plotly
Typesense
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plotly | Typesense | |
---|---|---|
65 | 129 | |
15,247 | 17,876 | |
2.3% | 4.4% | |
9.4 | 9.8 | |
7 days ago | 6 days ago | |
Python | C++ | |
MIT License | GNU General Public License v3.0 only |
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.
plotly
- Yes, Python and Matplotlib can make pretty charts
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Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/plotly/plotly.py
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How to Create a Pareto Chart 📐
First we need to install the Plotly. To create some very dynamic graphics, this tool helps a lot.
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For all you computational people: What’s your favorite plotting software?
my good dude wake up and smell the plotly. Knowing the ins and outs of matplotlib is helpful but doing interactive stuff with jupyter I always use plotly.
- What does Power BI offer?
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Other programing options?
Plotly documentation (https://plotly.com/python/)
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Advice on upgrading my Presentation template
I don´t know your workflow, but I use 2 markdown based presentations: obsidian advance slides and Quarto presentations. The former is a plugin for Obsidian, which is the software I use to take all my notes, write my thesis, etc., so It makes it extremely easy to make presentations since all my information is in Obsidian. In the other hand, Quarto is a publishing system (articles, presentations, websites books) that can be easily integrated with python and R. This makes it supper convenient for showing my data to my PI since I can analyze my data and at the same time make a presentation for the data. Besides this, Quarto also integrates with my Zotero library, so I can insert citations. Lastly, one thing that made my Quarto presentations infinitely better that the powerpoints, Is that I can insert interactive graphs with plotly, so when I'm showing my data, my PI is able to explore the data inside the presentation.
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[OC] Clustering Images with OpenAI CLIP, T-SNE, UMAP & Plotly
Plotly GitHub repository: https://github.com/plotly/plotly.py
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Could you recommend some graphing GitHub Repo. for JupyterLab?
I'm using plotly.py now. This is why I love this community.
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Anyone else feel ‘trapped’ in power bi?
Depending on the nature of your reporting requirements, you could output a formatted Excel document with Python and a library such as openpyxl, and shove that into your SharePoint environment. This would be less dynamic than PBI reports can be, but may be sufficient. If you want viz as well, you can use something like ggplot or Plotly. Again, less dynamic than PBI for the same effort.
Typesense
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Website Search Hurts My Feelings
There are actually plenty of non-ES products that are way easier to integrate and tune (and get better results with less effort).
- Typesense (https://github.com/typesense/typesense)
- Algolia
- Google Programmable Search Engine (https://programmablesearchengine.google.com/about/)
- Remote Machine Learning and Searching on a Raspberry Pi 5
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Open Source alternatives to tools you Pay for
Typesense - Open Source Alternative to Algolia
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DNS record "hn.algolia.com" is gone
If you like your penny take a look at Typesense https://typesense.org/ - nothing to complain here. Especially nothing complain about pricing.
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Vector databases: analyzing the trade-offs
I work on Typesense [1] (historically considered an open source alternative to Algolia).
We then launched vector search in Jan 2023, and just last week we launched the ability to generate embeddings from within Typesense.
You'd just need to send JSON data, and Typesense can generate embeddings for your data using OpenAI, PaLM API, or built-in models like S-BERT, E-5, etc (running on a GPU if you prefer) [2]
You can then do a hybrid (keyword + semantic) search by just sending the search keywords to Typesense, and Typesense will automatically generate embeddings for you internally and return a ranked list of keyword results weaved with semantic results (using Rank Fusion).
You can also combine filtering, faceting, typo tolerance, etc - the things Typesense already had.
[1] https://github.com/typesense/typesense
[2] https://typesense.org/docs/0.25.0/api/vector-search.html
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Creating an advanced search engine with PostgreSQL
For something small with a minimal footprint, I'd recommend Typesense. https://github.com/typesense/typesense
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Obsidian Publish full text search
I haven’t used Publish, but I’d assume you could use something like https://typesense.org/ to index and search the vault.
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DynamoDB search options
A cheaper option would be to use https://typesense.org. You can use DynamoDb streams to automatically load records. It has worked well for me.
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[Guide] A Tour Through the Python Framework Galaxy: Discovering the Stars
Try tigris | typesense for faster search
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Is it worth using Postgres' builtin full-text search or should I go straight to Elastic?
I’m also checking out Typesense as a possibility for replacing Elastic: https://typesense.org/
What are some alternatives?
Altair - Declarative statistical visualization library for Python
MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
bokeh - Interactive Data Visualization in the browser, from Python
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
matplotlib - matplotlib: plotting with Python
Apache Solr - Apache Lucene and Solr open-source search software
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
meilisearch-laravel-scout - MeiliSearch integration for Laravel Scout
folium - Python Data. Leaflet.js Maps.
loki - Like Prometheus, but for logs.
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
sonic - 🦔 Fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM.