smart_open | Utils for streaming large files

by RaRe-Technologies Python Version: v6.3.0 License: MIT

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | smart_open Summary

smart_open is a Python library typically used in Big Data, Amazon S3, Hadoop applications. smart_open has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can download it from GitHub.

Utils for streaming large files (S3, HDFS, gzip, bz2...)

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Quality

Security

License

Reuse

Support

smart_open has a medium active ecosystem.

It has 2880 star(s) with 356 fork(s). There are 48 watchers for this library.

It had no major release in the last 12 months.

There are 66 open issues and 307 have been closed. On average issues are closed in 293 days. There are 19 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of smart_open is v6.3.0

Quality

smart_open has 0 bugs and 0 code smells.

Security

smart_open has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

smart_open code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

smart_open is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

smart_open releases are available to install and integrate.

Build file is available. You can build the component from source.

smart_open saves you 3209 person hours of effort in developing the same functionality from scratch.

It has 7630 lines of code, 904 functions and 61 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed smart_open and discovered the below as its top functions. This is intended to give you an instant insight into smart_open implemented functionality, and help decide if they suit your requirements.

Seek to the current position
Wrapper around get_object
Unwrap an IOError
Opens the content range
Move to the specified offset
Clamp a value
Make a partial request
Empty the buffer
Read a line from the stream
Upload bytes to the stream
Get an iterator over an S3 bucket
Extract preamble and body from a file
Read data into b
Reads the contents of a file
Close the upload
Copy text to the clipboard
Get the version string
Download a key from S3
Read data into b
Returns a raw byte buffer
Read up to size bytes from the stream
Register a callback for a file extension
Print out the docstring of the open function
Register a transport
Open a file using smart_open
Open a given URI

Get all kandi verified functions for this library.

smart_open Key Features

No Key Features are available at this moment for smart_open.

smart_open Examples and Code Snippets

No Code Snippets are available at this moment for smart_open.

Community Discussions

Trending Discussions on smart_open

Python: Stream gzip files from s3

No such file or directory: 'GoogleNews-vectors-negative300.bin'

How do I read an image using Rawpy image processing library, from a URL?

Issue in Lambda execution time

Package built by Poetry is missing runtime dependencies

h5py performs many small reads when accessing data over a file-like object

Loading a FastText Model from s3 without Saving Locally

How to add an additional python package to the Pipfile of a docker-compose project (DJANGO)?

Updating the json file edited in Python

How to load a trained model in django

QUESTION

Python: Stream gzip files from s3

Asked 2022-Mar-31 at 14:14

I have files in s3 as gzip chunks, thus I have to read the data continuously and cant read random ones. I always have to start with the first file.

For example lets say I have 3 gzip file in s3, f1.gz, f2.gz, f3.gz. If I download all locally, I can do cat * | gzip -d. If I do cat f2.gz | gzip -d, it will fail with gzip: stdin: not in gzip format.

How can I stream these data from s3 using python? I saw smart-open and it has the ability to decompress gz files with

...

ANSWER

Answered 2022-Mar-31 at 14:14

For example lets say I have 3 gzip file in s3, f1.gz, f2.gz, f3.gz. If I download all locally, I can do cat * | gzip -d.

One idea would be to make a file object to implement this. The file object reads from one filehandle, exhausts it, reads from the next one, exhausts it, etc. This is similar to how cat works internally.

The handy thing about this is that it does the same thing as concatenating all of your files, without the memory use of reading in all of your files at the same time.

Once you have the combined file object wrapper, you can pass it to Python's gzip module to decompress the file.

Examples:

Source https://stackoverflow.com/questions/71686366

QUESTION

No such file or directory: 'GoogleNews-vectors-negative300.bin'

Asked 2022-Feb-04 at 06:08

I have this code :

...

ANSWER

Answered 2022-Feb-04 at 06:08

The 'current working directory' that the Python process will consider active, and thus will use as the expected location for your plain relative filename GoogleNews-vectors-negative300.bin, will depend on how you launched Flask.

You could print out the directory to be sure – see some ways at How do you properly determine the current script directory? – but I suspect it may just be the /Users/Ile-Maurice/Desktop/Flask/flaskapp/ directory.

If so, you could relatively-reference your file with the path relative to the above directory...

Source https://stackoverflow.com/questions/70973660

QUESTION

How do I read an image using Rawpy image processing library, from a URL?

Asked 2022-Jan-27 at 13:19

How do I read an image using the rawpy library, from a url?

I have tried

...

ANSWER

Answered 2022-Jan-27 at 12:20

JPEG is not a Raw Image Format. You need to send some raw data as input.

So,

If you just want to process some JPEGs, try Pillow.
If you want to process raw images, change your input data.

Source https://stackoverflow.com/questions/70875810

QUESTION

Issue in Lambda execution time

Asked 2021-Nov-27 at 18:55

I am working on a project where I have to scrape maximum URLs (placed in an S3 bucket's file) in a limited time and store them in searchable database. Right now I am having an issue while scraping web pages inside aws lambda. I have a function for my task which when runs in a google Collab environment takes only 7-8 seconds to execute and produce the desired results. But the same function when deployed as lambda is taking almost 10X more time to execute. Here is my code:

...

ANSWER

Answered 2021-Nov-15 at 20:51

The only thing that you can configure to affect performance is memory allocation. Try increasing the memory allocated for your function, until you have at least the same performance as with Collab.

Billing shouldn't affected much, as it is calculated as the product of memory and execution time.

Source https://stackoverflow.com/questions/69980563

QUESTION

Package built by Poetry is missing runtime dependencies

Asked 2021-Nov-04 at 02:15

I've been working on a project which so far has just involved building some cloud infrastructure, and now I'm trying to add a CLI to simplify running some AWS Lambdas. Unfortunately both the sdist and wheel packages built using poetry build don't seem to include the dependencies, so I have to manually pip install all of them to run the command. Basically I

run poetry build in the project,
cd "$(mktemp --directory)",
python -m venv .venv,
. .venv/bin/activate,
pip install /path/to/result/of/poetry/build/above, and then
run the new .venv/bin/ executable.

At this point the executable fails, because pip did not install any of the package dependencies. If I pip show PACKAGE the Requires line is empty.

The Poetry manual doesn't seem to specify how to link dependencies to the built package, so what do I have to do instead?

I am using some optional dependencies, could that be interfering with the build process? To be clear, even non-optional dependencies do not show up in the package dependencies.

pyproject.toml:

...

ANSWER

Answered 2021-Nov-04 at 02:15

This appears to be a bug in Poetry. Or at least it's not clear from the documentation what the expected behavior would be in a case such as yours.

In your pyproject.toml, you specify two dependencies as required in this section:

Source https://stackoverflow.com/questions/69763090

QUESTION

h5py performs many small reads when accessing data over a file-like object

Asked 2021-Oct-24 at 02:37

I have the following two issues with h5py when passing it a Python file-like object that streams data over a network connection (the file-like object is efficient, e.g. doesn't perform full file scans for ranged reads, using smart_open).

h5py appears to make many calls to read(...) each time reading ~115k bytes (each read varies by a few hundred bytes).
h5py appears to be operating in column major mode, even though this article says it's row major, with a documentation reference.

I was able to count read calls by setting the read function on my file object to a local read function that counts calls and bytes, using functools.partial to do so.

My data is shaped as such:

...

ANSWER

Answered 2021-Oct-22 at 19:36

Compression and chunked I/O are features of HDF5/h5py. (Compression is automatically implemented when chunked I/O is used). Start by checking the dataset chunksize attribute: print(h5file['table'].chunks). Likely this will confirm the 115k value you see. The chunk shape should also indicate why you see read order as column major instead of row major -- because chunk shape1 is larger than chunk shape[0].

If the chunk size is causing the problem, you should use larger chunk size. However, AFAIK, you have to create a new file with new datasets to change to do so.

For reference, here is an example showing a simple array written with 3 different chunk shapes defined. The file is closed then reopened in read mode. Data is read and written to a new file using a larger chunk size. This works around a h5py limitation with group.copy() (it uses the same chunk parameter when it copies datasets). You can also copy datasets and modify chunk I/O attributes with the 'h5repack' external utility from The HDF Group, ref: h5repack doc page.

Source https://stackoverflow.com/questions/69681364

QUESTION

Loading a FastText Model from s3 without Saving Locally

Asked 2021-Oct-07 at 17:56

I am looking to use a FastText model in a ML pipeline that I made and saved as a .bin file on s3. My hope is to keep this all in a cloud based pipeline, so I don't want local files. I feel like I am really close, but I can't figure out how to make a temporary .bin file. I also am not sure if I am saving and reading the FastText model in the most efficient way. The below code works, but it saves the file locally which I want to avoid.

...

ANSWER

Answered 2021-Oct-06 at 16:50

If you want to use the fasttext wrapper for the official Facebook FastText code, you may need to create a local temporary copy - your troubles make it seem like that code relies on opening a local file path.

You could also try the Gensim package's separate FastText support, which should accept an S3 path via its load_facebook_model() function:

https://radimrehurek.com/gensim/models/fasttext.html#gensim.models.fasttext.load_facebook_model

(Note, though, that Gensim doesn't support all FastText functionality, like the supervised mode.)

Source https://stackoverflow.com/questions/69454398

QUESTION

How to add an additional python package to the Pipfile of a docker-compose project (DJANGO)?

Asked 2021-Jul-30 at 06:28

Good day everyone, hope you're doing really well. I would like to start this question by prefacing that I'm a real newbie when it comes to setting up projects in the right way. Right now I'm working on a Django app with a friend that already has some more experience with web development and he had already set up everything with Docker-compose, that is, we have containers for our Django app, MySQL, Celery, RabbitMQ, etc.

Now, I'm working on the back-end side of our project and need to add a new package to the list of packages the app container has: Smart-Open. The thing is, I have no idea how to do that. I'm on Windows, and using Git Bash to launch the docker-compose containers. What I've tried is opened the bash of the web app container and tried to pipenv install the module from there, but it was extremely slow, which made the Pipfile updating timeout:

...

ANSWER

Answered 2021-Jul-30 at 06:28

Does your project directory contain a docker-compose.yml, a Dockerfile, and a requirements.txt file? If so, then the following steps might help.

Open your requirements.txt. You should see all of the python project dependencies listed here. For example, it might look like this initially:

Source https://stackoverflow.com/questions/68583232

QUESTION

Updating the json file edited in Python

Asked 2021-Jul-16 at 17:57

Suppose I have a json file like -

...

ANSWER

Answered 2021-Jul-16 at 17:57

Let me show you with an example how you can do this:

Source https://stackoverflow.com/questions/68357171

QUESTION

How to load a trained model in django

Asked 2021-May-24 at 13:16

I'm working on a django project where I have to use Doc2Vec model to predict most similar articles based on the user input. I have trained a model with the help of articles in our database and when I test that model using a python file .py by right clicking in the file and selecting run from the context menu its working. The problem is Now I'm moving that working code to a django function to load model and predict article based on user-given abstract text But I'm getting FileNotFoundError.
I have searched how to load model in django and it seems the way is already OK. here is the complete exception:

FileNotFoundError at /searchresult
[Errno 2] No such file or directory: 'd2vmodel.model'
Request Method: GET
Request URL: http://127.0.0.1:8000/searchresult
Django Version: 3.1.5
Exception Type: FileNotFoundError
Exception Value:
[Errno 2] No such file or directory: 'd2vmodel.model'
Exception Location: C:\Users\INZIMAM_TARIQ\AppData\Roaming\Python\Python37\site-packages\smart_open\smart_open_lib.py, line 346, in _shortcut_open
Python Executable: C:\Program Files\Python37\python.exe
Python Version: 3.7.9
Python Path:
['D:\Web Work\doc2vec final submission',
'C:\Program Files\Python37\python37.zip',
'C:\Program Files\Python37\DLLs',
'C:\Program Files\Python37\lib',
'C:\Program Files\Python37',
'C:\Users\INZIMAM_TARIQ\AppData\Roaming\Python\Python37\site-packages',
'C:\Program Files\Python37\lib\site-packages']
Server time: Mon, 24 May 2021 12:44:47 +0000
D:\Web Work\doc2vec final submission\App\views.py, line 171, in searchresult
model = Doc2Vec.load("d2vmodel.model")

Here is my django function where I'm loading Doc2Vec model.

...

ANSWER

Answered 2021-May-24 at 13:16

Move the models from App to root directory of your project, I think it is 'doc2vec final submission'

Or create a folder inside 'doc2vec final submission' named 'models'

Change this

Source https://stackoverflow.com/questions/67672494

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install smart_open

You can download it from GitHub.
You can use smart_open like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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