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Welcome to Scrapy-IPFS-Filecoin

Version

Scrapy is a popular open-source and collaborative python framework for extracting the data you need from websites. scrapy-ipfs-filecoin provides scrapy pipelines and feed exports to store items into IPFS and Filecoin using services like Web3.Storage, LightHouse.Storage, Estuary, Pinata, Moralis, Filebase or any S3 compatible services.

🏠 Homepage

Install

npm install -g https://github.com/pawanpaudel93/ipfs-only-hash.git
pip install scrapy-ipfs-filecoin

Example

scrapy-ipfs-filecoin-example

Usage

  1. Install ipfs-only-hash and scrapy-ipfs-filecoin.
npm install -g https://github.com/pawanpaudel93/ipfs-only-hash.git
pip install scrapy-ipfs-filecoin
  1. Add 'scrapy-ipfs-filecoin.pipelines.ImagesPipeline' and/or 'scrapy-ipfs-filecoin.pipelines.FilesPipeline' to ITEM_PIPELINES setting in your Scrapy project if you need to store images or other files to IPFS and Filecoin. For Images Pipeline, use:
ITEM_PIPELINES = {'scrapy_ipfs_filecoin.pipelines.ImagesPipeline': 1}

For Files Pipeline, use:

ITEM_PIPELINES = {'scrapy_ipfs_filecoin.pipelines.FilesPipeline': 1}

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.

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

ITEM_PIPELINES = {
 'scrapy_ipfs_filecoin.pipelines.ImagesPipeline': 1,
 'scrapy-ipfs-filecoin.pipelines.FilesPipeline': 1
}

If you are using the ImagesPipeline make sure to install the pillow package. The Images Pipeline requires Pillow 7.1.0 or greater. It is used for thumbnailing and normalizing images to JPEG/RGB format.

pip install pillow

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.

Add store path of files or images for Web3Storage, LightHouse, Moralis, Pinata or Estuary as required.

# for ImagesPipeline
IMAGES_STORE = 'w3s://images' # For Web3Storage
IMAGES_STORE = 'es://images' # For Estuary
IMAGES_STORE = 'lh://images' # For LightHouse
IMAGES_STORE = 'pn://images' # For Pinata
IMAGES_STORE = 'ms://images' # For Moralis
 # For Filebase or other s3 compatible services
 # Here bucket-name can be your bucket name created and folder-name can be a scraping specific folder to store your files
IMAGES_STORE = "s3://bucket-name/folder-name/images/"

# For FilesPipeline
FILES_STORE = 'w3s://files' # For Web3Storage
FILES_STORE = 'es://files' # For Estuary
FILES_STORE = 'lh://files' # For LightHouse
FILES_STORE = 'es://files' # For Pinata
FILES_STORE = 'pn://files' # For Moralis
 # For Filebase or other s3 compatible services
 # Here bucket-name can be your bucket name created and folder-name can be a scraping specific folder to store your files
FILES_STORE = "s3://bucket-name/folder-name/files/"

For more info regarding ImagesPipeline and FilesPipline. See here

  1. For Feed storage to store the output of scraping as json, csv, json, jsonlines, jsonl, jl, csv, xml, marshal, pickle etc set FEED_STORAGES as following for the desired output format:
from scrapy_ipfs_filecoin.feedexport import get_feed_storages
FEED_STORAGES = get_feed_storages()

Then set API Key for one of the storage i.e Web3Storage, LightHouse, Moralis, Pinata or Estuary. And, set FEEDS as following to finally store the scraped data.

For Web3Storage:

W3S_API_KEY = "<W3S_API_KEY>"

FEEDS = {
 'w3s://house.json': {
  "format": "json"
 },
}

For LightHouse:

LH_API_KEY = "<LH_API_KEY>"

FEEDS = {
 'lh://house.json': {
  "format": "json"
 },
}

For Estuary:

ES_API_KEY = "<ES_API_KEY>"

FEEDS = {
 'es://house.json': {
  "format": "json"
 },
}

For Pinata:

PN_JWT_TOKEN = "<PN_JWT_TOKEN>"

FEEDS = {
 'pn://house.json': {
  "format": "json"
 },
}

For Moralis:

MS_API_KEY = "<MS_API_KEY>"

FEEDS = {
 'ms://house.json': {
  "format": "json"
 },
}

For Filebase or other s3 compatible services

The S3 pipeline requires botocore so install it.

pip install botocore
 S3_ACCESS_KEY_ID = "<S3_ACCESS_KEY_ID>"
 S3_SECRET_ACCESS_KEY = "<S3_SECRET_ACCESS_KEY>"
 S3_ENDPOINT_URL = "https://s3.filebase.com"
 S3_IPFS_URL_FORMAT = "https://ipfs.filebase.io/ipfs/{cid}"

  # Here bucket-name can be your bucket name created and folder-name can be a scraping specific folder to store your files

 FEEDS = {
  "s3://bucket-name/folder-name/%(name)s_%(time)s.json": {"format": "json"},
  "s3://bucket-name/folder-name/%(name)s_%(time)s.csv": {"format": "csv"},
 }

See more on FEEDS here

  1. Now perform the scrapping as you would normally.

Author

👤 Pawan Paudel

🤝 Contributing

Contributions, issues and feature requests are welcome!
Feel free to check issues page.

Show your support

Give a ⭐️ if this project helped you!

Copyright © 2022 Pawan Paudel.