Petrovisor

This is a patch release in the 0.1.x series. It includes bug fixes and performance and stability improvements.

Below are some of the highlights from this release.
- new objects `Context`, `Scope`, `EntitySet`, `Entity`, `Hierarchy`, and `Signal` are added for more seamless work with PetroVisor API serialization and deserialization. Dedicated Contexts and Signals related api calls can now take such objects as an argument
- new functions `create_contexts_manager` and `merged_contexts` are added to better manage passed Contexts to the script.
- requests timeout was removed to allow longer processes such as loading big amounts of data or running big workflow
- improved loading of string depth data, useful for marking up formations, logs, perforations

PetroVisor Python API package can be installed using `pip`

bash
python -m pip install petrovisor


Please refer to the documentation of all available PetroVisor REST API endpoints using the up-to-date Swagger links
[PetroVisor Web API (US1)](https://api.us1.petrovisor.com)
[PetroVisor Web API (EU1)](https://api.eu1.petrovisor.com)

To get more familiar with the PetroVisor platform, please follow the articles hosted on the [Datagration Knowledge Base](https://www.datagration.com/knowledge)

This is a patch release in the 0.1.x series. It includes bug fixes and performance and stability improvements.

Below are some of the highlights from this release.
- new api call `load_signals_data` to load different type of signals (static, time, depth) as DataFrame
- create Context, Scope, EntitySet, Hierarchy with the ability to override certain parts of the Context like start/end date etc.

PetroVisor Python API package can be installed using `pip`

bash
python -m pip install petrovisor


Please refer to the documentation of all available PetroVisor REST API endpoints using the up-to-date Swagger links
[PetroVisor Web API (US1)](https://api.us1.petrovisor.com)
[PetroVisor Web API (EU1)](https://api.eu1.petrovisor.com)

To get more familiar with the PetroVisor platform, please follow the articles hosted on the [Datagration Knowledge Base](https://www.datagration.com/knowledge)

This is a patch release in the 0.1.x series. It includes bug fixes and performance and stability improvements.

Below are some of the highlights from this release.
- new `RefTables` api calls, which are on par with `DataFrames` functionality and share the same representation
- improved loading of `P Tables` and `Pivot Tables`
- more consistent handling of `NaN` values
- more comprehensive error messages

PetroVisor Python API package can be installed using `pip`

bash
python -m pip install petrovisor


Please refer to the documentation of all available PetroVisor REST API endpoints using the up-to-date Swagger links
[PetroVisor Web API (US1)](https://api.us1.petrovisor.com)
[PetroVisor Web API (EU1)](https://api.eu1.petrovisor.com)

To get more familiar with the PetroVisor platform, please follow the articles hosted on the [Datagration Knowledge Base](https://www.datagration.com/knowledge)

We are pleased to announce the first release of a Python wrapper for PetroVisor REST API.

PetroVisor Python API package can be installed using `pip`

bash
python -m pip install petrovisor


The main functionality of this release includes:
- Basic `get`, `post`, `put`, and `delete` requests
- Methods for working with PetroVisor [`Items`](https://www.datagration.com/knowledge/how-do-i-work-with-data-in-petrovisor), [`Signals`](https://www.datagration.com/knowledge/what-is-on-the-signals-summary-page), [`Entities`](https://www.datagration.com/knowledge/overview-of-entities), [`Workspace Values`](https://www.datagration.com/knowledge/how-do-i-edit-workspace-values), [`Reference Tables`](https://www.datagration.com/knowledge/working-with-reference-tables-in-petrovisor), [`Pivot Tables`](https://www.datagration.com/knowledge/overview-of-tables-in-build)
- Functions for executing scripts, written in domain-specific [`P`](https://www.datagration.com/knowledge/what-is-p) language, which was designed specifically for engineers to process data in an easy yet powerful manner. As a result of running a `P#` script, the user gets a familiar and loved by everyone [`pandas`](https://pandas.pydata.org) `DataFrame`
- Methods for the execution of [`Workflows`](https://www.datagration.com/knowledge/how-do-workflows-work-in-petrovisor), which can be written in `Python`, [`R`](https://www.datagration.com/knowledge/how-can-i-use-r-in-petrovisor), [`C#`](https://www.nuget.org/packages/MyrConn.PetroVisor.Web.Client), or any other language of your choice through the [`Web Activity`](https://www.datagration.com/knowledge/external-activity) interface of the PetroVisor platform
- Basic functionality for training [`Machine Learning`](https://www.datagration.com/knowledge/how-do-i-run-a-machine-learning-model-in-petrovisor) models and getting pre-training and post-training statistics
- Methods for working with files of [`Workspace`](https://www.datagration.com/knowledge/what-are-workspaces-in-the-web-app-and-how-do-i-navigate-to-them) storage, including the capability of uploading native Python objects using the "pickling" and "unpickling" process
- Methods for importing and exporting [`DataGrids`](https://www.datagration.com/knowledge/overview-of-data-grids), which can store from simple point clouds to polygonal, and three-dimensional `Reservoir Grids`, with underlying properties. All of the grids and their properties can be later visualized on an embedded [`mapbox`](https://www.mapbox.com) map right from [PetroVisor](https://www.datagration.com/knowledge/how-do-i-set-up-layers-in-petrovisor)

Please refer to the documentation of all available PetroVisor REST API endpoints using the up-to-date Swagger links
[PetroVisor Web API (US1)](https://api.us1.petrovisor.com/index.html?__hstc=187844791.915eb7f16db6760da47f18781132b2ac.1677840296877.1677840296877.1678450552784.2&__hssc=187844791.4.1678450552784&__hsfp=3193161031)
[PetroVisor Web API (EU1)](https://api.eu1.petrovisor.com/index.html?__hstc=187844791.915eb7f16db6760da47f18781132b2ac.1677840296877.1677840296877.1678450552784.2&__hssc=187844791.4.1678450552784&__hsfp=3193161031)

To get more familiar with the PetroVisor platform, please follow the articles hosted on the [Datagration Knowledge Base](https://www.datagration.com/knowledge)