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Merge pull request #14 from edge-ml/king_test
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‎README.md‎

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# edge-ml python
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[![Tests](https://github.com/edge-ml/python/actions/workflows/tests.yml/badge.svg)](https://github.com/edge-ml/python/actions/workflows/tests.yml)
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[![PyPI Publish](https://github.com/edge-ml/python/actions/workflows/PyPIPublish.yml/badge.svg)](https://github.com/edge-ml/python/actions/workflows/PyPIPublish.yml)
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# Obtain data from edge-ml
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Python package for [edge-ml.org](https://edge-ml.org).
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## Usage
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### Installation
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Install edge-ml using the follwing command.
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```bash
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pip install edge-ml
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```python
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from edgeml import DatasetReceiver
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```
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### Retrieve Project
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This functionality comes in handy if you would like to train a machine learning model from edge-ml data.
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### 1. Create a project
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This will also pull the metadata from the server.
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Here you need the *read*-key.
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Make sure there is not trailing */* in your URL.
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```python
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from edgeml import edgeml
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project = DatasetReceiver("https://edge-ml-beta.dmz.teco.edu", "8c051972b56e6b4ad6bd0bf573da580f")
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print(project)
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```
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Dataset - Name: W_001, ID: 645a255bdd19d537f2a50126, Metadata: {}
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Dataset - Name: W_004, ID: 645a255b7d9569d03843a12b, Metadata: {}
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Dataset - Name: Square_003, ID: 645a255b2ce253c26b52426c, Metadata: {}
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Dataset - Name: Square_004, ID: 645a255b1d6af5e7ed04575f, Metadata: {}
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Dataset - Name: Square_002, ID: 645a255bc21261d4cbdc990d, Metadata: {}
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Dataset - Name: W_002, ID: 645a255b3ebe0af02b211d5d, Metadata: {}
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Dataset - Name: W_003, ID: 645a255b074737af782167e2, Metadata: {}
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Dataset - Name: Square_001, ID: 645a255bbacf5ab8ff044304, Metadata: {}
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Dataset - Name: edgemlDemo, ID: 64635a79a7a7513e8ac92d32, Metadata: {'langauge': 'python'}
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Dataset - Name: edgemlDemo, ID: 64635a7b6fec1d2800b1cd06, Metadata: {'langauge': 'python'}
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### 2. Actually obtain data
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Until now, we only have metadata available. We need to pull the actual time-series data using one of the following methods:
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*We can load the data for a single timeSeries*
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```python
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project.datasets[0].timeSeries[0].loadData()
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project.datasets[0].timeSeries[0].data.head()
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# get the API key from the settings of your project
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project = edgeml.getProject("https://app.edge-ml.org", PROJECT_API_KEY)
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```
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### Push Data from Python
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<div>
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<style scoped>
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.dataframe tbody tr th:only-of-type {
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vertical-align: middle;
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}
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.dataframe tbody tr th {
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vertical-align: top;
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}
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.dataframe thead th {
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text-align: right;
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}
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</style>
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<table class="dataframe">
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<thead>
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<tr style="text-align: right;">
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<th></th>
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<th>time</th>
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<th>x</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<th>0</th>
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<td>1970-01-01 00:10:23.339</td>
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<td>-823.0</td>
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</tr>
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<tr>
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<th>1</th>
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<td>1970-01-01 00:10:23.378</td>
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<td>-819.0</td>
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</tr>
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<tr>
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<th>2</th>
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<td>1970-01-01 00:10:23.418</td>
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<td>-770.0</td>
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</tr>
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<tr>
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<th>3</th>
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<td>1970-01-01 00:10:23.458</td>
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<td>-746.0</td>
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</tr>
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<tr>
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<th>4</th>
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<td>1970-01-01 00:10:23.497</td>
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<td>-783.0</td>
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</tr>
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</tbody>
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</table>
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</div>
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*For a single dataset*
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```python
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project.datasets[0].loadData()
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project.datasets[0].data.head()
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```
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<div>
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<style scoped>
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.dataframe tbody tr th:only-of-type {
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vertical-align: middle;
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}
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.dataframe tbody tr th {
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vertical-align: top;
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}
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.dataframe thead th {
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text-align: right;
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}
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</style>
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<table class="dataframe">
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<thead>
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<tr style="text-align: right;">
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<th></th>
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<th>time</th>
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<th>x</th>
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<th>y</th>
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<th>z</th>
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<th>Gestures</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<th>0</th>
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<td>1970-01-01 00:10:23.339</td>
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<td>-823.0</td>
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<td>-45.0</td>
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<td>4025.0</td>
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<td></td>
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</tr>
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<tr>
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<th>1</th>
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<td>1970-01-01 00:10:23.378</td>
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<td>-819.0</td>
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<td>-158.0</td>
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<td>4075.0</td>
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<td></td>
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</tr>
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<tr>
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<th>2</th>
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<td>1970-01-01 00:10:23.418</td>
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<td>-770.0</td>
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<td>-255.0</td>
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<td>4116.0</td>
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<td></td>
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</tr>
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<tr>
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<th>3</th>
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<td>1970-01-01 00:10:23.458</td>
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<td>-746.0</td>
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<td>-155.0</td>
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<td>4059.0</td>
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<td></td>
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</tr>
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<tr>
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<th>4</th>
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<td>1970-01-01 00:10:23.497</td>
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<td>-783.0</td>
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<td>-104.0</td>
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<td>3963.0</td>
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<td></td>
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</tr>
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</tbody>
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</table>
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</div>
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*Or for all datasets in the project*
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```python
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project.loadData()
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project.data[0].head()
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```
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<div>
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<style scoped>
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.dataframe tbody tr th:only-of-type {
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vertical-align: middle;
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}
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.dataframe tbody tr th {
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vertical-align: top;
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}
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.dataframe thead th {
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text-align: right;
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}
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</style>
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<table class="dataframe">
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<thead>
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<tr style="text-align: right;">
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<th></th>
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<th>time</th>
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<th>x</th>
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<th>y</th>
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<th>z</th>
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<th>Gestures</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<th>0</th>
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<td>1970-01-01 00:10:23.339</td>
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<td>-823.0</td>
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<td>-45.0</td>
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<td>4025.0</td>
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<td></td>
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</tr>
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<tr>
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<th>1</th>
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<td>1970-01-01 00:10:23.378</td>
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<td>-819.0</td>
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<td>-158.0</td>
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<td>4075.0</td>
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<td></td>
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</tr>
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<tr>
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<th>2</th>
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<td>1970-01-01 00:10:23.418</td>
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<td>-770.0</td>
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<td>-255.0</td>
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<td>4116.0</td>
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<td></td>
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</tr>
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<tr>
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<th>3</th>
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<td>1970-01-01 00:10:23.458</td>
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<td>-746.0</td>
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<td>-155.0</td>
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<td>4059.0</td>
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<td></td>
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</tr>
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<tr>
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<th>4</th>
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<td>1970-01-01 00:10:23.497</td>
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<td>-783.0</td>
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<td>-104.0</td>
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<td>3963.0</td>
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<td></td>
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</tr>
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</tbody>
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</table>
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</div>
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# Upload data to edge-ml
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### 1. Upload data using timestamps from the device
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Here you will need the *write*-key
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```python
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from edgeml.edgeml import DatasetCollector
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sender = DatasetCollector(url="https://edge-ml-beta.dmz.teco.edu", apiKey="4e6159c9c77124d71f298e93f1ed7254", name="edgemlDemo", useDeviceTime=True, timeSeries=["accX", "accY"], metaData={"langauge": "python"})
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```
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```python
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from edgeml import edgeml
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import time
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key = "YOUR_API_KEY"
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startTime = time.time()
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collector = edgeml.datasetCollector("https://app.edge-ml.org",
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key,
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"Example Dataset", # name the dataset you would like to upload
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False) # do not use server timestamps
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for i in range (100):
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await sender.addDataPoint(name="accX", value=i*0.1)
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await sender.addDataPoint(name="accY", value=i*0.5)
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time.sleep(0.01)
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sender.onComplete()
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```
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True
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for i in range(500):
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current_time = startTime + i * 10 # adding samples at 10 ms time steps
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collector.addDataPoint("Accelerometer X", random.randint(1,50) / 10.0, current_time)
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collector.addDataPoint("Accelerometer Y", random.randint(1,50) / 10.0, current_time)
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collector.addDataPoint("Accelerometer Z", random.randint(1,50) / 10.0, current_time)
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collector.onComplete()
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### 2. Provide your own timestamps
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```python
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from edgeml.edgeml import DatasetCollector
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sender = DatasetCollector(url="https://edge-ml-beta.dmz.teco.edu", apiKey="4e6159c9c77124d71f298e93f1ed7254", name="edgemlDemo", useDeviceTime=False, timeSeries=["accX", "accY"], metaData={"langauge": "python"})
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```
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## Development
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### Testing
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To run the tests please enter:
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```bash
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python -m unittest -v tests/all.py
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```python
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import time
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for i in range (100):
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await sender.addDataPoint(timestamp=i*1000, name="accX", value=i*0.1)
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await sender.addDataPoint(timestamp=i*1000, name="accY", value=i*0.5)
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time.sleep(0.01)
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sender.onComplete()
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```
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True
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