govcookiecutter
splink
| govcookiecutter | splink | |
|---|---|---|
| 1 | 16 | |
| 132 | 1,091 | |
| 0.0% | 2.8% | |
| 4.3 | 9.9 | |
| 3 months ago | 3 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
govcookiecutter
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New DS here. Where can I learn best practices for organizing a project, folder structure, BASH scripting/scheduling, etc?
For testing your statistical assumptions and performance, govcookiecutter is worth a look for its integration of agile and baked in unit testing, see: https://github.com/best-practice-and-impact/govcookiecutter
splink
- Splink: Fast, accurate, scalable probabilistic data linkage
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Ask HN: What projects are you working on?
https://github.com/moj-analytical-services/splink
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Record linkage/Entity linkage
Record linkage has been a big part of a project I've been working on for 6 months now. I personally think a great and free solution be using the splink package in Python which can handle 10+m rows which implements the Fellegi-Sunter model (equivalent to a naive-Bayes model) is the classical model in record linkage. It can be trained in an unsupervised manner using some initial parameter estimation (these are quite intuitive) and then expectation maximisation. The features in the model will be different pairwise string comparisons on your field of interest. These can include exact equality; edit distance comparisons like Levensthein distance and Jaro-Winkler; and phonetic comparisons like soundex and double metaphone. The splink pacakge will handle training the model and then all the graph theory at the end to connect all your links into clusters. All the details you'll need are in the links. https://www.robinlinacre.com/probabilistic\_linkage/ https://moj-analytical-services.github.io/splink/
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What is the best approach to removing duplicate person records if the only identifier is person firstname middle name and last name? These names are entered in varying ways to the DB, thus they are free-fromatted.
https://moj-analytical-services.github.io/splink/ is a FOSS python package (but it runs against your db using SQL).
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DuckDB – in-process SQL OLAP database management system
If you're curious, I've written a FOSS record linkage library that executes everything as SQL. It supports multiple SQL backends including DuckDB and Spark for scale, and runs faster than most competitors because it's able to leverage the speed of these backends: https://github.com/moj-analytical-services/splink
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Ask HN: What have you created that deserves a second chance on HN?
Splink - a python library for probabilistic record linkage (fuzzy matching/entity resolution).
Splink is dramatically faster and works on much larger datasets than other open source libraries. I'm particularly proud of the fact we support multiple execution backends (at the moment, DuckDb Spark Athena and Sqlite, but additional adaptors are relatively straightforward to write).
We've had >4 million pypi downloads and it's used in government, academia and the private sector, often replacing extremely expensive proprietary solutions.
https://github.com/moj-analytical-services/splink
More info in blog posts here:
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Conformed Dimensions problem that keeps recurring on every project
Splink is a SQL tool that can do this https://github.com/moj-analytical-services/splink
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How do you join two sources with attributes that aren't identical?
Probabilistic record matching model such as a Fellegi-Sunter. Check out the splink package in Python.
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Splink 3: Fast, accurate and scalable record linkage (entity resolution) in Python
Main docs here: https://moj-analytical-services.github.io/splink
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Splink 3: Fast, accurate and scalable fuzzy record linkage in Python with support for multiple backends (FOSS)
It'd be great to see Splink add value in this area! Do give us a shout if you have any questions. The best place to post is on the Github discussions: https://github.com/moj-analytical-services/splink/discussions
What are some alternatives?
workspace-dotfiles-ansible - Automated and periodically configure workspace based on cronjob.
zingg - Scalable identity resolution, entity resolution, data mastering and deduplication using ML
cookiecutter-data-science - A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
dedupe - :id: A python library for accurate and scalable fuzzy matching, record deduplication and entity-resolution.
dslp - The Data Science Lifecycle Process is a process for taking data science teams from Idea to Value repeatedly and sustainably. The process is documented in this repo.
libpostal - A C library for parsing/normalizing street addresses around the world. Powered by statistical NLP and open geo data.
robs_awesome_python_template - A Highly Configurable Python Project Template for Modern Python Projects
sqlglot - Python SQL Parser and Transpiler
entity-embed - PyTorch library for transforming entities like companies, products, etc. into vectors to support scalable Record Linkage / Entity Resolution using Approximate Nearest Neighbors.
dblink - Distributed Bayesian Entity Resolution in Apache Spark
KaithemAutomation - Pure Python, GUI-focused home automation/consumer grade SCADA
splink_demos - Interactive notebooks containing demonstration code of the splink library