "2.2.3"
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source = { registry = "https://pypi.org/simple" }
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sdist = { url = "https://files.pythonhosted.org/packages/ed/63/22ba4ebfe7430b76388e7cd448d5478814d3032121827c12a2cc287e2260/urllib3-2.2.3.tar.gz", hash = "sha256:e7d814a81dad81e6caf2ec9fdedb284ecc9c73076b62654547cc64ccdcae26e9", size = 300677 }
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/ce/d9/5f4c13cecde62396b0d3fe530a50ccea91e7dfc1ccf0e09c228841bb5ba8/urllib3-2.2.3-py3-none-any.whl", hash = "sha256:ca899ca043dcb1bafa3e262d73aa25c465bfb49e0bd9dd5d59f1d0acba2f8fac", size = 126338 },
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]
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|
||||
[[package]]
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||||
name = "warcio"
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version = "1.7.5"
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||||
source = { registry = "https://pypi.org/simple" }
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dependencies = [
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||||
{ name = "six" },
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]
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/5c/f0/3f19085980f8a4485f4265cc9dba1099b2fa35ef7552390a8446e149c293/warcio-1.7.5-py2.py3-none-any.whl", hash = "sha256:ca96130bde7747e49da714097d144c6ff939458d4f93e1beb1e42455db4326d4", size = 40568 },
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||||
]
|
||||
Loading…
Add table
Reference in a new issue