largefileuploadtask Python

[R-LIBIN]

Hello Team ,

I would like to get sample code largefileupload task to send mail and upload file in the onedrive/sharepoint placed in samples folder or updated in ms documentation.

Kindly request you to update the sample code in a separate tab for python with the documentation URL.

Ref#: https://docs.microsoft.com/en-us/graph/sdks/large-file-upload?tabs=csharp

Note : Please provide two separate code that demonstrate files sending greater than 4 mb and secondly, upload cide to 1Drive.

Kindly request you to help me as it is a new requirement for business purpose.

Thank you.

Regards , Libin

[tpcgold]

Hi @R-LIBIN accidentally stumbled upon this ticket. what you want is quite easy to do: here is an example where a "response.content" will be uploaded to SharePoint if the size is more than 4.1MB the file is streamed (uploaded in chunks) as it cannot be uploaded via single post request:

import os
import tempfile

from azure.identity import ClientSecretCredential
from msgraph.core import GraphClient

credential = ClientSecretCredential(
    tenant_id=tenant, client_id=client_id, client_secret=client_secret
)
client = GraphClient(credential=credential)
sharepoint_url = f"https://graph.microsoft.com/v1.0/drives/{driveid}/items/{itemid}:/{foldername}/{filename}"

if len(response.content) < 4100000:
    print("File is smaller than 4.1MB")
    data_upload = client.put(
        sharepoint_url + ":/content",
        data=response.content,
        headers={"Content-Type": "application/octet-stream"},
    )

    print(data_upload)
    print(data_upload.json())

else:
    print("File is bigger than 4.1MB")
    fd, path = tempfile.mkstemp()

    try:
        with os.fdopen(fd, "wb") as tmp:
            tmp.write(response.content)

            # Creating an upload session
            upload_session = client.post(
                sharepoint_url + ":/createUploadSession",
                headers={"Content-Type": "application/json"},
            ).json()

            with open(path, "rb") as f:
                total_file_size = os.path.getsize(path)
                chunk_size = 327680
                chunk_number = total_file_size // chunk_size
                chunk_leftover = total_file_size - chunk_size * chunk_number
                i = 0
                while True:
                    chunk_data = f.read(chunk_size)
                    start_index = i * chunk_size
                    end_index = start_index + chunk_size
                    # If end of file, break
                    if not chunk_data:
                        break
                    if i == chunk_number:
                        end_index = start_index + chunk_leftover
                    # Setting the header with the appropriate chunk data location in the file
                    headers = {
                        "Content-Type": "application/octet-stream",
                        "Content-Length": "{}".format(chunk_size),
                        "Content-Range": "bytes {}-{}/{}".format(
                            start_index, end_index - 1, total_file_size
                        ),
                    }
                    # Upload one chunk at a time
                    chunk_data_upload = client.put(
                        upload_session["uploadUrl"],
                        data=chunk_data,
                        headers=headers,
                    )
                    print(chunk_data_upload)
                    print(chunk_data_upload.json())
                    i = i + 1
    except Exception as error:
        print(error)

    finally:
        os.remove(path)

[R-LIBIN]

Thanks!. Stephen.

On Wed, 10 Jan, 2024, 1:29 pm Goldener Stefan, @.***> wrote:

Hi @R-LIBIN https://github.com/R-LIBIN accidentally stumbled upon this ticket. what you want is quite easy to do: here is an example where a "response.content" will be uploaded to sharepoint if the size is more than 4.1MB:

import os import tempfile

from azure.identity import ClientSecretCredential from msgraph.core import GraphClient

credential = ClientSecretCredential( tenant_id=tenant, client_id=client_id, client_secret=client_secret ) client = GraphClient(credential=credential) sharepoint_url = f"https://graph.microsoft.com/v1.0/drives/{driveid}/items/{itemid}:/{partner_id} - {partner_name}/{filename}"

if len(response.content) < 4100000: print("File is smaller than 4.1MB") data_upload = client.put( sharepoint_url + ":/content", data=response.content, headers={"Content-Type": "application/octet-stream"}, )

print(data_upload)
print(data_upload.json())

else: print("File is bigger than 4.1MB") fd, path = tempfile.mkstemp()

try:
    with os.fdopen(fd, "wb") as tmp:
        tmp.write(response.content)

        # Creating an upload session
        upload_session = client.post(
            sharepoint_url + ":/createUploadSession",
            headers={"Content-Type": "application/json"},
        ).json()

        with open(path, "rb") as f:
            total_file_size = os.path.getsize(path)
            chunk_size = 327680
            chunk_number = total_file_size // chunk_size
            chunk_leftover = total_file_size - chunk_size * chunk_number
            i = 0
            while True:
                chunk_data = f.read(chunk_size)
                start_index = i * chunk_size
                end_index = start_index + chunk_size
                # If end of file, break
                if not chunk_data:
                    break
                if i == chunk_number:
                    end_index = start_index + chunk_leftover
                # Setting the header with the appropriate chunk data location in the file
                headers = {
                    "Content-Type": "application/octet-stream",
                    "Content-Length": "{}".format(chunk_size),
                    "Content-Range": "bytes {}-{}/{}".format(
                        start_index, end_index - 1, total_file_size
                    ),
                }
                # Upload one chunk at a time
                chunk_data_upload = client.put(
                    upload_session["uploadUrl"],
                    data=chunk_data,
                    headers=headers,
                )
                print(chunk_data_upload)
                print(chunk_data_upload.json())
                i = i + 1
except Exception as error:
    print(error)

finally:
    os.remove(path)

— Reply to this email directly, view it on GitHub https://github.com/microsoftgraph/msgraph-sdk-python-core/issues/137#issuecomment-1884355965, or unsubscribe https://github.com/notifications/unsubscribe-auth/AEBCZFPJMNVJ24355FOTV53YNZC65AVCNFSM57RJBOFKU5DIOJSWCZC7NNSXTN2JONZXKZKDN5WW2ZLOOQ5TCOBYGQZTKNJZGY2Q . You are receiving this because you were mentioned.Message ID: @.***>

[R-LIBIN]

Please update in the documentation as well. I struggled when I wanted it. Hope it does help people. Mainly, Java, Python and C#.

On Wed, Jan 10, 2024 at 1:33 PM Libin Raveendran @.***> wrote:

Thanks!. Stephen.

On Wed, 10 Jan, 2024, 1:29 pm Goldener Stefan, @.***> wrote:

Hi @R-LIBIN https://github.com/R-LIBIN accidentally stumbled upon this ticket. what you want is quite easy to do: here is an example where a "response.content" will be uploaded to sharepoint if the size is more than 4.1MB:

import os import tempfile

from azure.identity import ClientSecretCredential from msgraph.core import GraphClient

credential = ClientSecretCredential( tenant_id=tenant, client_id=client_id, client_secret=client_secret ) client = GraphClient(credential=credential) sharepoint_url = f"https://graph.microsoft.com/v1.0/drives/{driveid}/items/{itemid}:/{partner_id} - {partner_name}/{filename}"

if len(response.content) < 4100000: print("File is smaller than 4.1MB") data_upload = client.put( sharepoint_url + ":/content", data=response.content, headers={"Content-Type": "application/octet-stream"}, )

print(data_upload)
print(data_upload.json())

else: print("File is bigger than 4.1MB") fd, path = tempfile.mkstemp()

try:
    with os.fdopen(fd, "wb") as tmp:
        tmp.write(response.content)

        # Creating an upload session
        upload_session = client.post(
            sharepoint_url + ":/createUploadSession",
            headers={"Content-Type": "application/json"},
        ).json()

        with open(path, "rb") as f:
            total_file_size = os.path.getsize(path)
            chunk_size = 327680
            chunk_number = total_file_size // chunk_size
            chunk_leftover = total_file_size - chunk_size * chunk_number
            i = 0
            while True:
                chunk_data = f.read(chunk_size)
                start_index = i * chunk_size
                end_index = start_index + chunk_size
                # If end of file, break
                if not chunk_data:
                    break
                if i == chunk_number:
                    end_index = start_index + chunk_leftover
                # Setting the header with the appropriate chunk data location in the file
                headers = {
                    "Content-Type": "application/octet-stream",
                    "Content-Length": "{}".format(chunk_size),
                    "Content-Range": "bytes {}-{}/{}".format(
                        start_index, end_index - 1, total_file_size
                    ),
                }
                # Upload one chunk at a time
                chunk_data_upload = client.put(
                    upload_session["uploadUrl"],
                    data=chunk_data,
                    headers=headers,
                )
                print(chunk_data_upload)
                print(chunk_data_upload.json())
                i = i + 1
except Exception as error:
    print(error)

finally:
    os.remove(path)

— Reply to this email directly, view it on GitHub https://github.com/microsoftgraph/msgraph-sdk-python-core/issues/137#issuecomment-1884355965, or unsubscribe https://github.com/notifications/unsubscribe-auth/AEBCZFPJMNVJ24355FOTV53YNZC65AVCNFSM57RJBOFKU5DIOJSWCZC7NNSXTN2JONZXKZKDN5WW2ZLOOQ5TCOBYGQZTKNJZGY2Q . You are receiving this because you were mentioned.Message ID: @.***>

[baywet]

thanks for reporting this issue, we have since released a new version of the SDK which this issue doesn't apply to. We encourage you to migrate to the new version and open a new issue if you still need help