Merge pull request #47 from scramjetorg/feat/new_samples

add fire sequence

python/seq-fire-alert/README.md

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+# Sequence sends forest images to the fire detecting machine learning API.
+___
+
+
+## Running
+
+> ❗ Remember to [setup transform-hub locally](https://docs.scramjet.org/platform/self-hosted-installation) or use the [platform's environment](https://docs.scramjet.org/platform/quick-start) for the sequence deployment.
+
+Open two terminals and run the following commands:
+
+
+```bash
+# go to 'seq-fire-alert' directory
+cd python/seq-fire-alert
+
+# build
+npm run build
+```
+
+If you run this sample on Self Hosted Hub, please start it with process adapter option:
+
+```bash
+DEVELOPMENT=1 sth --runtime-adapter=process
+```
+
+Once you've built it, you need to deploy it.
+
+```bash
+si seq deploy dist
+```
+
+
+Now you should be able to see on the parameters on topic "fire":
+
+```bash
+si topic get pi

python/seq-fire-alert/main.py

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+import asyncio
+from scramjet.streams import Stream
+import aiohttp
+import os
+
+
+API_BASE = 'https://forestapi.bieda.it'
+IMAGE_DIR = '/Users/spiderman/raspberry-pi-dash/seq-fire-alert/images'
+
+provides = {
+   'provides': 'fire',
+   'contentType': 'text/plain'
+}
+
+def get_bytes(path):
+    with open(path, 'rb') as f:
+        data = f.read()
+    return data
+
+async def post(data, url):
+    async with aiohttp.ClientSession() as session:
+        form_data = aiohttp.FormData()
+        form_data.add_field('file', data)
+        url = f'{API_BASE}/{url}'
+        async with session.post(url, data=form_data) as response:
+            return await response.json()
+
+async def main(stream):
+    for file in os.listdir(f'{IMAGE_DIR}'):
+        image = get_bytes(f'{IMAGE_DIR}/{file}')
+        response = await post(image, 'predict')
+        stream.write([response])
+        stream.write(['some actions...'])
+        await asyncio.sleep(3)
+
+async def run(context, input):
+    stream = Stream()
+    asyncio.gather(main(stream), return_exceptions=True)
+    return stream.map(lambda x : str(x) + "\n")
+
+
+

python/seq-fire-alert/package.json

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+{
+  "name": "@scramjet/fire-alert",
+  "version": "0.0.1",
+  "main": "main.py",
+  "author": "mcdominik",
+  "license": "GPL-3.0",
+  "description": "raspberry pi internal parameters fetcher example",
+  "keywords": [
+    "fire",
+    "python",
+    "machine learning",
+    "topics"
+  ],
+  "repository": {
+    "type": "git",
+    "url": "https://github.com/scramjetorg/platform-samples"
+  },
+  "engines": {
+    "python3": "3.8.0"
+  },
+  "scripts": {
+    "build": "mkdir -p dist/__pypackages__/ && pip3 install -t dist/__pypackages__/ -r requirements.txt && cp main.py package.json ./dist/",
+    "pack" : "si seq pack dist",
+    "clean": "rm -rf ./dist"
+  },
+  "dependencies": {
+    "@scramjet/api-client": "0.32.1"
+  }
+}

python/seq-fire-alert/requirements.txt

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+scramjet-framework-py==0.10
+pyee==9.0.4
+aiohttp==3.8.4