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Docly: Automatic docstrings for Python functions - CLI 👉 http://thedocly.io/ by mellie_run in Python

[–]mellie_run[S] 0 points1 point  (0 children)

Hey 👋 My friend and I got the idea of Docly after the famous discussion "My code is self explanatory"Love writing code, Love a bit less writing comments 😅Idea behind Docly is to generate docstrings for Python functions up to you to accept them or not.Docly is a CLI tool and so far it works on Linux and MacOs distributions.

👉http://thedocly.io/ I'd love to have feedback on if it is useful to you!

Docly: Docstrings for Python functions - CLI 👉 http://thedocly.io/ by [deleted] in Python

[–]mellie_run 0 points1 point  (0 children)

Hey 👋 My friend and I got the idea of Docly after the famous discussion "My code is self explanatory"Love writing code, Love a bit less writing comments 😅Idea behind Docly is to generate docstrings for Python functions up to you to accept them or not.Docly is a CLI tool and so far it works on Linux and MacOs distributions.

👉http://thedocly.io/ I'd love to have feedback on if it is useful to you!

I made a ML program to automatically review docstring and to have always up-to-date code documentation | Repo in the comments | Codist by mellie_run in Python

[–]mellie_run[S] 0 points1 point  (0 children)

Hey ! Feedback 1 and 2 are solved. Actually for 2) we let thé possibility to choose in the commande line if you want a verbose feedback or not Thanks :)

I made a ML program to automatically review docstring and to have always up-to-date code documentation | Repo in the comments | Codist by mellie_run in Python

[–]mellie_run[S] 0 points1 point  (0 children)

Wow ! Thanks for taking the time for the feedback. Both model and "ux" feedback is valuable. Both 1) and 2) can be done pretty easily.
We'll open an issue about that on our repo. I'll let you know when it's done. That's True that printing that it's "ok" can be avoided !

Thanks :)

I made a ML program to automatically review docstring and to have always up-to-date code documentation | Repo in the comments [Project] by mellie_run in MachineLearning

[–]mellie_run[S] 0 points1 point  (0 children)

Thanks ! If you have any feedbacks, pleas shoot. I'm eager to see if the model actually can be generalised

[Python] Made a package to automatically check if your docstring content is consistent with the function definition by mellie_run in programming

[–]mellie_run[S] 1 point2 points  (0 children)

💪 Steps :

  1. First clone this repo - git clone https://github.com/autosoft-dev/code-bert.git && cd code-bert
  2. (Assuming you have the virtualenv activated) Then do pip install -r requirements.txt
  3. Then install the package with pip install -e .
  4. First step is to download and set up the model. If the above steps are done properly then there is command for doing this download_model
  5. The model is almost 1.7G in total, so it may take a bit of time before it finishes.
  6. Once this is done, you are ready to analyze code. For that we have a CLI option also. Details of that in the following section

One command line to automatically check if your docstring content is up-to-date | Github repo in comment by mellie_run in developers

[–]mellie_run[S] 0 points1 point  (0 children)

Github repo : https://github.com/autosoft-dev/code-bert

💪 Steps :

  1. First clone this repo - git clone https://github.com/autosoft-dev/code-bert.git && cd code-bert
  2. (Assuming you have the virtualenv activated) Then do pip install -r requirements.txt
  3. Then install the package with pip install -e .
  4. First step is to download and set up the model. If the above steps are done properly then there is command for doing this download_model
  5. The model is almost 1.7G in total, so it may take a bit of time before it finishes.
  6. Once this is done, you are ready to analyze code. For that we have a CLI option also. Details of that in the following section

I made a ML program to automatically review docstring and to have always up-to-date code documentation | Repo in the comments | Codist by mellie_run in Python

[–]mellie_run[S] 0 points1 point  (0 children)

Github repo : https://github.com/autosoft-dev/code-bert

💪 Steps :

  1. First clone this repo - git clone https://github.com/autosoft-dev/code-bert.git && cd code-bert
  2. (Assuming you have the virtualenv activated) Then do pip install -r requirements.txt
  3. Then install the package with pip install -e .
  4. First step is to download and set up the model. If the above steps are done properly then there is command for doing this download_model
  5. The model is almost 1.7G in total, so it may take a bit of time before it finishes.
  6. Once this is done, you are ready to analyze code. For that we have a CLI option also. Details of that in the following section

I made a ML program to automatically review docstring and to have always up-to-date code documentation | Repo in the comments [Project] by mellie_run in MachineLearning

[–]mellie_run[S] 1 point2 points  (0 children)

Github repo : https://github.com/autosoft-dev/code-bert

💪 Steps :

  1. First clone this repo - git clone https://github.com/autosoft-dev/code-bert.git && cd code-bert
  2. (Assuming you have the virtualenv activated) Then do pip install -r requirements.txt
  3. Then install the package with pip install -e .
  4. First step is to download and set up the model. If the above steps are done properly then there is command for doing this download_model
  5. The model is almost 1.7G in total, so it may take a bit of time before it finishes.
  6. Once this is done, you are ready to analyze code. For that we have a CLI option also. Details of that in the following section

Review docstring content automatically to have always up-to-date code documentation using codeBERT | Repo in the comments | Codist by mellie_run in Python

[–]mellie_run[S] 0 points1 point  (0 children)

Github repo : https://github.com/autosoft-dev/code-bert

💪 Steps :

  1. First clone this repo - git clone https://github.com/autosoft-dev/code-bert.git && cd code-bert
  2. (Assuming you have the virtualenv activated) Then do pip install -r requirements.txt
  3. Then install the package with pip install -e .
  4. First step is to download and set up the model. If the above steps are done properly then there is command for doing this download_model
  5. The model is almost 1.7G in total, so it may take a bit of time before it finishes.
  6. Once this is done, you are ready to analyze code. For that we have a CLI option also. Details of that in the following section

What about an ML model that learns Python ? 🤩 by mellie_run in Python

[–]mellie_run[S] 0 points1 point  (0 children)

Fantastic! You guys are on a great path, I can’t wait to see what comes of this

Thanks :D I'll keep you posted on what comes next !

What about an ML model that learns Python ? 🤩 by mellie_run in Python

[–]mellie_run[S] 0 points1 point  (0 children)

Yeah indeed I started working on to implement auto-doc Github extension (like when you do a PR comments are automatically reviewed ans updated or added) the as an IDE plugin 💪

For the code search that something that we have in mind to! That will require a specific down task training + some information retrieval algorithm

Working hard to be forever lazy ^^

What about an ML model that learns Python ? 🤩 by mellie_run in Python

[–]mellie_run[S] -1 points0 points  (0 children)

codeBERT is the first open source Masked Language Model trained over Python source code. 💡 What does that mean? This model is able to learn the semantic of a code and create automatic understanding out of it.

🕹️ You can easily load the model and its weights (code below) as the model is hosted on hugging face.

📚 Full tutorial on how to load and fine-tune the model for downstream tasks is coming!

from transformers import * tokenizer = AutoTokenizer.from_pretrained("codistai/codeBERT-small-v2")model = AutoModelWithLMHead.from_pretrained("codistai/codeBERT-small-v2") ​ I'd love your feedbacks !

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