flanker | Python email address and Mime | Email library

by mailgun Python Version: v0.9.15 License: Apache-2.0

X-Ray Key Features Code Snippets(1)Community Discussions(5)Vulnerabilities Install Support

kandi X-RAY | flanker Summary

flanker is a Python library typically used in Messaging, Email applications. flanker 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.

Python email address and Mime parsing library

Support

Quality

Security

License

Reuse

Support

flanker has a medium active ecosystem.

It has 1580 star(s) with 200 fork(s). There are 90 watchers for this library.

It had no major release in the last 12 months.

There are 52 open issues and 36 have been closed. On average issues are closed in 129 days. There are 16 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of flanker is v0.9.15

Quality

flanker has 0 bugs and 0 code smells.

Security

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

flanker code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

flanker is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

flanker releases are available to install and integrate.

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

flanker saves you 4291 person hours of effort in developing the same functionality from scratch.

It has 9098 lines of code, 790 functions and 88 files.

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

Top functions reviewed by kandi - BETA

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

Parse an address
Unquote a string
Lift a parse result
Convert val to text
Validate a list
Validate an address specification
Lookup the mail exchange for a given domain
Get the global cache
Signs a message
Parse an email address
Return the size in bytes
Match style parameters
Match new style
Get the content type
Set the charset
Create an instance from a stream
Generate a new email address
Return a list of MessageId
Write headers to stream
Sign a message
Validate an email address
Create an attachment
Suggest an address for an address
Apply a function to the headers
The body
Converts a message into a string
Returns the filename of the MIME header

Get all kandi verified functions for this library.

flanker Key Features

No Key Features are available at this moment for flanker.

flanker Examples and Code Snippets

An example experiment

Jupyter Notebook

Lines of Code : 7

License : Permissive (Apache-2.0)

Copy

train_11-1-1-1-1_total_pool_contrast_areafactor_lr0.001.sh
train_11-1-1-1-1_total_pool_contrast_areafactor_lr0.01.sh
train_11-1-1-1-1_total_pool_contrast_areafactor_lr0.1.sh
train_11-1-1-1-1_total_pool_contrast_None_lr0.001.sh
train_11-1-1-1-1_total_

Community Discussions

Trending Discussions on flanker

How to calculate conditional means from .txt files

x-axis labels ggplot2 in R

Changing font size on collated plot

JSON navigation

GGPlot combining/overlaying column and line (Gantt) charts

QUESTION

How to calculate conditional means from .txt files

Asked 2021-Dec-16 at 01:01

I'm fairly new to programming and am looking for some guidance. Any help is appreciated.

Here's what I'm trying to do: I have a large number of .txt files from a cognitive experiment (Flanker task, if curious) that I need to compute means for based on condition. The files have no headers and look like below:

XXXXX 1 1 675
XXYXX 0 1 844
YYYYY 1 1 599
YYXYY 0 1 902

I would like to compute means for miliseconds (rightmost column; c4) based on the experimental condition (0 or 1; c2). I would also need the file name of each .txt file (my participant ID) included in the output.

I'm most familiar with R but really just for data analysis. I also have a little experience with Python and Matlab if those (or something else) better suit my needs. Again, a point in any direction would be greatly appreciated.

Thanks

...

ANSWER

Answered 2021-Dec-16 at 00:46

The Tidyverse collection of packages specially the dplyr and readr can easy do this task for you on a grammar likely SQL.

Something like

Source https://stackoverflow.com/questions/70371957

QUESTION

x-axis labels ggplot2 in R

Asked 2021-Apr-21 at 21:09

I am trying to label my individual boxplots in this graph as "Cong." and "Incong." I am drawing from a df "flanker.Summary.ID.RT", and using the column in this df "Type" for the boxplot x-axis, and the column "Flanker.RT" for the boxplot y-axis. I am currently trying this code:

...

ANSWER

Answered 2021-Apr-21 at 21:09

To relabel values on the x axis with scale_x_discrete() you need to access the labels argument. Here's a demonstration:

Source https://stackoverflow.com/questions/67203268

QUESTION

Changing font size on collated plot

Asked 2021-Apr-21 at 14:22

I want to make the font bigger on the axes on a collated plot. I'd like both the axes on the collated plot, as well as the axes on each individual plot to be bigger. Is there an easy way to do this without individually going into each of the plots I've collated together and changing the font size- for example, can I add anything to the plot_grid() function to do this? Code for context is included below.

...

ANSWER

Answered 2021-Apr-21 at 14:22

If you're willing to switch to the patchwork package for plot composition, you can easily set global theme elements with the & theme(...) operation. Simplified example below.

Source https://stackoverflow.com/questions/67197510

QUESTION

JSON navigation

Asked 2020-Nov-03 at 00:27

I am trying to implement the Websters Dictionary into this python code so that I can look up the definition of a word.

As Trigonom pointed out I can search for "shortdef" in the JSON

...

ANSWER

Answered 2020-Nov-03 at 00:23

As the error indicates, the JSON result is a list. In particular, a list of objects.

There are multiple shortdefs, and you need to parse each object out

Source https://stackoverflow.com/questions/64617996

QUESTION

GGPlot combining/overlaying column and line (Gantt) charts

Asked 2020-Jan-22 at 08:51

I would like to overlay rainfall data (column) over a Gantt chart that contains 'suggested sowing windows' and actual sowing dates. From the dataset, I can create both separately but not on one chart. Any pointers greatly appreciated.

...

ANSWER

Answered 2020-Jan-22 at 08:51

As you can see on the image that you have posted - the plot you are shown just overlays two plots. Although this is also possible to do with ggplot2, I don't find this very elegant, and can be very tricky, because you need to find the exact positions of both plots so that it looks neat.

Your workaround using geom_line with your factor levels as y values is interesting, but I am not sure if so desirable.

In any case - this is probably the core of your problem. You are mixing different y measures - and they are of different classes. Factor levels for one plot, numeric / integer for the other. This is problematic. I would not try hard and force those into one y-axis, but I would rather create two plots and combine them with one of the plot combining packages such as patchwork. Like so

I have renamed your columns, am using a package from GitHub user @alisdaire47 for reading your data and also change some columns in order to achieve the plot. Key is using the right classes: Dates as dates, numerics as numerics.

First read your data:

Source https://stackoverflow.com/questions/59834007

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

Vulnerabilities

No vulnerabilities reported

Install flanker

You can download it from GitHub.
You can use flanker 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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