add readme and publish workflow

.github/workflows/publish.yml

@@ -0,0 +1,19 @@
+name: Publish Python 🐍 distributions 📦 to PyPI
+
+on:
+  release:
+
+jobs:
+  pypi-publish:
+    name: Upload release to PyPI
+    runs-on: ubuntu-latest
+    # environment:
+    #   name: github
+    #   url: https://pypi.org/p/scrapework
+    permissions:
+      id-token: write # IMPORTANT: this permission is mandatory for trusted publishing
+    steps:
+      # retrieve your distributions here
+
+      - name: Publish package distributions to PyPI
+        uses: pypa/gh-action-pypi-publish@release/v1

README.md

@@ -1,3 +1,100 @@
 # Scrapework
 
-A simple scraping framework based on scrapy for simple tasks and management. Using convention over configuration, it allows you to focus on the scraping logic and not on the boilerplate code.
+Scrapework is a simple scraping framework inspired by Scrapy. It's designed for simple tasks and management, allowing you to focus on the scraping logic and not on the boilerplate code.
+
+- No CLI
+- No twisted / async
+- Respectful and slow for websites
+
+## Getting Started
+
+### Installation
+
+First, clone the repository and install the dependencies:
+
+```sh
+git clone https://github.com/yourusername/scrapework.git
+cd scrapework
+poetry install
+```
+
+### Creating a Spider
+
+A Spider is a class that defines how to navigate a website and extract data. Here's how you can create a Spider:
+
+```python
+from scrapework.spider import Spider
+
+class MySpider(Spider):
+    start_urls = ['http://quotes.toscrape.com']
+
+    def parse(self, response):
+        for quote in response.css('div.quote'):
+            yield {
+                'text': quote.css('span.text::text').get(),
+                'author': quote.css('span small::text').get(),
+            }
+```
+
+The `parse` method is where you define your scraping logic. It's called with the HTTP response of the initial URL.
+
+### Creating an Extractor
+
+An Extractor is a class that defines how to extract data from a webpage. Here's how you can create an Extractor:
+
+```python
+from scrapework.extractors import Extractor
+
+class MyExtractor(Extractor):
+    def extract(self, selector):
+        return {
+            'text': selector.css('span.text::text').get(),
+            'author': selector.css('span small::text').get(),
+        }
+```
+
+The `extract` method is where you define your extraction logic. It's called with a `parsel.Selector` object that you can use to extract data from the HTML.
+
+### Creating a Pipeline
+
+A Pipeline is a class that defines how to process and store the data. Here's how you can create a Pipeline:
+
+```python
+from scrapework.pipelines import ItemPipeline
+
+class MyPipeline(ItemPipeline):
+    def process_items(self, items, config):
+        for item in items:
+            print(f"Quote: {item['text']}, Author: {item['author']}")
+```
+
+The `process_items` method is where you define your processing logic. It's called with the items extracted by the Extractor and a `PipelineConfig` object.
+
+### Running the Spider
+
+To run the Spider, you need to create an instance of it and call the `start_requests` method:
+
+```python
+spider = MySpider()
+spider.start_requests()
+```
+
+## Advanced Usage
+
+For more advanced usage, you can override other methods in the Spider, Extractor, and Pipeline classes. Check the source code for more details.
+
+## Testing
+
+To run the tests, use the following command:
+
+```sh
+pytest tests/
+```
+
+## Contributing
+
+Contributions are welcome! Please read the contributing guidelines first.
+
+## License
+
+Scrapework is licensed under the MIT License.