semvec/pypi-packages huggingface dataset:
get-unicode-multiline-input-with-editor 0.1.0a1
Opens `$EDITOR` to get multi-line input as a list of Unicode strings, just like what `git commit` does.
Requires Python: >=2

# `get-unicode-multiline-input-with-editor`

Opens `$EDITOR` to get multi-line input as a list of Unicode strings, just like what `git commit` does.

- Determines `$EDITOR` either manually or via the Git-flavored heuristics in [`get-unicode-arguments-to-launch-editor`](https://github.com/jifengwu2k/get-unicode-arguments-to-launch-editor)
- Supports optional initial content and comment lines
- Opens a temporary file in the editor to get multi-line input
- Ignores comment lines and blank lines in the result
- Works with Python 2+

## Installation

```bash
pip install get-unicode-multiline-input-with-editor
```

## Usage

```python
# coding=utf-8
from __future__ import print_function
from get_unicode_multiline_input_with_editor import get_unicode_multiline_input_with_editor

result = get_unicode_multiline_input_with_editor(
    unicode_initial_input_lines=[
        u'Write something here...',
        u'# Enter your text above.',
        u'# Lines starting with # will be ignored.'
    ],
    unicode_line_comments_start_with=u'#',  # specify `None` to not skip over any line
    editor=None  # or specify e.g. 'vim'
)

print(result)
```

Assuming `nano` is the default editor, the user will see something like this:


```
GNU nano 7.2    /tmp/tmp9khfi5es.txt                                                                                                 
Write something here...
# Enter your text above.
# Lines starting with # will be ignored.












^G Help         ^O Write Out    ^W Where Is     ^K Cut          ^T Execute      ^C Location     M-U Undo        M-A Set Mark
^X Exit         ^R Read File    ^\ Replace      ^U Paste        ^J Justify      ^_ Go To Line   M-E Redo        M-6 Copy
```

Afterward, if the user enters some text, `print(result)` basically prints whatever the user entered, minus the comments.

## Contributing

Contributions welcome! Please open issues or pull requests on GitHub.

## License

This project is licensed under the [MIT License](LICENSE).
appwrite-lab 0.1.5
Zero-click Appwrite test environments.
Requires Python: >=3.11

# appwrite-lab
Zero-click Appwrite test environments.

Allows you to spin up versioned Appwrite deployments for easy testing via CLI or through code, that can be ran in a sequence of E2E tests.

## Installation
```sh
pip install appwrite-lab
```
## Appwrite Lab features
- [x] Spin up ephemeral Appwrite instances with Docker/Podman
- [x] Automatically grab API keys (for programmatic access)
- [x] Environment syncing (with `appwrite.json`)
- [x] Clean teardowns
- [x] Test suite

## Appwrite Lab (in progress)
- [ ] Appwrite data population

## CLI Usage
### Help with appwrite-lab CLI
```sh
appwrite-lab --help
```
or
```sh
awlab --help
```

### To get started spinning up a lab instance, use:

```sh
awlab new lab test --version 1.7.4
```
*Note:* This might take a few minutes the first time as its downloading all of the necessary images to launch Appwrite.
#### Example of additional args:
Additional arguments can be found here.
```sh
awlab new lab --help
```

```sh
awlab new lab test --version 1.7.4 --port 8005 --email test@example.com --password xxxxxxx12
```

### To teardown

```sh
awlab stop test
```
### Listing Appwrite Labs
```sh
awlab list labs
```
<img width="673" height="79" alt="image" src="https://github.com/user-attachments/assets/566bb734-8684-4b5b-ae34-70eac04af812" />

### Sync an Appwrite lab from your prod lab schema
Run in the same folder where your `appwrite.json` is located to sync `all` resources:
```sh
awlab sync test
```
or sync a specific resource:

```sh
awlab sync test --resource functions
```

## Python usage

### Creating a lab
```py
from appwrite_lab import Labs
from appwrite_lab.automations.models import AppwriteLabCreation

labs = Labs()
lab_res = labs.new(
    name="test",
    version="1.7.4",
    auth=AppwriteLabCreation(
        admin_email="test@example.com",
        admin_password="xxxxxxx12",
        project_id=None, # for auto gen
        project_name=None, # for auto gen
    )
    port=8005
)

assert lab_res.data
```

#### Random generation that's compliant
```py
from appwrite_lab.models import AppwriteLabCreation

auth = AppwriteLabCreation.generate()
```

### Syncing a lab
```py
from appwrite_lab import Labs
from appwrite_lab.automations.models import Expiration

Labs().sync_with_appwrite_config(
    name="test",
    appwrite_json="appwrite.json", # if not directly in folder
    sync_type="all",
    expiration=Expiration.THIRTY_DAYS,
)
```
## Known Troubleshooting
### Podman support and Selinux
Since I am mimicking the `compose` file that Appwrite provides, it was not designed to work rootless, but I have adjusted to work also on Fedora. You will need to turn `selinux` off for now to use.
PGMInt 1.1
See Readme
Requires Python: >=3.9

This is a package primarily developed for neutron phase-grating moire interferometry simulations (PGMI, read: https://link.aps.org/doi/10.1103/PhysRevResearch.6.023260), however it should serve well for any reasonably discretizable (again, see the paper previously mentioned) wave optics applications. 

Possible applications are mostly in interferometry (i.e., neutron, optical, and/or atom with modifications). 

Credit: Davis V. Garrad, University of Waterloo, dvlast(at)uwaterloo.ca
License: GNU General Public License (GPL) of your choice of version. See LICENSE.
pytae 2.6.1
A package to enhance common day to day tasks in the life of a data scientist
Requires Python: >=3.7

## This contains following five sets of features. Each of these sets of features are explained in accompanying notebooks.

### 1) Plotting: This is main feature. A light weight plotting package build on top of pandas plot and fully compatible with matplotlib
https://github.com/maddytae/pytae/blob/master/src/plotter.ipynb

### 2) Filtering: qry()
https://github.com/maddytae/pytae/blob/master/src/qry.ipynb

### 3) Selection: select()
https://github.com/maddytae/pytae/blob/master/src/select.ipynb

### 4) Transformations: long(), wide()
https://github.com/maddytae/pytae/blob/master/src/shape.ipynb

### 5) Aggregation: agg_df()
https://github.com/maddytae/pytae/blob/master/src/agg_df.ipynb

### 6) Utilities: clip(), handle_missing(), cols(), group_x()
https://github.com/maddytae/pytae/blob/master/src/other_utilities.ipynb