semvec/pypi-packages huggingface dataset:
hatch-msgfmt 1.1.6
Msgfmt build hook, replacing all po with mo in build
Requires Python: >=3.7

# hatch-msgfmt
A hatch msgfmt plugin, simply replacing all po files with mo files, using msgfmt in `PATH`.

At a future point, a pure-python version could be implemented, by implementing
a pure-Python version of msgfmt.  [The standard cpython msgfmt.py](https://
github.com/python/cpython/blob/main/Tools/i18n/msgfmt.py) could be a starting
point for this, but it's not as capable as GNU Gettext, and doesn't support
plural forms.  Even with a fresh implementation, handling the file encoding
from the header is challenging, especially for variable-length encodings like
EUC-JP, which could feasibly cause particular problems.

Better to just use the system one for now.  If somebody wants to submit a pure-
python implementation that functions, I'll gladly integrate it as a separate
`msgfmtpy` plugin in the same repository.

# Config parameters

* `locales`: The location of the source `.po` files.

* `destination`: The location of the destination `.mo` files.  They will be put
  into this location in the same structure as the source tree relative to the
  `locales` path.

* `pathsub_regex` (optional): An input regex to match against source files for
  name changes.

* `pathsub_replace` (required if `pathsub_regex` is present): An replacement
  pattern to use for name changes.

# Copyright

This plugin is Copyright 2023 Absolute Performance, Inc. with contributions by
[Adrián Chaves](https://github.com/Gallaecio).

MIT licensed.
pandas2pg 0.0.1
A package that contains several functions for interacting with a PostgreSQL database using Python and the Pandas library
Requires Python: >=3.10

## Description

This package contains several functions for interacting with a PostgreSQL database using Python and the Pandas library. Specifically, it includes functions for:

- Loading data from a CSV file to a Pandas dataframe
- Mapping Pandas datatypes to suitable PostgreSQL datatypes
- Creating new tables on a PostgreSQL database
- Inserting data from a Pandas DataFrame into a table in a PostgreSQL database

## Functions

### `csv_to_dataframe(filepath: str) -> pd.DataFrame`

This function reads a CSV file and returns a Pandas DataFrame.

### `get_dtatframe_column_dtypes_dict(dataframe: pd.DataFrame) -> dict`

This function takes a Pandas DataFrame as input and returns a dictionary with the data types of each column.

### `map_pandas_to_postgresql_datatypes(column_datatype_dict: dict) -> dict`

This function maps Pandas datatypes to suitable PostgreSQL datatypes.

### `connect_to_postgresql(**connection_params)`

This function takes keyword arguments containing connection parameters for a PostgreSQL database and returns a database connection object.

### `create_postgresql_table(connection, table_name, field_dict) -> bool`

This function creates a new table with the specified name and fields using the provided database connection.

### `insert_dataframe_into_postgresql(connection, table_name, dataframe) -> None`

This function inserts all values in a Pandas DataFrame into a table in a PostgreSQL database.

## Dependencies

This package requires the following Python libraries:

- `pandas`
- `psycopg2`

It also assumes that a PostgreSQL database is available and that the necessary connection parameters are provided to the `connect_to_postgresql` function.
pandas2pg-adolfoj 0.0.1
A package that contains several functions for interacting with a PostgreSQL database using Python and the Pandas library
Requires Python: >=3.10

## Description

This package contains several functions for interacting with a PostgreSQL database using Python and the Pandas library. Specifically, it includes functions for:

- Loading data from a CSV file to a Pandas dataframe
- Mapping Pandas datatypes to suitable PostgreSQL datatypes
- Creating new tables on a PostgreSQL database
- Inserting data from a Pandas DataFrame into a table in a PostgreSQL database

## Functions

### `csv_to_dataframe(filepath: str) -> pd.DataFrame`

This function reads a CSV file and returns a Pandas DataFrame.

### `get_dtatframe_column_dtypes_dict(dataframe: pd.DataFrame) -> dict`

This function takes a Pandas DataFrame as input and returns a dictionary with the data types of each column.

### `map_pandas_to_postgresql_datatypes(column_datatype_dict: dict) -> dict`

This function maps Pandas datatypes to suitable PostgreSQL datatypes.

### `connect_to_postgresql(**connection_params)`

This function takes keyword arguments containing connection parameters for a PostgreSQL database and returns a database connection object.

### `create_postgresql_table(connection, table_name, field_dict) -> bool`

This function creates a new table with the specified name and fields using the provided database connection.

### `insert_dataframe_into_postgresql(connection, table_name, dataframe) -> None`

This function inserts all values in a Pandas DataFrame into a table in a PostgreSQL database.

## Dependencies

This package requires the following Python libraries:

- `pandas`
- `psycopg2`

It also assumes that a PostgreSQL database is available and that the necessary connection parameters are provided to the `connect_to_postgresql` function.