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discogs-xml2db v2

discogs-xml2db is a python program for importing discogs data dumps into several databases.

Version 2 is a rewrite of the original discogs-xml2db (referred in here as the classic version).
It is based on a branch by RedApple and it is several times faster.

Currently supports MySQL and PostgreSQL as target databases. Instructions for importing into MongoDB, though these are untested.
Let us know how it goes!

Experimental version

In parallel to the original Python codebase, we're working on a parser/exporter that's even faster. This is a complete rewrite in C# and initial results are highly promising:

File Record Count Python C#
discogs_20200806_artists.xml.gz 7,046,615 6:22 2:35
discogs_20200806_labels.xml.gz 1,571,873 1:15 0:22
discogs_20200806_masters.xml.gz 1,734,371 3:56 1:57
discogs_20200806_releases.xml.gz 12,867,980 1:45:16 42:38

If you're interested in testing one of this versions, read more about it in the .NET Parser README or grab the appropriate binaries from the Releases page.

While this version does not have yet complete feature-parity with the Python version, the core export-to-csv is there and it's likely it will eventually replace it.

DotNet Build

Running discogs-xml2db

Build Status - develop

Requirements

discogs-xml2db requires python3 (minimum 3.6) and some python modules.
Additionally, the bash shell is used for automating some tasks.

Importing to some databases may require additional dependencies, see the documentation for your target database below.

It's best that a Python virtual environment is created in order to install the required modules in a safe location, which does not require elevated security permissions:

# Create a virtual environment and activate it
$ python3 -m venv .discogsenv

# Activate virtual environment
# On Linux/macOS:
$ source .discogsenv/bin/activate
# on Windows, in Powershell
$ .discogsenv\Scripts\Activate.ps1

# Install requirements:
(.discogsenv) $ pip3 install -r requirements.txt

Installation instruction for other platforms can be found in the pip documentation.

Downloading discogs dumps

Download the latest dump files from discogs manually from discogs or run get_latest_dumps.sh.

To check the files' integrity download the appropriate checksum file from https://data.discogs.com/, place it in the same directory as the dumps and compare the checksums.

# run in folder where the data dump files have been downloaded
$ sha256sum -c discogs_*_CHECKSUM.txt

Converting dumps to CSV

Run run.py to convert the dump files to csv.

There are two run modes:

  1. You can point it to a directory where the discogs dump files are and use one or multiple --export options to indicate which files to process:
# ensure the virtual environment is active
(.discogsenv) $ python3 run.py \
  --bz2 \ # compresses resulting csv files
  --apicounts \ # provides more accurate progress counts
  --export artist --export label --export master --export release \
  --output csv-dir    # folder where to output the csv files
  dump-dir \ # folder where the data dumps are
  1. You can specify the individual files instead:
# ensure the virtual environment is active
(.discogsenv) $ python3 run.py \
  --bz2 \ # compresses resulting csv files
  --apicounts \ # provides more accurate progress counts
  --output csv-dir    # folder where to output the csv files
  path/to/discogs_20200806_artist.xml.gz path/to/discogs_20200806_labels.xml.gz

run.py takes the following arguments:

  • --export: the types of dump files to export: "artist", "label", "master", "release.
    It matches the names of the dump files, e.g. "discogs_20200806_artists.xml.gz" Not needed if the individual files are specified.
  • --bz2: Compresses output csv files using bz2 compression library.
  • --limit=<lines>: Limits export to some number of entities
  • --apicounts: Makes progress report more accurate by getting total amounts from Discogs API.
  • --output : the folder where to store the csv files; default it current directory

The exporter provides progress information in real time:

Processing      labels:  99%|█████████████████████████████████████████▊| 1523623/1531339 [01:41<00:00, 14979.04labels/s]
Processing     artists: 100%|████████████████████████████████████████▊| 6861991/6894139 [09:02<00:02, 12652.23artists/s]
Processing    releases:  78%|█████████████████████████████▌        | 9757740/12560177 [2:02:15<36:29, 1279.82releases/s]

The total amount and percentages might be off a bit as the exact amount is not known while reading the file.
Specifying --apicounts will provide more accurate predictions by getting the latest amounts from the Discogs API.

Importing

If pv is available it will be used to display progress during import.
To install it run $ sudo apt-get install pv on Ubuntu and Debian or check the installation instructions for other platforms.

Example output if using pv:

$ mysql/importcsv.sh 2020-05-01/csv/*
artist_alias.csv.bz2: 12,5MiB 0:00:03 [3,75MiB/s] [===================================>] 100%
artist.csv.bz2:  121MiB 0:00:29 [4,09MiB/s] [=========================================>] 100%
artist_image.csv.bz2:  7,3MiB 0:00:01 [3,72MiB/s] [===================================>] 100%
artist_namevariation.csv.bz2: 2,84MiB 0:00:01 [2,76MiB/s] [==>                         ] 12% ETA 0:00:07

Importing into PostgreSQL

# install PostgreSQL libraries (might be required for next step)
$ sudo apt-get install libpq-dev

# install the PostgreSQL package for python
# ensure the virtual environment has been activated
(.discogsenv) $ pip3 install -r postgresql/requirements.txt

# Configure PostgreSQL username, password, database, ...
$ nano postgresql/postgresql.conf

# Create database tables
(.discogsenv) $ python3 postgresql/psql.py < postgresql/sql/CreateTables.sql

# Import CSV files
(.discogsenv) $ python3 postgresql/importcsv.py /csvdir/*

# Configure primary keys and constraints, build indexes
(.discogsenv) $ python3 postgresql/psql.py < postgresql/sql/CreatePrimaryKeys.sql
(.discogsenv) $python3 postgresql/psql.py < postgresql/sql/CreateFKConstraints.sql
(.discogsenv) $ python3 postgresql/psql.py < postgresql/sql/CreateIndexes.sql

Importing into Mysql

# Configure MySQL username, password, database, ...
$ nano mysql/mysql.conf

# Create database tables
$ mysql/exec_sql.sh < mysql/CreateTables.sql

# Import CSV files
$ mysql/importcsv.sh /csvdir/*

# Configure primary keys and build indexes
$ mysql/exec_sql.sh < mysql/AssignPrimaryKeys.sql

Importing into MongoDB

The CSV files can be imported into MongoDB using mongoimport.

mongoimport --db=discogs --collection=releases --type=csv --headerline --file=release.csv

Importing into CouchDB

CouchDB only supports importing JSON files.
couchimport can be used to convert the CSV files to JSON and import them into CouchDB, as explained in this tutorial.

Comparison to classic discogs-xml2db

speedup is many times faster than classic because it uses a different approach:

  1. The discogs xml dumps are first converted into one csv file per database table.
  2. These csv files are then imported into the different target databases (bulk load).
    This is different from classic discogs-xml2db which loads records into the database one by one while parsing the xml file, waiting on the database after every row.

speedup requires less disk space than classic as it can work while the dump files are still compressed. While the uncompressed dumps for May 2020 take up 57GB of space the compressed dumps are only 8.8GB. The dumps can be deleted after converting them to compressed CSV files (6.1GB).

As many databases can import CSV files out of the box it should be easy to add support for more databases to discogs-xml2db speedup in the future.

Database schema changes

The database schema was changed in v2.0 to be more consistent and normalize some more data. The following things changed compared to classic discogs-xml2db:

  • renamed table: releases_labels => release_label
  • renamed table: releases_formats => release_format
  • renamed table: releases_artists => release_artist
  • renamed table: tracks_artists => release_track_artist
  • renamed table: track => release_track
  • renamed column: release_artists.join_relation => release_artist.join_string
  • renamed column: release_track_artist.join_relation => release_track_artist.join_string
  • renamed column: release_format.format_name => release_format.name
  • renamed column: label.contactinfo => label.contact_info
  • renamed column: label.parent_label => label.parent_name
  • added: label has new parent_id field
  • added: release_label has extra fields
  • moved: aliases now in artist_alias table
  • moved: tracks_extra_artists now in track_artist table with extra flag
  • moved: releases_extra_artists now in release_track_artist table with extra flag
  • moved: release.genres now in own release_genre table
  • moved: release.styles now in own release_style table
  • moved: release.barcode now in release_identifier table
  • moved: artist.anv fields now in artist_namevariation table
  • moved: artist.url fields now in artist_url table
  • removed: release_format.position no longer exists but can use id field to preserve order when release has multiple formats.
  • release_track_artist now use tmp_track_id to match to tmp_track in release_track

Running discogs-xml2db classic

To run the classic version of discogs-xml2db, check out the v1.99 git tag.
It contains both the classic and the speed-up version.

Please be aware that the classic version is no longer maintained.