semvec/pypi-packages huggingface dataset:
zodb-convert 1.0.0b1
Generic ZODB storage conversion tool
Requires Python: >=3.12

# zodb-convert

Generic ZODB storage conversion tool. Copies data between any two ZODB-compatible storages.

Derived from [RelStorage's zodbconvert](https://github.com/zodb/relstorage) by the
Zope Foundation and Contributors, extracted as a standalone generic tool.

## Installation

```bash
pip install zodb-convert
```

To convert between specific storage types, install their packages too:

```bash
pip install zodb-convert ZODB RelStorage  # FileStorage ↔ RelStorage
pip install zodb-convert ZODB zodb-pgjsonb  # FileStorage ↔ PGJsonb
```

## Usage

### Traditional config file

Create a config file (`convert.conf`):

```
<filestorage source>
    path /data/Data.fs
    blob-dir /data/blobs
</filestorage>

<filestorage destination>
    path /backup/Data.fs
    blob-dir /backup/blobs
</filestorage>
```

For storages that need blob wrapping:

```
<blobstorage source>
    blob-dir /data/blobs
    <filestorage>
        path /data/Data.fs
    </filestorage>
</blobstorage>

<filestorage destination>
    path /backup/Data.fs
    blob-dir /backup/blobs
</filestorage>
```

For third-party storages, use `%import`:

```
%import relstorage

<relstorage source>
    <postgresql>
        dsn dbname=zodb user=zodb
    </postgresql>
</relstorage>

<filestorage destination>
    path /backup/Data.fs
</filestorage>
```

Run:

```bash
zodb-convert convert.conf
```

### Using existing zope.conf files

Extract storage configuration directly from Zope config files:

```bash
zodb-convert --source-zope-conf /old/etc/zope.conf --dest-zope-conf /new/etc/zope.conf
```

Specify which database to use (defaults to "main"):

```bash
zodb-convert --source-zope-conf zope.conf --source-db main \
             --dest-zope-conf other.conf --dest-db catalog
```

### Mixed mode

Combine traditional config with zope.conf extraction:

```bash
zodb-convert convert.conf --source-zope-conf /old/etc/zope.conf
```

Where `convert.conf` contains only the destination storage section.

### Options

- `--dry-run` — show what would be copied without making changes
- `--incremental` — resume from the last transaction in the destination
- `-v` / `--verbose` — increase verbosity (`-v` for INFO, `-vv` for DEBUG)

## License

ZPL-2.1 — see [LICENSE.txt](LICENSE.txt)
backuprotation 0.0.2
A tool for rotating backups
Requires Python: >=3.7

Backuprotation
==============

A minimalistic python tool which allows you to easily rotate your backups, whether they are a directory or files.


## Installation

`backuprotation` is available through `pip`

```shell
pip install backuprotation
```

## Usage

To rotate your backups which are stored in `./path` simply run

```shell
backuprotation ./path
```
and `backuprotation` will look through `./path` and keep the last ten directories while deleting the rest.

You can specify the amount of backups to keep with `-n` or `--number`
```shell
backuprotation -n 20 ./path
```

By default `backuprotation` looks for directories but it can also rotate files or both files and directories
```shell
backuprotation -f ./path        # files
backuprotation -fd ./path       # files and directories
```

If you're ever unsure of what effects `backuprotation` will have you can perform a dry-run to verify.
```shell
backuprotation --dry-run ./path
```
This will print out the changes that `backuprotation` would perform without actually changing the filesystem.
crospint 0.1.6
Coordinate Rotation for Spatial Interpolation
Requires Python: >=3.12

#  `crospint`: Coordinate Rotation for Spatial Interpolation

This package provides lightweight utilities and `scikit-learn`-compatible transformers to build efficient **machine learning pipelines for spatio-temporal interpolation** with tree-based ensemble methods. This package also contains functions and classes uses to model housing prices at the national scale (see Meslin [2026]).

This package has three distinctive features:

- It offers a native `sklearn.Pipeline` integration;
- It uses [`polars`](https://pola.rs/) for fast feature engineering but is also fully [`pandas`](https://pandas.pydata.org/)-compatible to simplify use with other ML libraries;
- It is agnostic to the algorithms used for interpolation (though is uses [`lightgbm`](https://lightgbm.readthedocs.io/en/stable/) by default).

This package also contains functions and classes uses to model housing prices at the national scale (see Meslin [2026]).

## Installation

Just execute `uv add crospint` or `pip install crospint`.

## Basic use

To be completed

# Notebooks

Two notebooks illustrate the valuation method describe in Meslin [2026]:

- How to apply the conditional tail removal procedure [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/oliviermeslin/crospint/blob/improve_readme/notebooks/outlier_removal_through_CTR.ipynb)

- How to train price models at the national scale [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/oliviermeslin/crospint/blob/improve_readme/notebooks/model_training_and_evaluation.ipynb)