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Dictionary in which the *insertion* order of items is preserved (using an internal double linked list). In this implementation replacing an existing item keeps it at its original position.
|Build Status| |Doc Status| Data migration in PythonDocumentation_Example Odo migrates data between different containers.. codeblock:: python >>> from odo import odo >>> odo((1, 2, 3), list) [1, 2, 3]It operates on small, inmemory containers (as above) and large, outofcore containers (as below).. codeblock:: python >>> odo('myfile.hdf5::/data', ':pass@host::mytable') Table('mytable', ...
Python-oembed This library provides a pure python OEmbed consumer to get resources from OEmbed providers.Based on reference from is a format for allowing an embedded representation of a URL on third party sites. The simple API allows a website to display embedded content (such as photos or videos) when a user posts a link to that resource, without having to parse the resource directly.OEmbed...
ofxparse is a parser for Open Financial Exchange (.ofx) format files. OFX files are available from almost any online banking site, so they work well if you want to pull together your finances from multiple sources. Online trading accounts also provide account statements in OFX files.
olefile is a Python package to parse, read and write Microsoft OLE2 files (also called Structured Storage, Compound File Binary Format or Compound Document File Format), such as Microsoft Office 97-2003 documents, vbaProject.bin in MS Office 2007+ files, Image Composer and FlashPix files, Outlook messages, StickyNotes, several Microscopy file formats, McAfee antivirus quarantine files, etc. Python3 version.
Ollama Python Library The Ollama Python library provides the easiest way to integrate Python 3.8+ projects with Ollama. Prerequisites Ollama should be installed and running Pull a model to use with the library: ollama pull <model> e.g. ollama pull llama3.2 See Ollama.com for more information on the models available. Usage from ollama import chat from ollama import ChatResponse response: ChatResponse = chat(model='llama3.2', messages=[ { 'role': 'user', 'content': 'Why is the sky blue?', }, ]) print(response['message']['content']) print(response.message.content)
This is a metapackage bringing in datalib extras requires for python3-openai. It makes sure the dependencies are installed.
This is a metapackage bringing in realtime extras requires for python3-openai. It makes sure the dependencies are installed.
This is a metapackage bringing in voice_helpers extras requires for python3-openai. It makes sure the dependencies are installed.