Programming Languages Infrastructure as Code (PL-IaC) enables IaC programs written in general-purpose programming languages like Python and TypeScript. The currently available PL-IaC solutions are Pulumi and the Cloud Development Kits (CDKs) of Amazon Web Services (AWS) and Terraform. This dataset provides metadata and initial analyses of all public GitHub repositories in August 2022 with an IaC program, including their programming languages, applied testing techniques, and licenses. Further, we provide a shallow copy of the head state of those 7104 repositories whose licenses permit redistribution. The dataset is available under the Open Data Commons Attribution License (ODC-By) v1.0.

Contents:

• metadata.zip: The dataset metadata and analysis results as CSV files.
• scripts-and-logs.zip: Scripts and logs of the dataset creation.
• LICENSE: The Open Data Commons Attribution License (ODC-By) v1.0 text.
• README.md: This document.
• redistributable-repositiories.zip: Shallow copies of the head state of all redistributable repositories with an IaC program.

This artifact is part of the ProTI Infrastructure as Code testing project: https://proti-iac.github.io.

Metadata

The dataset's metadata comprises three tabular CSV files containing metadata about all analyzed repositories, IaC programs, and testing source code files.

repositories.csv:

• ID (integer): GitHub repository ID
• url (string): GitHub repository URL
• downloaded (boolean): Whether cloning the repository succeeded
• name (string): Repository name
• description (string): Repository description
• licenses (string, list of strings): Repository licenses
• redistributable (boolean): Whether the repository's licenses permit redistribution
• created (string, date & time): Time of the repository's creation
• updated (string, date & time): Time of the last update to the repository
• pushed (string, date & time): Time of the last push to the repository
• fork (boolean): Whether the repository is a fork
• forks (integer): Number of forks
• archive (boolean): Whether the repository is archived
• programs (string, list of strings): Project file path of each IaC program in the repository

programs.csv:

• ID (string): Project file path of the IaC program
• repository (integer): GitHub repository ID of the repository containing the IaC program
• directory (string): Path of the directory containing the IaC program's project file
• solution (string, enum): PL-IaC solution of the IaC program ("AWS CDK", "CDKTF", "Pulumi")
• language (string, enum): Programming language of the IaC program (enum values: "csharp", "go", "haskell", "java", "javascript", "python", "typescript", "yaml")
• name (string): IaC program name
• description (string): IaC program description
• runtime (string): Runtime string of the IaC program
• testing (string, list of enum): Testing techniques of the IaC program (enum values: "awscdk", "awscdk_assert", "awscdk_snapshot", "cdktf", "cdktf_snapshot", "cdktf_tf", "pulumi_crossguard", "pulumi_integration", "pulumi_unit", "pulumi_unit_mocking")
• tests (string, list of strings): File paths of IaC program's tests

testing-files.csv:

• file (string): Testing file path
• language (string, enum): Programming language of the testing file (enum values: "csharp", "go", "java", "javascript", "python", "typescript")
• techniques (string, list of enum): Testing techniques used in the testing file (enum values: "awscdk", "awscdk_assert", "awscdk_snapshot", "cdktf", "cdktf_snapshot", "cdktf_tf", "pulumi_crossguard", "pulumi_integration", "pulumi_unit", "pulumi_unit_mocking")
• keywords (string, list of enum): Keywords found in the testing file (enum values: "/go/auto", "/testing/integration", "@AfterAll", "@BeforeAll", "@Test", "@aws-cdk", "@aws-cdk/assert", "@pulumi.runtime.test", "@pulumi/", "@pulumi/policy", "@pulumi/pulumi/automation", "Amazon.CDK", "Amazon.CDK.Assertions", "Assertions_", "HashiCorp.Cdktf", "IMocks", "Moq", "NUnit", "PolicyPack(", "ProgramTest", "Pulumi", "Pulumi.Automation", "PulumiTest", "ResourceValidationArgs", "ResourceValidationPolicy", "SnapshotTest()", "StackValidationPolicy", "Testing", "Testing_ToBeValidTerraform(", "ToBeValidTerraform(", "Verifier.Verify(", "WithMocks(", "[Fact]", "[TestClass]", "[TestFixture]", "[TestMethod]", "[Test]", "afterAll(", "assertions", "automation", "aws-cdk-lib", "aws-cdk-lib/assert", "aws_cdk", "aws_cdk.assertions", "awscdk", "beforeAll(", "cdktf", "com.pulumi", "def test_", "describe(", "github.com/aws/aws-cdk-go/awscdk", "github.com/hashicorp/terraform-cdk-go/cdktf", "github.com/pulumi/pulumi", "integration", "junit", "pulumi", "pulumi.runtime.setMocks(", "pulumi.runtime.set_mocks(", "pulumi_policy", "pytest", "setMocks(", "set_mocks(", "snapshot", "software.amazon.awscdk.assertions", "stretchr", "test(", "testing", "toBeValidTerraform(", "toMatchInlineSnapshot(", "toMatchSnapshot(", "to_be_valid_terraform(", "unittest", "withMocks(")
• program (string): Project file path of the testing file's IaC program

Dataset Creation

scripts-and-logs.zip contains all scripts and logs of the creation of this dataset. In it, executions/executions.log documents the commands that generated this dataset in detail. On a high level, the dataset was created as follows:

1. A list of all repositories with a PL-IaC program configuration file was created using search-repositories.py (documented below). The execution took two weeks due to the non-deterministic nature of GitHub's REST API, causing excessive retries.
2. A shallow copy of the head of all repositories was downloaded using download-repositories.py (documented below).
3. Using analysis.ipynb, the repositories were analyzed for the programs' metadata, including the used programming languages and licenses.
4. Based on the analysis, all repositories with at least one IaC program and a redistributable license were packaged into redistributable-repositiories.zip, excluding any node_modules and .git directories.

Searching Repositories

The repositories are searched through search-repositories.py and saved in a CSV file. The script takes these arguments in the following order:

1. Github access token.
2. Name of the CSV output file.
3. Filename to search for.
4. File extensions to search for, separated by commas.
5. Min file size for the search (for all files: 0).
6. Max file size for the search or * for unlimited (for all files: *).

Pulumi projects have a Pulumi.yaml or Pulumi.yml (case-sensitive file name) file in their root folder, i.e., (3) is Pulumi and (4) is yml,yaml. https://www.pulumi.com/docs/intro/concepts/project/

AWS CDK projects have a cdk.json (case-sensitive file name) file in their root folder, i.e., (3) is cdk and (4) is json. https://docs.aws.amazon.com/cdk/v2/guide/cli.html

CDK for Terraform (CDKTF) projects have a cdktf.json (case-sensitive file name) file in their root folder, i.e., (3) is cdktf and (4) is json. https://www.terraform.io/cdktf/create-and-deploy/project-setup

Limitations

The script uses the GitHub code search API and inherits its limitations:

• Only forks with more stars than the parent repository are included.
• Only the repositories' default branches are considered.
• Only files smaller than 384 KB are searchable.
• Only repositories with fewer than 500,000 files are considered.
• Only repositories that have had activity or have been returned in search results in the last year are considered.

More details: https://docs.github.com/en/search-github/searching-on-github/searching-code

The results of the GitHub code search API are not stable. However, the generally more robust GraphQL API does not support searching for files in repositories: https://stackoverflow.com/questions/45382069/search-for-code-in-github-using-graphql-v4-api

Downloading Repositories

download-repositories.py downloads all repositories in CSV files generated through search-respositories.py and generates an overview CSV file of the downloads. The script takes these arguments in the following order:

1. Name of the repositories CSV files generated through search-repositories.py, separated by commas.
2. Output directory to download the repositories to.
3. Name of the CSV output file.

The script only downloads a shallow recursive copy of the HEAD of the repo, i.e., only the main branch's most recent state, including submodules, without the rest of the git history. Each repository is downloaded to a subfolder named by the repository's ID.

Price Index of Private Rents (PIPR) data volumes, including volumes collected each month and volumes within the monthly dataset used by the PIPR model.

Non-traditional data signals from social media and employment platforms for PIPR stock analysis

The average rent in the private rental market in England reached 117.9 index points in January 2025, reflecting an annual percentage change of 8.8 percent. This marks a consistent upward trend, with the index value increasing by approximately 18 percent since the baseline year of January 2023. The Index of Private Housing Rental Prices measures the change in the price of renting residential property from private landlords, based on an index value of 100 in January 2023

The Price Index of Private Rents (PIPR) in England, Wales, and Scotland has shown significant growth, with Scotland reaching an index value of ***** points in January 2025, indicating an increase of **** percent since the baseline year of January 2023. The IPHRP measures the change in price of renting residential property from private landlords, based on an index value of 100 in January 2023. The IPHRP saw the highest growth in Wales, reaching ***** index points in January 2025 and suggesting an increase in private rents amounting to **** percent since the baseline year.

Historical StockTwits watcher counts and sentiment trend for PIPR (Piper Sandler Companies).

Pipe

## Overview

Pipe is a dataset for object detection tasks - it contains Pipes annotations for 680 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [Public Domain license](https://creativecommons.org/licenses/Public Domain).

The Price Index of Private Rents (PIPR) has shown significant growth, reaching a value of 117.9 in January 2025. This marks an increase of approximately 17.9 percent since January 2023, reflecting a robust upward trend in rental prices. Notably, the index saw a steady rise throughout 2024, with an annual percentage change peaking at 9.2 percent in March 2024. Mainstream properties are forecast to see rents further increase until 2028.

Explore the historical Whois records related to pipr.network (Domain). Get insights into ownership history and changes over time.

Month-over-month StockTwits watcher counts and percentage changes for PIPR.

The average rent for flats and maisonettes in the private rental market in Great Britain increased faster than any other property type as of January 2025. The Index of Private Housing Rental Prices measures the change in the price of renting residential property from private landlords, based on an index value of 100 in January 2023. In January 2025, the index value for flats and maisonettes amounted to 119.5 index point, suggesting an increase of nearly 20 percent since the baseline year. Detached houses increased by 16 percent.

AI-powered price forecasts for PIPR stock across different timeframes including weekly, monthly, yearly, and multi-year predictions.

Dataset Card for PIPE Dataset

  Dataset Summary

The PIPE (Paint by InPaint Edit) dataset is designed to enhance the efficacy of mask-free, instruction-following image editing models by providing a large-scale collection of image pairs and diverse object addition instructions. Comprising approximately 1 million image pairs, PIPE includes both source and target images, along with corresponding natural language instructions for object addition. The dataset leverages extensive… See the full description on the dataset page: https://huggingface.co/datasets/paint-by-inpaint/PIPE.

Oxidative addition of BrCCC(O)NR2 to [Pd(PPh3)4] affords the trans-alkynylbromopalladium complexes trans-Br(PPh3)2Pd−CCC(O)NR2 (2b)). Subsequent reaction of 2a,b with PiPr3 in excess gives trans-Br(PiPr3)2Pd−CCC(O)NR2. The analogous reaction of 2b with P(C6H4OMe-4)3 gives trans-Br(P{C6H4OMe-4}3)2Pd−CCC(O)NR2, and that of 2a with trifluoroacetate gives trans-(F3CCOO)(PPh3)2Pd−CCC(O)NMe2. Methylation of 2a,b, 7b, and 9a with either MeOTf or [Me3O]BF4 and ethylation of 2a,b with [Et3O]BF4 yield the first cationic allenylidene complexes of palladium, trans-[R*(PR′3)2Pd−CCC(OMe)NR2]+X− (R* = Br, CF3COO; R′ = Ph, C6H4OMe-4, iPr; X = OTf, BF4).

INDUSTRIAL PIPE DETECTION

## Overview

INDUSTRIAL PIPE DETECTION is a dataset for object detection tasks - it contains Pipes annotations for 741 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This dataset tracks annual diversity score from 1991 to 2023 for Piper High School vs. Kansas and Piper-Kansas City School District

The Price Index of Private Rents (PIPR) increased gradually since 2015 and reached a value of ***** in ************. That indicates a rental increase of ** percent since ************, the baseline year when the index was set to 100. The rental rates for mainstream properties are forecast to continue to grow over the next five years.

This page, "piPr-benzoate anion", is part of the NIST Chemistry WebBook. This site and its contents are part of the NIST Standard Reference Data Program.

This dataset was created using LeRobot.

  Dataset Structure

meta/info.json: { "codebase_version": "v2.1", "robot_type": "bi_piper", "total_episodes": 1, "total_frames": 2817, "total_tasks": 1, "total_videos": 3, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:1"}, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path":… See the full description on the dataset page: https://huggingface.co/datasets/HCHoongChing/bimanual-piper-dataset-threecam-test-10.

The main assets that Cadent owns are gas pipes. These pipes move gas from where gas enters our network to where it exits our network. This dataset contains information on low pressure and medium pressure pipe gas assets in all our distribution networks.This Data Asset shows these pipes owned by Cadent Gas Limited in its role as a Licensed Gas Transporter (GT). Gas pipe owned by other GT's or otherwise privately owned may be present in this area. Information with regards to such pipe should be obtained from the relevant owners. This data asset should NOT be used for digging practices. The information provided through https://cadentgas.opendatasoft.com/ is given without warranty, the accuracy thereof cannot be guaranteed. No liability of any kind whatsoever is accepted by Cadent Gas or their agents, servant or contractors for any errors or omission. For digging practices, please refer to LSBUD. https://lsbud.co.uk/Safe digging practices, in accordance with HS(G)47.This Data Asset replaces "GPI - Pipe Infrastructure - Open" and has been updated to comply with the Gas Network Interoperable Data Standard, enabling greater consistency and integration with similar data from other gas distribution networks.