Prometheus Exporter for data scraped from datenplattform.darmstadt.de

Martin Weinelt

Last update: Apr 12, 2022

Related tags

Deep Learning darmstadt-opendata-exporter

Overview

darmstadt-opendata-exporter

Scrapes data from https://datenplattform.darmstadt.de and presents it in the Prometheus Exposition format.

Pull requests welcome.

Example

# HELP darmstadt_environment_no2_micrograms_per_cubic_meter Environment measurement for no2
# TYPE darmstadt_environment_no2_micrograms_per_cubic_meter gauge
darmstadt_environment_no2_micrograms_per_cubic_meter{sensor="3ac073c4-b5b8-421d-b91a-5aa001234f7e"} 9.5615
# HELP darmstadt_environment_o3_micrograms_per_cubic_meter Environment measurement for o3
# TYPE darmstadt_environment_o3_micrograms_per_cubic_meter gauge
darmstadt_environment_o3_micrograms_per_cubic_meter{sensor="3ac073c4-b5b8-421d-b91a-5aa001234f7e"} 70.83670000000001
# HELP darmstadt_environment_pm2_5_micrograms_per_cubic_meter Environment measurement for dust_pm2.5
# TYPE darmstadt_environment_pm2_5_micrograms_per_cubic_meter gauge
darmstadt_environment_pm2_5_micrograms_per_cubic_meter{sensor="3ac073c4-b5b8-421d-b91a-5aa001234f7e"} 0.1
# HELP darmstadt_environment_so2_micrograms_per_cubic_meter Environment measurement for so2
# TYPE darmstadt_environment_so2_micrograms_per_cubic_meter gauge
darmstadt_environment_so2_micrograms_per_cubic_meter{sensor="3ac073c4-b5b8-421d-b91a-5aa001234f7e"} 0.8
# HELP darmstadt_environment_pm10_micrograms_per_cubic_meter Environment measurement for dust_pm10
# TYPE darmstadt_environment_pm10_micrograms_per_cubic_meter gauge
darmstadt_environment_pm10_micrograms_per_cubic_meter{sensor="3ac073c4-b5b8-421d-b91a-5aa001234f7e"} 0.1
# HELP darmstadt_environment_co_milligrams_per_cubic_meter Environment measurement for co
# TYPE darmstadt_environment_co_milligrams_per_cubic_meter gauge
darmstadt_environment_co_milligrams_per_cubic_meter{sensor="3ac073c4-b5b8-421d-b91a-5aa001234f7e"} 0.10592399999999999

You might also like...

[IJCAI-2021] A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation"

DataFree A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation" Authors: Gongfa

47 Jan 9, 2023

Data Preparation, Processing, and Visualization for MoVi Data

MoVi-Toolbox Data Preparation, Processing, and Visualization for MoVi Data, https://www.biomotionlab.ca/movi/ MoVi is a large multipurpose dataset of

51 Nov 27, 2022

Image transformations designed for Scene Text Recognition (STR) data augmentation. Published at ICCV 2021 Workshop on Interactive Labeling and Data Augmentation for Vision.

Data Augmentation for Scene Text Recognition (ICCV 2021 Workshop) (Pronounced as "strog") Paper Arxiv Why it matters? Scene Text Recognition (STR) req

152 Dec 28, 2022

code for paper "Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning" by Zhongzheng Ren, Raymond A. Yeh, Alexander G. Schwing.

Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning Overview This code is for paper: Not All Unlabeled Data are Equa

22 Nov 23, 2022

Angle data is a simple data type.

angledat Angle data is a simple data type. Installing + using Put angledat.py in the main dir of your project. Import it and use. Comments Comments st

1 Jan 5, 2022

Team nan solution repository for FPT data-centric competition. Data augmentation, Albumentation, Mosaic, Visualization, KNN application

FPT_data_centric_competition - Team nan solution repository for FPT data-centric competition. Data augmentation, Albumentation, Mosaic, Visualization, KNN application

2 Oct 30, 2022

Data-depth-inference - Data depth inference with python

Comments

Nix expression

{ pkgs, ... }:
{
  systemd.services.darmstadt-opendata-exporter = {
    wantedBy = [ "multi-user.target" ];
    serviceConfig = {
      DynamicUser = true;
      User = "darmstadt-opendata";
      ExecStart = let
        python = pkgs.python3.withPackages (py: with py; [
          requests
          prometheus_client
        ]);
        in
          "${python.interpreter} " + /path/to/darmstadt_opendata_exporter/__main__.py;
      Restart = "on-failure";
    };
  };
}

opened by mweinelt 0

Prometheus Exporter for data scraped from datenplattform.darmstadt.de

Related tags

Overview

darmstadt-opendata-exporter

Example

You might also like...

[IJCAI-2021] A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation"

Data Preparation, Processing, and Visualization for MoVi Data

Image transformations designed for Scene Text Recognition (STR) data augmentation. Published at ICCV 2021 Workshop on Interactive Labeling and Data Augmentation for Vision.

code for paper "Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning" by Zhongzheng Ren, Raymond A. Yeh, Alexander G. Schwing.

Angle data is a simple data type.

Team nan solution repository for FPT data-centric competition. Data augmentation, Albumentation, Mosaic, Visualization, KNN application

Data-depth-inference - Data depth inference with python

Pull sensitive data from users on windows including discord tokens and chrome data.

A data-driven approach to quantify the value of classifiers in a machine learning ensemble.

Comments

Nix expression

Owner

Martin Weinelt

Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt)

Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt)

Exporter for Storage Area Network (SAN)

Automatically download the cwru data set, and then divide it into training data set and test data set

A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.

The source code for the Cutoff data augmentation approach proposed in this paper: "A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation".

Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

Rayvens makes it possible for data scientists to access hundreds of data services within Ray with little effort.

nnDetection is a self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention. It includes guides for 12 data sets that were used to develop and evaluate the performance of the proposed method.

Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data

Prometheus Exporter for data scraped from datenplattform.darmstadt.de

Related tags

Overview

darmstadt-opendata-exporter

Example

You might also like...

[IJCAI-2021] A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation"

Data Preparation, Processing, and Visualization for MoVi Data

Image transformations designed for Scene Text Recognition (STR) data augmentation. Published at ICCV 2021 Workshop on Interactive Labeling and Data Augmentation for Vision.

code for paper "Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning" by Zhongzheng Ren*, Raymond A. Yeh*, Alexander G. Schwing.

Angle data is a simple data type.

Team nan solution repository for FPT data-centric competition. Data augmentation, Albumentation, Mosaic, Visualization, KNN application

Data-depth-inference - Data depth inference with python

Pull sensitive data from users on windows including discord tokens and chrome data.

A data-driven approach to quantify the value of classifiers in a machine learning ensemble.

Comments

Nix expression

Owner

Martin Weinelt

Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt)

Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt)

Exporter for Storage Area Network (SAN)

Automatically download the cwru data set, and then divide it into training data set and test data set

A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.

The source code for the Cutoff data augmentation approach proposed in this paper: "A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation".

Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

Rayvens makes it possible for data scientists to access hundreds of data services within Ray with little effort.

nnDetection is a self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention. It includes guides for 12 data sets that were used to develop and evaluate the performance of the proposed method.

Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data

code for paper "Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning" by Zhongzheng Ren, Raymond A. Yeh, Alexander G. Schwing.