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# Downloading Item Images

Scrapy provides an item pipeline for downloading images attached to a particular item, for example, when you scrape products and also want to download their images locally.

This pipeline, called the Images Pipeline and implemented in the `ImagesPipeline` class, provides a convenient way for downloading and storing images locally with some additional features:

- Convert all downloaded images to a common format (JPG) and mode (RGB)
- Avoid re-downloading images which were downloaded recently
- Thumbnail generation
- Check images width/height to make sure they meet a minimum constraint

This pipeline also keeps an internal queue of those images which are currently being scheduled for download, and connects those items that arrive containing the same image, to that queue. This avoids downloading the same image more than once when it’s shared by several items.

The Python Imaging Library is used for thumbnailing and normalizing images to JPEG/RGB format, so you need to install that library in order to use the images pipeline.

## Using the Images Pipeline

The typical workflow, when using the `ImagesPipeline` goes like this:

1. In a Spider, you scrape an item and put the URLs of its images into a `image_urls` field.
2. The item is returned from the spider and goes to the item pipeline.
3. When the item reaches the `ImagesPipeline`, the URLs in the `image_urls` field are scheduled for download using the standard Scrapy scheduler and downloader (which means the scheduler and downloader middlewares are reused), but with a higher priority, processing them before other pages are scraped. The item remains “locked” at that particular pipeline stage until the images have finish downloading (or fail for some reason).
4. When the images are downloaded another field (`images`) will be populated with the results. This field will contain a list of dicts with information about the images downloaded, such as the downloaded path, the original scraped url (taken from the `image_urls` field) , and the image checksum. The images in the list of the `images` field will retain the same order of the original `image_urls` field. If some image failed downloading, an error will be logged and the image won’t be present in the `images` field.

## Usage example

In order to use the image pipeline you just need to enable it and define an item with the `image_urls` and `images` fields:

    from scrapy.item import Item

    class MyItem(Item):

        # ... other item fields ...
        image_urls = Field()
        images = Field()

If you need something more complex and want to override the custom images pipeline behaviour, see Implementing your custom Images Pipeline.

## Enabling your Images Pipeline

To enable your images pipeline you must first add it to your project `ITEM_PIPELINES` setting:

    ITEM_PIPELINES = ['scrapy.contrib.pipeline.images.ImagesPipeline']

And set the `IMAGES_STORE` setting to a valid directory that will be used for storing the downloaded images. Otherwise the pipeline will remain disabled, even if you include it in the `ITEM_PIPELINES` setting.

For example:

    IMAGES_STORE = '/path/to/valid/dir'

## Images Storage

File system is currently the only officially supported storage, but there is also (undocumented) support for Amazon S3.

### File system storage

The images are stored in files (one per image), using a SHA1 hash of their URLs for the file names.

For example, the following image URL:

    http://www.example.com/image.jpg

Whose SHA1 hash is:

    3afec3b4765f8f0a07b78f98c07b83f013567a0a

Will be downloaded and stored in the following file:

    <IMAGES_STORE>/full/3afec3b4765f8f0a07b78f98c07b83f013567a0a.jpg

Where:

- `<IMAGES_STORE>` is the directory defined in `IMAGES_STORE` setting
- `full` is a sub-directory to separate full images from thumbnails (if used). For more info see Thumbnail generation.

## Additional features

### Image expiration

The Image Pipeline avoids downloading images that were downloaded recently. To adjust this retention delay use the `IMAGES_EXPIRES` setting, which specifies the delay in number of days:

    # 90 days of delay for image expiration
    IMAGES_EXPIRES = 90

### Thumbnail generation

The Images Pipeline can automatically create thumbnails of the downloaded images.

In order use this feature, you must set `IMAGES_THUMBS` to a dictionary where the keys are the thumbnail names and the values are their dimensions.

For example:

    IMAGES_THUMBS = {
        'small': (50, 50),
        'big': (270, 270),
    }

When you use this feature, the Images Pipeline will create thumbnails of the each specified size with this format:

    <IMAGES_STORE>/thumbs/<size_name>/<image_id>.jpg

Where:

- `<size_name>` is the one specified in the `IMAGES_THUMBS` dictionary keys (`small`, `big`, etc)
- `<image_id>` is the SHA1 hash of the image url

Example of image files stored using `small` and `big` thumbnail names:

    <IMAGES_STORE>/full/63bbfea82b8880ed33cdb762aa11fab722a90a24.jpg
    <IMAGES_STORE>/thumbs/small/63bbfea82b8880ed33cdb762aa11fab722a90a24.jpg
    <IMAGES_STORE>/thumbs/big/63bbfea82b8880ed33cdb762aa11fab722a90a24.jpg

The first one is the full image, as downloaded from the site.

### Filtering out small images

You can drop images which are too small, by specifying the minimum allowed size in the `IMAGES_MIN_HEIGHT` and `IMAGES_MIN_WIDTH` settings.

For example:

    IMAGES_MIN_HEIGHT = 110
    IMAGES_MIN_WIDTH = 110

Note: these size constraints don’t affect thumbnail generation at all.

By default, there are no size constraints, so all images are processed.

## Implementing your custom Images Pipeline

Here are the methods that you should override in your custom Images Pipeline:

class `scrapy.contrib.pipeline.images.``ImagesPipeline`
  `get_media_requests`(item, info)

    As seen on the workflow, the pipeline will get the URLs of the images to download from the item. In order to do this, you must override the `get_media_requests()` method and return a Request for each image URL:

        def get_media_requests(self, item, info):
            for image_url in item['image_urls']:
                yield Request(image_url)

    Those requests will be processed by the pipeline and, when they have finished downloading, the results will be sent to the `item_completed()` method, as a list of 2-element tuples. Each tuple will contain `(success, image_info_or_failure)` where:

    - `success` is a boolean which is `True` if the image was downloaded successfully or `False` if it failed for some reason
    - `image_info_or_error` is a dict containing the following keys (if success is `True`) or a Twisted Failure if there was a problem.
      - `url` - the url where the image was downloaded from. This is the url of the request returned from the `get_media_requests()` method.
      - `path` - the path (relative to `IMAGES_STORE`) where the image was stored
      - `checksum` - a MD5 hash of the image contents

    The list of tuples received by `item_completed()` is guaranteed to retain the same order of the requests returned from the `get_media_requests()` method.

    Here’s a typical value of the `results` argument:

        [(True,
          {'checksum': '2b00042f7481c7b056c4b410d28f33cf',
           'path': 'full/7d97e98f8af710c7e7fe703abc8f639e0ee507c4.jpg',
           'url': 'http://www.example.com/images/product1.jpg'}),
         (True,
          {'checksum': 'b9628c4ab9b595f72f280b90c4fd093d',
           'path': 'full/1ca5879492b8fd606df1964ea3c1e2f4520f076f.jpg',
           'url': 'http://www.example.com/images/product2.jpg'}),
         (False,
          Failure(...))]

    By default the `get_media_requests()` method returns `None` which means there are no images to download for the item.

  `item_completed`(results, items, info)

    The `ImagesPipeline.item_completed()` method called when all image requests for a single item have completed (either finshed downloading, or failed for some reason).

    The `item_completed()` method must return the output that will be sent to subsequent item pipeline stages, so you must return (or drop) the item, as you would in any pipeline.

    Here is an example of the `item_completed()` method where we store the downloaded image paths (passed in results) in the `image_paths` item field, and we drop the item if it doesn’t contain any images:

        from scrapy.exceptions import DropItem

        def item_completed(self, results, item, info):
            image_paths = [x['path'] for ok, x in results if ok]
            if not image_paths:
                raise DropItem("Item contains no images")
            item['image_paths'] = image_paths
            return item

    By default, the `item_completed()` method returns the item.

## Custom Images pipeline example

Here is a full example of the Images Pipeline whose methods are examplified above:

    from scrapy.contrib.pipeline.images import ImagesPipeline
    from scrapy.exceptions import DropItem
    from scrapy.http import Request

    class MyImagesPipeline(ImagesPipeline):

        def get_media_requests(self, item, info):
            for image_url in item['image_urls']:
                yield Request(image_url)

        def item_completed(self, results, item, info):
            image_paths = [x['path'] for ok, x in results if ok]
            if not image_paths:
                raise DropItem("Item contains no images")
            item['image_paths'] = image_paths
            return item

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