PetroVisor Python API 0.1.9

This is a patch release in the 0.1.x series. It focuses on bug fixes, as well as performance and stability improvements.

Below are some of the highlights from this release:

• load_signals_data(): added loading signals with specified unit "signal name [unit name]"
• save_table_data(): when saving signals data the checks are performed not only for existing entities, but also for opportunities
• upload_object(), get_object(): when filename contains extention '.csv' or '.xlsx', the DataFrame will be saved and loaded using corresponding format
• backward compatibility with Python 3.7+
• more tests are added for Python 3.7-3.12

PetroVisor Python API package can be installed using pip

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)
PetroVisor Web API (EU1)

To get more familiar with the PetroVisor platform, please follow the articles hosted on the Datagration Knowledge Base

PetroVisor Python API 0.1.8

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.

• fixed loading of PivotTables with string data columns
• fixed saving RefTables with numeric column names, i.e. 0, 1, 2, etc.
• added default log entries such as workspace name and category for easier filtering in the app

PetroVisor Python API package can be installed using pip

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)
PetroVisor Web API (EU1)

To get more familiar with the PetroVisor platform, please follow the articles hosted on the Datagration Knowledge Base

PetroVisor Python API 0.1.7

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.

• added more examples for loading signals data
• fixed contex_manager bug for overriding entity_set

PetroVisor Python API package can be installed using pip

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)
PetroVisor Web API (EU1)

To get more familiar with the PetroVisor platform, please follow the articles hosted on the Datagration Knowledge Base

PetroVisor Python API 0.1.5

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

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)
PetroVisor Web API (EU1)

To get more familiar with the PetroVisor platform, please follow the articles hosted on the Datagration Knowledge Base

PetroVisor Python API 0.1.3

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

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)
PetroVisor Web API (EU1)

To get more familiar with the PetroVisor platform, please follow the articles hosted on the Datagration Knowledge Base

PetroVisor Python API 0.1.2

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

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)
PetroVisor Web API (EU1)

To get more familiar with the PetroVisor platform, please follow the articles hosted on the Datagration Knowledge Base

PetroVisor Python API 0.1.1

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

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, Signals, Entities, Workspace Values, Reference Tables, Pivot Tables
• Functions for executing scripts, written in domain-specific 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 DataFrame
• Methods for the execution of Workflows, which can be written in Python, R, C#, or any other language of your choice through the Web Activity interface of the PetroVisor platform
• Basic functionality for training Machine Learning models and getting pre-training and post-training statistics
• Methods for working with files of Workspace storage, including the capability of uploading native Python objects using the "pickling" and "unpickling" process
• Methods for importing and exporting DataGrids, 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 map right from PetroVisor

Please refer to the documentation of all available PetroVisor REST API endpoints using the up-to-date Swagger links
PetroVisor Web API (US1)
PetroVisor Web API (EU1)

To get more familiar with the PetroVisor platform, please follow the articles hosted on the Datagration Knowledge Base