semvec/pypi-packages huggingface dataset:
insta-fetcher 0.1.2
A script to fetch and organize Instagram data using instaloader
Requires Python: >=3.6

# Insta Fetcher

Insta Fetcher is a Python tool designed to fetch and organize Instagram data using [instaloader](https://instaloader.github.io/). This script automates the process of downloading posts from an Instagram account, organizing them by date, and extracting any `.tar.gz` files.

## Features

- Fetch Instagram posts using instaloader
- Automatically organize downloaded files into date-based directories
- Extract `.tar.gz` files if present
- Automatically installs `instaloader` if not already installed

## Installation

### Prerequisites

- Python 3.6 or higher
- pip

### Steps

1. Clone the repository:

```bash
git clone https://github.com/IvesLiu1026/insta-fetcher.git
cd insta-fetcher
```

2. Create and activate a virtual environment (recommended):
```bash
python3 -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`
```

3. Install the package:
```bash
pip install -e .
```

### Usage

To fetch and organize Instagram data, use the following command:

```bash
insta_fetcher -a INSTAGRAM_ACCOUNT
```

Replace INSTAGRAM_ACCOUNT with the username of the Instagram account you want to download data from.

#### Example
```bash
insta_fetcher -a instagram
```

### Project Structure

- insta_fetcher/:
  - __init__.py: Initializes the package.
  - ins_fetcher.py: Main script to fetch and organize Instagram data.
- README.md: This file.
- setup.py: Setup script for installing the package.
ifcfm 0.7.10
Extract data from IFC following facility management standards
Keywords: IFC, FM, BIM

# IfcFM

IfcFM is a library that handles the extraction and analysis of IFC data for the
purposes of facility management.

It is currently a prototype and will supersede the IfcCOBie library. It is
planned to support workflows related to the old COBie standard, as well as
upcoming IFC Facility Management related MVDs.
ifc4d 0.7.10
IFC 4D scheduling library to support file conversions and calculations
Keywords: IFC, 4D, BIM

# ifc4d

Ifc4D contains a series of utilities for converting to and from various 4D software. Currently supported:

 - Microsoft Project to IFC
 - Oracle Primavera 6 (P6) XML to IFC
 - Oracle Primavera 6 (P6) XER to IFC
 - Asta Powerproject to IFC
 - IFC to Oracle Primavera 6 (P6) XML
 - IFC to Microsoft Project

Planned (would you like to contribute? Please reach out!):

 - IFC to Oracle Primavera 6 (P6) XER
 - IFC to Oracle Primavera 6 (P6) XLS
 - IFC to Asta Powerproject
 - LibreProject to IFC
 - IFC to LibreProject
 - IFC to Gantt

## Useful links

 - [P6 EPPM XER Import/Export Data Map Guide](https://docs.oracle.com/cd/F12057_01/English/Mapping_and_Schema/xer_import_export_data_map_project/helpmain.htm?toc.htm?97881.htm)
 - [Microsoft Project 2007 XML XSD](https://schemas.microsoft.com/project/2007/mspdi_pj12.xsd)
 - [Microsoft Project XML Documentation](https://docs.microsoft.com/en-us/office-project/xml-data-interchange/project-xml-data-interchange-schema-reference?view=project-client-2016)
 - [Microsoft Project 2010 SDK Download](https://www.microsoft.com/en-us/download/details.aspx?id=15511) (needed to get `mspdi_pj14.xsd`)
ifc5d 0.7.10
IFC 5D costing library for quantity take-off and schedule production
Keywords: IFC, 5D, BIM

# ifc5d

## Description

Ifc5D is a collection of utilities of manipulating cost-related data to and from
formats, reports, and optimisation engines.

Currently supported:

 - CSV to IFC
 - IFC to XLSX
 - IFC to CSV
 - IFC to ODS


Planned (would you like to contribute? Please reach out!):


 - IFC to PDF
 - ODS to CSV
 - XLSX to CSV
 - IFC to Graph

## Usage CSV to IFC

## Usage IFC to CSV, ODS, XSLS

#TODO

### CLI app for converting IFC files to CSV, ODS or XLSX format.

Usage:
    python ifc5Dspreadsheet.py input_file output_file [-l log_file] [-f format_type]

Arguments:
    input_file (str): The path to the input IFC file to process.
    output_file (str): The output directory for CSV or filename for other formats.

Options:
    -l, --log log_file (str): The path to the file where errors should be logged. Default is process.log.
    -f, --format format_type (str): The output format to export in (csv/ods/xlsx). Default is csv.

Examples:
    python ifc5Dspreadsheet.py "C:\Users\Dev-Machine\Desktop\test_cost.ifc" rev_01_schedule -l error.log -f ODS
    python ifc5Dspreadsheet.py "C:\Users\Username\Desktop\test_cost.ifc" "C:\Users\Username\Desktop" -l error.log -f CSV

### Scripting:

Example for ODS exports:

```
import ifcopenshell
from ifc5d.ifc5Dspreadsheet import Ifc5DOdsWriter

file = "path_to_file/file.ifc"

path = "directory/cost_schedule"
writer = Ifc5DOdsWriter(file=file, output=path)
writer.write()

```
bsdd 0.7.10
Library to interact with the buildingSMART Data Dictionary
Requires Python: >=3.9
Keywords: IFC, bSDD, BIM

# bsdd

A library to interact with the buildingSMART Data Dictionary (bSDD) API.
This packages is totally independent from other packages in IfcOpenShell and requires only a python installation to run.

## Installation

```bash
pip install git+https://git@github.com/ifcopenshell/ifcopenshell.git@v0.8.0#subdirectory=src/bsdd

# check your installation
python
>>> from bsdd import Client
>>> client = Client()
>>> [l["uri"] for l in client.get_dictionary()["dictionaries"] if "4.3" in l["uri"]][0]
'https://identifier.buildingsmart.org/uri/buildingsmart/ifc/4.3'
```

## Develop

```bash
# create a fork in your domain
git clone git@github.com:<your-name>/IfcOpenShell.git
cd src/bsdd

# if you use vs code / pycharm, you can launch it from this folder
code .

# if you use conda/mamba. follow instructions below:
# otherwise setup a dev env in your preferred way.
mamba create -n bsdd-dev python pytest requests
mamba activate bsdd-dev

# run tests
pytest
```
ifctester 0.7.10
IFC model auditing tool with support for IDS
Keywords: IFC, IDS, BIM

# ifctester

With **IfcTester**, you can author and read **Information Delivery Specification** - **IDS** - files and validate your IFC models against IDS to see if your model is compliant. After the audit, you can generate reports in console, as a web page, JSON or BCF file. It works from the command line, as a web app, or as a library.

## How to use it

### Command line use

.. code-block:: bash

    # run console reporter
    python -m ifctester example.ids example.ifc
    python -m ifctester example.ids example.ifc -r Html -o report.html

Available flags:

- ``-r`` / ``--reporter``: The reporting method to view audit results. Availabe reporters: Console, Txt, Json, Html, Ods, Bcf
- ``--no-color``: Disable colour output (supported by Console reporting).
- ``--excel-safe``: Make sure exported ODS is safely exported for Excel.
- ``-o`` / ``--output``: Output file (supported for all types of reporting except Console).

### Code example

```python
import ifcopenshell
from ifctester import ids, reporter


# create new IDS
my_ids = ids.Ids(title="My IDS")

# add specification to it
my_spec = ids.Specification(name="My first specification")
my_spec.applicability.append(ids.Entity(name="IFCWALL"))
property = ids.Property(
    baseName="IsExternal",
    value="TRUE", 
    propertySet="Pset_WallCommon", 
    dataType="IfcBoolean",
    uri="https://identifier.buildingsmart.org/uri/.../prop/LoadBearing", 
    instructions="Walls need to be load bearing.",
    cardinality="required")
my_spec.requirements.append(property)
my_ids.specifications.append(my_spec)

# Save such IDS to file
result = my_ids.to_xml("SampleIDS.xml")

# open  IFC file:
my_ifc = ifcopenshell.open("MyIfcModel.ifc")

# validate IFC model against IDS requirements:
my_ids.validate(my_ifc)

# show results:
reporter.Console(my_ids).report()
```
ninja-authtoken 1.0.1
A simple Django app for django-ninja authentication tokens
Requires Python: >=3.6

# ninja-authtoken
## A simple Django app for django-ninja authentication tokens

## source code : [Visit GitHub!](https://github.com/MoriZoki/ninja-authtoken/)

#### installaton

```shell
pip install ninja-authtoken
```

#### add ninja-authtoken to django installed app

```python
INSTALLED_APPS = [
    ...
    "authtoken",
    ...
]
```

#### set user model in settings.py
#### Example {AUTH_USER_MODEL = "accounts.USER"}


## Usage
**for routers**

```python
from authtoken.security import APIKeyAuth

auth = APIKeyAuth()

@router.get('profile/', auth=auth)
def profile(request):
    return f"Hello, {request.user}!"
```

**Api Base**

```python
from ninja import NinjaAPI
from authtoken.security import APIKeyAuth

#  ...

api = NinjaAPI(auth=APIKeyAuth())

# ...

@api.get("/profile")
def profile(request):
    return f"Hello, {request.user}!"
```



**ـ The token is generated automatically as soon as a new user is created by Signal ـ**