Dropbox rest api, in function metatada has a parameter named "hash" https://www.dropbox.com/developers/reference/api#metadata
Can I calculate this hash locally without call any remote api rest function?
I need know this value to reduce upload bandwidth.
https://www.dropbox.com/developers/reference/content-hash explains how Dropbox computes their file hashes. A Python implementation of this is below:
import hashlib
import math
import os
DROPBOX_HASH_CHUNK_SIZE = 4*1024*1024
def compute_dropbox_hash(filename):
file_size = os.stat(filename).st_size
with open(filename, 'rb') as f:
block_hashes = b''
while True:
chunk = f.read(DROPBOX_HASH_CHUNK_SIZE)
if not chunk:
break
block_hashes += hashlib.sha256(chunk).digest()
return hashlib.sha256(block_hashes).hexdigest()
The "hash" parameter on the metadata call isn't actually the hash of the file, but a hash of the metadata. It's purpose is to save you having to re-download the metadata in your request if it hasn't changed by supplying it during the metadata request. It is not intended to be used as a file hash.
Unfortunately I don't see any way via the Dropbox API to get a hash of the file itself. I think your best bet for reducing your upload bandwidth would be to keep track of the hash's of your files locally and detect if they have changed when determining whether to upload them. Depending on your system you also likely want to keep track of the "rev" (revision) value returned on the metadata request so you can tell whether the version on Dropbox itself has changed.
This won't directly answer your question, but is meant more as a workaround; The dropbox sdk gives a simple updown.py example that uses file size and modification time to check the currency of a file.
an abbreviated example taken from updown.py:
dbx = dropbox.Dropbox(api_token)
...
# returns a dictionary of name: FileMetaData
listing = list_folder(dbx, folder, subfolder)
# name is the name of the file
md = listing[name]
# fullname is the path of the local file
mtime = os.path.getmtime(fullname)
mtime_dt = datetime.datetime(*time.gmtime(mtime)[:6])
size = os.path.getsize(fullname)
if (isinstance(md, dropbox.files.FileMetadata) and mtime_dt == md.client_modified and size == md.size):
print(name, 'is already synced [stats match]')
As far as I am concerned, No you can't.
The only way is using Dropbox API which is explained here.
The rclone go program from https://rclone.org has exactly what you want:
rclone hashsum dropbox localfile
rclone hashsum dropbox localdir
It can't take more than one path argument but I suspect that's something you can work with...
t0|todd#tlaptop/p8 ~/tmp|295$ echo "Hello, World!" > dropbox-hash-demo/hello.txt
t0|todd#tlaptop/p8 ~/tmp|296$ rclone copy dropbox-hash-demo/hello.txt dropbox-ttf:demo
t0|todd#tlaptop/p8 ~/tmp|297$ rclone hashsum dropbox dropbox-hash-demo
aa4aeabf82d0f32ed81807b2ddbb48e6d3bf58c7598a835651895e5ecb282e77 hello.txt
t0|todd#tlaptop/p8 ~/tmp|298$ rclone hashsum dropbox dropbox-ttf:demo
aa4aeabf82d0f32ed81807b2ddbb48e6d3bf58c7598a835651895e5ecb282e77 hello.txt
Related
I've been experimenting with Scrapy for sometime now and recently have been trying to upload files (data and images) to an S3 bucket. If the directory is static, it is pretty straightforward and I didn't hit any roadblocks. But what I want to achieve is to dynamically create directories based on a certain field from the extract data and place the data & media in those directories. The template path, if you will, is below:
s3://<bucket-name>/crawl_data/<account_id>/<media_type>/<file_name>
For example if the account_id is 123, then the images should be placed in the following directory:
s3://<bucket-name>/crawl_data/123/images/file_name.jpeg
and the data file should be placed in the following directory:
s3://<bucket-name>/crawl_data/123/data/file_name.json
I have been able to achieve this for the media downloads (kind of a crude way to segregate media types, as of now), with the following custom File Pipeline:
class CustomFilepathPipeline(FilesPipeline):
def file_path(self, request, response=None, info=None, *, item=None):
adapter = ItemAdapter(item)
account_id = adapter["account_id"]
file_name = os.path.basename(urlparse(request.url).path)
if ".mp4" in file_name:
media_type = "video"
else:
media_type = "image"
file_path = f"crawl_data/{account_id}/{media_type}/{file_name}"
return file_path
The following settings have been configured at a spider level with custom_settings:
custom_settings = {
'FILES_STORE': 's3://<my_s3_bucket_name>/',
'FILES_RESULT_FIELD': 's3_media_url',
'DOWNLOAD_WARNSIZE': 0,
'AWS_ACCESS_KEY_ID': <my_access_key>,
'AWS_SECRET_ACCESS_KEY': <my_secret_key>,
}
So, the media part works flawlessly and I have been able to download the images and videos in their separate directories based on the account_id, in the S3 bucket. My questions is:
Is there a way to achieve the same results with the data files as well? Maybe another custom pipeline?
I have tried to experiment with the 1st example on the Item Exporters page but couldn't make any headway. One thing that I thought might help is to use boto3 to establish connection and then upload files but that might possibly require me to segregate files locally and upload those files together, by using a combination of Pipelines (to split data) and Signals (once spider is closed to upload the files to S3).
Any thoughts and/or guidance on this or a better approach would be greatly appreciated.
For example:
session = boto3.Session()
client = session.client('custom-service')
I know that I can create a json with API definitions under ~/.aws/models and botocore will load it from there. The problem is that I need to get it done on the AWS Lambda function, which looks like impossible to do so.
Looking for a way to tell boto3 where are the custom json api definitions so it could load from the defined path.
Thanks
I have only a partial answer. There's a bit of documentation about botocore's loader module, which is what reads the model files. In a disscusion about loading models from ZIP archives, a monkey patch was offered up which extracts the ZIP to a temporary filesystem location and then extends the loader search path to that location. It doesn't seem like you can load model data directly from memory based on the API, but Lambda does give you some scratch space in /tmp.
Here's the important bits:
import boto3
session = boto3.Session()
session._loader.search_paths.extend(["/tmp/boto"])
client = session.client("custom-service")
The directory structure of /tmp/boto needs to follow the resource loader documentation. The main model file needs to be at /tmp/boto/custom-service/yyyy-mm-dd/service-2.json.
The issue also mentions that alternative loaders can be swapped in using Session.register_component so if you wanted to write a scrappy loader which returned a model straight from memory you could try that too. I don't have any info about how to go about doing that.
Just adding more details:
import boto3
import zipfile
import os
s3_client = boto3.client('s3')
s3_client.download_file('your-bucket','model.zip','/tmp/model.zip')
os.chdir('/tmp')
with zipfile.ZipFile('model.zip', 'r') as archive:
archive.extractall()
session = boto3.Session()
session._loader.search_paths.extend(["/tmp/boto"])
client = session.client("custom-service")
model.zip is just a compressed file that contains:
Archive: model.zip
Length Date Time Name
--------- ---------- ----- ----
0 11-04-2020 16:44 boto/
0 11-04-2020 16:44 boto/custom-service/
0 11-04-2020 16:44 boto/custom-service/2018-04-23/
21440 11-04-2020 16:44 boto/custom-service/2018-04-23/service-2.json
Just remember to have the proper lambda role to access S3 and your custom-service.
boto3 also allows setting the AWS_DATA_PATH environment variable which can point to a directory path of your choice.
[boto3 Docs]
Everything zipped with your lambda function is put under /opt/.
Let's assume all your custom models live under a models/ folder. When this folder is mounted to the lambda environment, it'll live under /opt/models/.
Simply specify AWS_DATA_PATH=/opt/models/ in the Lambda configuration and boto3 will pick up models in that directory.
This is better than fetching models from S3 during runtime, unpacking, and then modifying session parameters.
I have a list of .zip files on S3 which is dynamically created and passed to flask view /download. My problem doesn't seem to be in looping through this list, but rather in returning a response so that all files from the list are downloaded to users computer. If I have a view return a response it only downloads the first file, as return closes the connection.
I have tried a number of things and looked at similar issues (like this one: Boto3 to download all files from a S3 Bucket ), but so far had no luck in resolving this. I have also looked at streaming (as in here: http://flask.pocoo.org/docs/1.0/patterns/streaming/ ) and tried creating a subfunction which is a generator, but the same issue persists as I still have to pass a return value to View function - here is that last code example:
#app.route('/download', methods=['POST'])
def download():
download=[]
download = request.form.getlist('checked')
def generate(result):
s3_resource = boto3.resource('s3')
my_bucket = s3_resource.Bucket(S3_BUCKET)
d_object = my_bucket.Object(result).get()
yield d_object['Body'].read()
for filename in download:
return Response (generate(filename), mimetype='application/zip', headers={'Content-Disposition': 'attachment;filename=' + filename})
What would be the best way of doing this so that all the files are downloaded?
Is there an easier way to pass a list to boto3 or any other flask module to download those files?
I am new to S3 and need to use it for image storage. I found a half dozen versions of an s2wrapper for cf but it appears that the only one set of for v4 is one modified by Leigh
https://gist.github.com/Leigh-/26993ed79c956c9309a9dfe40f1fce29
Dropped in the com directory and created a "test" page that contains the following code:
s3 = createObject('component','com.S3Wrapper').init(application.s3.AccessKeyId,application.s3.SecretAccessKey);
but got the following error :
So I changed the line 37 from
variables.Sv4Util = createObject('component', 'Sv4').init(arguments.S3AccessKey, arguments.S3SecretAccessKey);
to
variables.Sv4Util = createObject('component', 'Sv4Util').init(arguments.S3AccessKey, arguments.S3SecretAccessKey);
Now I am getting:
I feel like going through Leigh code and start changing things is a bad idea since I have lurked here for year an know Leigh's code is solid.
Does any know if there are any examples on how to use this anywhere? If not what I am doing wrong. If it makes a difference I am using Lucee 5 and not Adobe's CF engine.
UPDATE :
I followed Leigh's directions and the error is now gone. I am addedsome more code to my test page which now looks like this :
<cfscript>
s3 = createObject('component','com.S3v4').init(application.s3.AccessKeyId,application.s3.SecretAccessKey);
bucket = "imgbkt.domain.com";
obj = "fake.ping";
region = "s3-us-west-1"
test = s3.getObject(bucket,obj,region);
writeDump(test);
test2 = s3.getObjectLink(bucket,obj,region);
writeDump(test2);
writeDump(s3);
</cfscript>
Regardless of what I put in for bucket, obj or region I get :
JIC I did go to AWS and get new keys:
Leigh if you are still around or anyone how has used one of the s3Wrappers any suggestions or guidance?
UPDATE #2:
Even after Alex's help I am not able to get this to work. The Link I receive from getObjectLink is not valid and getObject never does download an object. I thought I would try the putObject method
test3 = s3.putObject(bucketName=bucket,regionName=region,keyName="favicon.ico");
writeDump(test3);
to see if there is any additional information, I received this :
I did find this article https://shlomoswidler.com/2009/08/amazon-s3-gotcha-using-virtual-host.html but it is pretty old and since S3 specifically suggests using dots in bucketnames I don't that it is relevant any longer. There is obviously something I am doing wrong but I have spent hours trying to resolve this and I can't seem to figure out what it might be.
I will give you a rundown of what the code does:
getObjectLink returns a HTTP URL for the file fake.ping that is found looking in the bucket imgbkt.domain.com of region s3-us-west-1. This link is temporary and expires after 60 seconds by default.
getObject invokes getObjectLink and immediately requests the URL using HTTP GET. The response is then saved to the directory of the S3v4.cfc with the filename fake.ping by default. Finally the function returns the full path of the downloaded file: E:\wwwDevRoot\taa\fake.ping
To save the file in a different location, you would invoke:
downloadPath = 'E:\';
test = s3.getObject(bucket,obj,region,downloadPath);
writeDump(test);
The HTTP request is synchronous, meaning the file will be downloaded completely when the functions returns the filepath.
If you want to access the actual content of the file, you can do this:
test = s3.getObject(bucket,obj,region);
contentAsString = fileRead(test); // returns the file content as string
// or
contentAsBinary = fileReadBinary(test); // returns the content as binary (byte array)
writeDump(contentAsString);
writeDump(contentAsBinary);
(You might want to stream the content if the file is large since fileRead/fileReadBinary reads the whole file into buffer. Use fileOpen to stream the content.
Does that help you?
Say for example I have the following bucket set up:
bucketone
…/folderone
…/text1.txt
…/text2.txt
…/foldertwo
…/file1.json
…/folderthree
…/folderthreesub
…/file2.json
…/file3.json
But it only goes down one level.
What’s the proper way of retrieving information under a bucket?
Will be sure to accept/upvote answer.
Whats wrong with just doing this from the CLI?
aws s3 cp s3://bucketing . --recursive
Contrary to the way you'd think it will work, rsplit() actually returns the splits from left-right, even though it applies it right-to-left.
Therefore, you actually want to obtain the last element of the split:
filename = obj['Key'].rsplit('/', 1)[-1]
See: Python rsplit() documentation
Also, be careful of 'pretend directories' that might be created via the console. They are actually zero-length files the make the folder appear in the UI. Therefore, skip files with no name after the final slash.
Make those fixes and it works as desired:
import boto3
import os
s3client = boto3.client('s3')
for obj in s3client.list_objects_v2(Bucket='my-bucket')['Contents']:
filename = obj['Key'].rsplit('/', 1)[-1]
localfiledir = os.path.join('/tmp', filename)
if filename != '':
s3client.download_file('my-bucket', obj['Key'], localfiledir)