Top 23 Python Metric Projects
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datasets
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Project mention: FauxPilot – an open-source GitHub Copilot server | news.ycombinator.com | 2022-08-02And then pass that my_code.json as the dataset name.
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ignite
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently. (by pytorch)
Along with the PyTorch-Ignite 0.4.5 release, we are excited to announce the new release of the web application for generating PyTorch-Ignite's training pipelines. This blog post is an overview of the key features and updates of the Code Generator v0.2.0 project release.
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SonarLint
Clean code begins in your IDE with SonarLint. Up your coding game and discover issues early. SonarLint is a free plugin that helps you find & fix bugs and security issues from the moment you start writing code. Install from your favorite IDE marketplace today.
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Project mention: Setup Grafana with Prometheus for Python projects using Docker | dev.to | 2022-06-11
The code above is copied from the official documentation of prometheus_client which simply creates a new metric named request_processing_seconds that measures the time spent on that particular request. We'll cover other types of metrics later in this post.
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PyTorch-NLP
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CSrankings
A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.
Project mention: Profile Evaluation for MS CS in Fall '23 | reddit.com/r/gradadmissions | 2022-08-15Don't ask for direct university recommendations. First, search for places that meet your needs. You're looking for places with good ML & Systems research, so use a combination of Csrankings and US News rankings to try and get a feel of what universities are good for the subjects you want to study. If you're looking to do research, another excellent way of shortlisting is by seeing where the folks you cited in your research currently teach. Its an excellent organic way to highlight why you're applying to a specific university.
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Project mention: Best practices for setting up monitoring for a Dockerized Django app on Ubuntu 20.04? | reddit.com/r/django | 2021-12-27
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Project mention: [R] Single-task Continual/Incremental/Online/Life-Long learning. | reddit.com/r/MachineLearning | 2022-07-09
Lastly, there are several github repo, but the most popular one is ContinualAI/avalanche, which already implement some of above algorithm, for the purpose of reproducibility i.e. can be applied to your task (probably)
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Scout APM
Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.
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resoto
Resoto creates an inventory of your cloud, provides deep visibility, and reacts to changes in your infrastructure. ⚡️
Project mention: Write code that reacts to changes in your cloud infrastructure (AWS, GCP, DigitalOcean). | reddit.com/r/coolgithubprojects | 2022-07-30 -
Project mention: Show HN: Soda Core is now GA – Test data like you would test your code | news.ycombinator.com | 2022-06-28
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review_object_detection_metrics
Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box formats as in COCO, PASCAL, Imagenet, etc.
Project mention: Links to papers or books that discuss model evaluation methods for object detection models | reddit.com/r/computervision | 2022-03-25This is a good repository for you to start. https://github.com/rafaelpadilla/review_object_detection_metrics Ultimately you would want to compute the precision, recall, average precision, average recall, and mean Average Precision (mAP) that you’ve probably seen in many papers. Good luck!
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Project mention: Show HN: MetricFlow – open-source metric framework | news.ycombinator.com | 2022-04-06
Three things:
First, MetricFlow does not currently support MySQL. We launched with support for BigQuery, Redshift, and Snowflake. I have opened an issue to add support for MySQL (and similar issues for other SQL engines are coming): https://github.com/transform-data/metricflow/issues/27
Second, what we call a data source is more similar to a table in a database, rather than the underlying database service itself. Metricflow itself is useful when you're using a single SQL engine - indeed, that's all we support today - but it is most useful when you're in a world where joins are a thing. That said, if you have one big data table you might still find it useful to have declarative metric definitions defined in Metricflow. Suppose, for example, you had a big NoSQL style table filled with JSON objects. You might define a few data sources that normalize those JSON objects into top level elements (identifiers, dimensions, aggregated measures) using the sql_query data source config attribute, and then that'd allow you to support structured queries on the data consumption end while pushing unstructured blobs from your application layer. This will be slow at query time, and only as reliable as the level of discipline exerted in your application development workflow, but it's possible.
Third, if we did support MySQL you'd basically connect to it via standard connection parameters - we have a config file where you can store the required information and then we'll manage the connections for you. However, I'm not familiar with uxwizz, and a quick perusal of their documentation did not turn up how one goes about connecting to the underlying DB. It's likely I just missed this, but at any rate I don't know how it is done. If they don't support standard MySQL client connections you'd need to write an adapter of some kind against whatever DB connection APIs they provide, in which case you'd likely need to roll a custom implementation of MetricFlow's SqlClient interface and initialize the MetricFlowEngine with that.
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For my needs, the Chrome Platform Status Roadmap may be able replace the V8 blog – if it had a feed (RSS, Atom and/or JSON Feed). I’ve filed an issue: https://github.com/GoogleChrome/chromium-dashboard/issues/1948
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Then you can use a role like this.
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There is a way to install separately StatsD server and Graphite but for this tutorial, I'll just use the official Graphite docker image that also includes the StatsD server.
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Project mention: Monitoring data from query using prometheus? | reddit.com/r/PrometheusMonitoring | 2022-02-10
Isn't this an exporter which is able to do what you want? https://github.com/albertodonato/query-exporter
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image-similarity-measures
:chart_with_upwards_trend: Implementation of eight evaluation metrics to access the similarity between two images. The eight metrics are as follows: RMSE, PSNR, SSIM, ISSM, FSIM, SRE, SAM, and UIQ.
Project mention: I matched 400+ images to create illusion of motion [epilepsy] | reddit.com/r/woahdude | 2021-09-11The easiest place to start is using the classical approaches such as implemented here. For the kind of qualitative assessments you're performing, you'd probably need to use some deep learning techniques but these generally require significant technical background to implement.
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I'm building an open source data observability platform - https://github.com/monosidev/monosi that visualizes metadata collected from data warehouses. Databricks is currently not supported (contributions welcome!), but it may help to take a look at how we approach the anomaly detection & visualization aspects.
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Project mention: Show HN: RexMex – A Recommender Systems Evaluation Metrics Library | news.ycombinator.com | 2022-01-04
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emerge
emerge is a source code analysis tool and dependency visualizer that can be used to gather insights about source code structure, metrics, dependencies and complexity of software projects. After scanning the source code of a project it provides you an interactive web interface to explore and analyze your project by using graph structures.
Project mention: Is it possible to generate a flow diagram from Javascript code? | reddit.com/r/vscode | 2021-09-06There's no VS Code extension for it AFAIK, but it's the best (and almost only) tool that I know which can do it for JavaScript code. There's also madge and emerge, in case the first one doesn't fit your needs.
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Python Metrics related posts
- Profile Evaluation for MS CS in Fall '23
- Best Uni of BSc Computer Science
- Global Colleges Tier List
- How to apply for a master's degree (M2) abroad
- Best universities for machine learning ?
- Write code that reacts to changes in your cloud infrastructure (AWS, GCP, DigitalOcean).
- Resoto: An open-source alternative to Google Cloud Asset Inventory
Index
What are some of the best open-source Metric projects in Python? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | datasets | 13,902 |
| 2 | ignite | 4,017 |
| 3 | client_python | 2,875 |
| 4 | PyTorch-NLP | 2,100 |
| 5 | CSrankings | 1,884 |
| 6 | django-prometheus | 1,063 |
| 7 | avalanche | 1,026 |
| 8 | resoto | 981 |
| 9 | soda-core | 947 |
| 10 | review_object_detection_metrics | 670 |
| 11 | metricflow | 637 |
| 12 | chromium-dashboard | 517 |
| 13 | prometheus_flask_exporter | 504 |
| 14 | ansible-node-exporter | 450 |
| 15 | torch-fidelity | 426 |
| 16 | docker-graphite-statsd | 417 |
| 17 | query-exporter | 302 |
| 18 | image-similarity-measures | 283 |
| 19 | monosi | 257 |
| 20 | piqa | 253 |
| 21 | rexmex | 245 |
| 22 | emerge | 236 |
| 23 | celery-exporter | 182 |
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