onegram | This repository | REST library

by pauloromeira Python Version: 1.3.2 License: MIT

X-Ray Key Features Code Snippets(2)Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | onegram Summary

onegram is a Python library typically used in Web Services, REST, Discord applications. onegram has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install onegram' or download it from GitHub, PyPI.

A simplistic api-like instagram bot powered by requests.

Support

Quality

Security

License

Reuse

Support

onegram has a low active ecosystem.

It has 137 star(s) with 6 fork(s). There are 11 watchers for this library.

It had no major release in the last 12 months.

There are 7 open issues and 5 have been closed. On average issues are closed in 2 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of onegram is 1.3.2

Quality

onegram has 0 bugs and 0 code smells.

Security

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

onegram code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

onegram 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

onegram releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

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

Installation instructions are not available. Examples and code snippets are available.

onegram saves you 425 person hours of effort in developing the same functionality from scratch.

It has 1006 lines of code, 121 functions and 16 files.

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

Top functions reviewed by kandi - BETA

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

Enter context manager
Update the CSRF token from cookies
Return the rank of comments for a given user
Iterate through a query
Calculate progress
Search content using jmespath
Return the rank of each user in the given user
Logs the session
Login to UCS
Generates a generator from a sequence of choices

Get all kandi verified functions for this library.

onegram Key Features

No Key Features are available at this moment for onegram.

onegram Examples and Code Snippets

Python - Invalid syntax

Python

Lines of Code : 2

License : Strong Copyleft (CC BY-SA 4.0)

Copy

print(fdist_onegram.plot(30)

Python: Fastest way to find list of words [with n-grams] in text conversations

Python

Lines of Code : 5

License : Strong Copyleft (CC BY-SA 4.0)

Copy

def count_words(doc, find):
    word_list = doc.split()
    onegram = [' '.join(grams) for grams in ngrams(word_list, 1)]
    ...

Community Discussions

Trending Discussions on onegram

Quanteda: Fastest way to replace tokens with lemma from dictionary?

Python - Invalid syntax

Split a sentence to word columns using loops or functions in R?

QUESTION

Quanteda: Fastest way to replace tokens with lemma from dictionary?

Asked 2018-May-14 at 15:48

Is there a much faster alternative to R quanteda::tokens_lookup()?

I use tokens() in the 'quanteda' R package to tokenize a data frame with 2000 documents. Each document is 50 - 600 words. This takes a couple of seconds on my PC (Microsoft R Open 3.4.1, Intel MKL (using 2 cores)).

I have a dictionary object, made from a data frame of nearly 600 000 words (TERMS) and their corresponding lemma (PARENT). There are 80 000 distinct lemmas.

I use tokens_lookup() to replace the elements in the token-list by their lemmas found in the dictionary. But this takes at least 1,5 hours. This function is TOO slow for my problem. Is there a quicker way, while still getting a token list?

I want to transform the token list directly, to be make ngrams AFTER using the dictionary. If I only wanted onegrams I could easily have done this by joining the document-feature matrix with the dictionary.

How can I do this faster? Convert token list to data frame, join with dictionary, convert back to ordered token list?

Here is the sample code:

...

ANSWER

Answered 2017-Oct-14 at 12:21

I don't have a lemma list to benchmark myself, but this is the fastest way to covert token types. Please try and let me know how long it takes (should be done in a few seconds).

Source https://stackoverflow.com/questions/46731429

QUESTION

Python - Invalid syntax

Asked 2018-May-10 at 10:35

I have this error: Invalid syntax in my code below:

...

ANSWER

Answered 2018-May-10 at 10:35

When you see a syntax error on a line that seems fine, look at the preceding line. In this case you forgot closing parenthesis.

Source https://stackoverflow.com/questions/50270844

QUESTION

Split a sentence to word columns using loops or functions in R?

Asked 2018-Mar-25 at 16:19

I have a dataframe corpus in R which looks like this :enter image description here And I want to create n-grams(upto 5-grams) using loops or functions. currently, I am doing it manually in this way:

Sample corpus structure:

{"colleagues were also at the other two events in aberystwyth and flint and by all accounts had a great time", "the lineup was whittled down to a more palatable five in when the bing crosby souffle going my way bested both gaslight and double indemnity proving oscar voters have always had a taste for pabulum", "felt my first earthquake today whole building at work was shaking", "she is the kind of mother friend and woman i aspire everyday to be", "she was processed and released pending a court appearance", "watching some sunday night despite the sadness i have been feeling i also feel very blessed and happy to be carrying another miracle", "every night when we listen to poohs heartbeat our hearts feel so much happiness and peace",}

...

ANSWER

Answered 2018-Mar-25 at 16:19

I don't know the function NGramTokenizer and couldn't get it to work. So here is a solution in quanteda, which produces individual tokens objects for each iteration (gram_1 for onegram, gram_2 for bigrams and so on):

Source https://stackoverflow.com/questions/49477358

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

Vulnerabilities

No vulnerabilities reported

Install onegram

You can install using 'pip install onegram' or download it from GitHub, PyPI.
You can use onegram 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 .

Find more information at: