# Downloading and processing files and images

Scrapy provides reusable item pipelines for downloading fies attached to a particular item (for example, when you scrape products and also want to download their images locally). These pipelines share a bit of functionality and structure (we refer to them as media pipelines), but typically you’ll either use the Files Pipeline or the Images Pipeline.

Both pipelines implement these features:

- Avoid re-downloading media that was downloaded recently
- Specifying where to store the media (filesystem directory, Amazon S3 bucket)

The Images Pipeline has a few extra functions for processing images:

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

The pipelines also keep an internal queue of those media URLs which are currently being scheduled for download, and connect those responses that arrive containing the same media to that queue. This avoids downloading the same media more than once when it’s shared by several items.

## Using the Files Pipeline

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

1. In a Spider, you scrape an item and put the URLs of the desired into a `file_urls` field.
2. The item is returned from the spider and goes to the item pipeline.
3. When the item reaches the `FilesPipeline`, the URLs in the `file_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 files have finish downloading (or fail for some reason).
4. When the files are downloaded, another field (`files`) will be populated with the results. This field will contain a list of dicts with information about the downloaded files, such as the downloaded path, the original scraped url (taken from the `file_urls` field) , and the file checksum. The files in the list of the `files` field will retain the same order of the original `file_urls` field. If some file failed downloading, an error will be logged and the file won’t be present in the `files` field.

## Using the Images Pipeline

Using the `ImagesPipeline` is a lot like using the `FilesPipeline`, except the default field names used are different: you use `image_urls` for the image URLs of an item and it will populate an `images` field for the information about the downloaded images.

The advantage of using the `ImagesPipeline` for image files is that you can configure some extra functions like generating thumbnails and filtering the images based on their size.

The Images Pipeline uses Pillow for thumbnailing and normalizing images to JPEG/RGB format, so you need to install this library in order to use it. Python Imaging Library (PIL) should also work in most cases, but it is known to cause troubles in some setups, so we recommend to use Pillow instead of PIL.

## Usage example

In order to use a media pipeline first, enable it.

Then, if a spider returns a dict with the URLs key (‘file_urls’ or ‘image_urls’, for the Files or Images Pipeline respectively), the pipeline will put the results under respective key (‘files’ or images’).

If you prefer to use `Item`, then define a custom item with the necessary fields, like in this example for Images Pipeline:

    import scrapy

    class MyItem(scrapy.Item):

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

If you need something more complex and want to override the custom pipeline behaviour, see Extending the Media Pipelines.

## Enabling your Media Pipeline

To enable your media pipeline you must first add it to your project `ITEM_PIPELINES` setting.

For Images Pipeline, use:

    ITEM_PIPELINES = {'scrapy.pipelines.images.ImagesPipeline': 1}

For Files Pipeline, use:

    ITEM_PIPELINES = {'scrapy.pipelines.files.FilesPipeline': 1}

Note

You can also use both the Files and Images Pipeline at the same time.

Then, configure the target storage setting to a valid value 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 the Files Pipeline, set the `FILES_STORE` setting:

    FILES_STORE = '/path/to/valid/dir'

For the Images Pipeline, set the `IMAGES_STORE` setting:

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

## Supported Storage

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

### File system storage

The files are stored 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 for the Images Pipeline.
- `full` is a sub-directory to separate full images from thumbnails (if used). For more info see Thumbnail generation for images.

## Additional features

### File expiration

The Image Pipeline avoids downloading files that were downloaded recently. To adjust this retention delay use the `FILES_EXPIRES` setting (or `IMAGES_EXPIRES`, in case of Images Pipeline), which specifies the delay in number of days:

    # 90 days of delay for files expiration
    FILES_EXPIRES = 90

    # 30 days of delay for images expiration
    IMAGES_EXPIRES = 30

### Thumbnail generation for images

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

When using the Images Pipeline, 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.

## Extending the Media Pipelines

See here the methods that you can override in your custom Files Pipeline:

class `scrapy.pipelines.files.``FilesPipeline`
  `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 can override the `get_media_requests()` method and return a Request for each file URL:

        def get_media_requests(self, item, info):
            for file_url in item['file_urls']:
                yield scrapy.Request(file_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, file_info_or_error)` where:

    - `success` is a boolean which is `True` if the image was downloaded successfully or `False` if it failed for some reason
    - `file_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 file was downloaded from. This is the url of the request returned from the `get_media_requests()` method.
      - `path` - the path (relative to `FILES_STORE`) where the file 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/0a79c461a4062ac383dc4fade7bc09f1384a3910.jpg',
           'url': 'http://www.example.com/files/product1.pdf'}),
         (False,
          Failure(...))]

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

  `item_completed`(results, items, info)

    The `FilesPipeline.item_completed()` method called when all file requests for a single item have completed (either finished 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 file paths (passed in results) in the `file_paths` item field, and we drop the item if it doesn’t contain any files:

        from scrapy.exceptions import DropItem

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

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

See here the methods that you can override in your custom Images Pipeline:

class `scrapy.pipelines.images.``ImagesPipeline`

  > The `ImagesPipeline` is an extension of the `FilesPipeline`, customizing the field names and adding custom behavior for images.

  `get_media_requests`(item, info)

    Works the same way as `FilesPipeline.get_media_requests()` method, but using a different field name for image urls.

    Must return a Request for each image URL.

  `item_completed`(results, items, info)

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

    Works the same way as `FilesPipeline.item_completed()` method, but using a different field names for storing image downloading results.

    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:

    import scrapy
    from scrapy.pipelines.images import ImagesPipeline
    from scrapy.exceptions import DropItem

    class MyImagesPipeline(ImagesPipeline):

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