vsphere-automation-sdk-python
nba_api
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| vsphere-automation-sdk-python | nba_api | |
|---|---|---|
| 4 | 55 | |
| 726 | 2,238 | |
| 1.8% | - | |
| 6.3 | 7.1 | |
| about 2 months ago | 13 days ago | |
| Python | Python | |
| MIT License | 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.
vsphere-automation-sdk-python
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Would anyone be interested in a web app for managing bare metal/kvms? Details in comments.
On the other hand, for VMWare I decide to use their API. For this I'd look at the Python libraries for VMWare (see [here](https://github.com/vmware/pyvmomi)) and start reading the documentation. I'd write simple scripts that do the things I want to do. There are some great [code samples](https://github.com/vmware/vsphere-automation-sdk-python) to even get you started.
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AttributeError: module 'pyVmomi.VmomiSupport' has no attribute 'VmomiJSONEncoder'
I've used this command line to install it on my Debian 12 virtual machine : bash pip install --upgrade git+https://github.com/vmware/vsphere-automation-sdk-python.git
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Using Ansible and Python in ESXi
Use a linux server to set things up for running the playbooks pip install pyvnomi pip install --upgrade git+https://github.com/vmware/vsphere-automation-sdk-python.git ansible-galaxy collection install community.vmware Make sure you have vcenter setup as this is where the magic happens (where the API and all the other capabilities exist) and you should be running at least vCenter Essentials Kit or Standard with a separate license for vCenter. The free version is kind of watered down and does not enable the APIs for full automation out of the box. You would need to use something similar to pexpect in order to orchestrate ssh commands that may or may not work in the free version.
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Help! I am mentally unable to learn ansible!
FROM python:3.7.6-stretch RUN pip3 install pip --upgrade RUN pip3 install ansible RUN apt-get update -y && \ DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \ sshpass RUN pip3 install --upgrade git+https://github.com/vmware/vsphere-automation-sdk-python.git RUN pip3 install --upgrade python-gitlab RUN ansible-galaxy collection install community.kubernetes RUN pip3 install openshift pyyaml kubernetes --user WORKDIR /ansible
nba_api
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An Analysis of How Chris Paul Has Affected His Teams (And How It May Impact the Warriors)
Thanks to the people putting together the open source nba_api, as well as the people at Basketball Reference and the NBA stats page.
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Stat Changes from Regular Season to Playoffs: 2022 - 2023 Season
NBA Stats API
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Scott Foster gets cracked in the face by Lebron. And Foster has his whistle in his mouth when it happens.
Yea ref stuff is hard to acquire. NBA api could b helpful tho and this is prob a good place to start
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NBA Game IDs to Playoff Game Numbers
I think you'll find this useful: https://github.com/swar/nba_api.
- Experiences with the different nba.com APIs? Which one would you recommend for play-by-play data to calculate player-specific ORtg or DRtg in a game?
- Don't have much experience using APIs, I'm trying to use one but do not know how to get it set up properly
- Trying to use an API in Python but I don't know how to set it up properly. Can I get some help?
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[OC] How does playoff basketball differ from the regular season? Analyzing team stats over the past 40 seasons
All data were collected using the nba_api. The dataset consists of per-game stat averages for all teams starting from the 1983-84 season through the 2021-22 season. In total: 1103 regular season teams, 624 of which made the playoffs in their respective years. Traditional stats include: PTS, FGM, FGA, FG_PCT, FG3M, FG3A, FG3_PCT, FTM, FTA, FT_PCT, OREB, DREB, REB, AST, STL, BLK, TOV, PF, PLUS_MINUS. Advanced stats include: NET_RATING, OFF_RATING, DEF_RATING, EFG_PCT, TS_PCT, PACE, OREB_PCT, DREB_PCT, REB_PCT, AST_PCT, AST_TO, AST_RATIO, TM_TOV_PCT. Note: for plus/minus and all of the advanced stats, I could only get data beginning from the 1997-98 season onwards, which resulted in 743 total regular season teams, 400 of which made the playoffs.
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Downloading stats from nba.com/stats
Is it not on the nba api? https://github.com/swar/nba_api/tree/master/docs/nba_api/stats/endpoints
- [Highlight] Poole gets a tech for passing the ball to the ref
What are some alternatives?
pyvmomi - VMware vSphere API Python Bindings
nbastatR - NBA Stats API Wrapper and more for R
community.vmware - Ansible Collection for VMware
ImportJSON - Import JSON into Google Sheets, this library adds various ImportJSON functions to your spreadsheet
hug - Embrace the APIs of the future. Hug aims to make developing APIs as simple as possible, but no simpler.
nba-stats-analysis - Jupyter Notebooks with Applications of Data Science and Analysis with NBA data, using the information available through the NBA Stats API.
ansible-ad-inventory - Ansible Active Directory Inventory script
Python-NSE-Option-Chain-Analyzer - The NSE has a website which displays the option chain in near real-time. This program retrieves this data from the NSE site and then generates useful analysis of the Option Chain for the specified Index or Stock. It also continuously refreshes the Option Chain and visually displays the trend in various indicators useful for Technical Analysis.
mega.py - Python library for the https://mega.nz/ API.
NBA-attendance-prediction - Attendance prediction tool for NBA games using machine learning. Full pipeline implemented in Python from data ingestion to prediction. Attained mean absolute error of around 800 people (about 5% capacity) on test set.
twitter-stream.py - Python API Client for Twitter API v2
td-ameritrade-python-api - Unofficial Python API client library for TD Ameritrade. This library allows for easy access of the Standard API and allows users to build data pipelines for the Streaming API.