This is a collection of Python utilities that I use in my projects.
To use them, follow each specific utility instructions here or on it's folder.
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Clone this repository
git clone
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Enter the folder
cd python-utils -
Create a virtual environment
python3 -m venv .venv
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Activate the virtual environment
source .venv/bin/activate -
Install the dependencies
pip install -r requirements.txt
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Run the desired utility!
python3 <utility_name>.py <args>
Script: parse_folder.py
This utility parses a folder and its sub-folders and stores the results either in a JSON or in a CSV file.
- Usage
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To export the results in a JSON file, run the following command:
python parse_folder.py <path> --json
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To export the results in a CSV file, run the following command:
python parse_folder.py <path> --csv
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Example
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Existing directory structure:
project │ README.md │ file001.txt │ └───folder1 │ │ file011.txt │ │ file012.txt │ │ │ └───subfolder1 │ │ file111.txt │ │ file112.txt │ │ ... │ └───folder2 │ file021.txt │ file022.txt -
To get a JSON file, you should run the following command:
python parse_folder.py project --json
Output:
[ { "file": "README.md", "parent_dir": "project", "other_parent_dirs": "", }, [...] { "file": "file011.txt", "parent_dir": "project", "other_parent_dirs": "folder1", }, [...] { "file": "file112.txt", "parent_dir": "project", "other_parent_dirs": "folder1, subfolder1", }, [...] ] -
Or, to get a CSV file, you should run the following command:
python parse_folder.py project --csv
And, you will get:
file parent_dir other_parent_dirs README.md project [...] file011.txt project folder1 [...] file112.txt project folder1, subfolder1
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Script: transparency_TJPR.py
This script simply extracts data from Paraná's Court of Justice and returns simple and queryable CSV with a summary of the financial results of the notaries and other agencies linked to the Court.
Transparência: verdadeira e simplificada
- Currently, it only extracts financial results data from Extrajudicial Agencies of TJPR
- Usage
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To run it, ensure that you have the
requestslibrary installed, with:pip install requests
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Then, just run the
transparency_TJPR.pyin your terminal and choose the simple or detailed option.python transparency_TJPR.py
With the simple option, you will see only the final result of the extraction when finished.
With the detailed option, you will see line by line the extraction of the data.
- Examples
At the end, you will have a CSV with all the data, and you can view them in a table with a structure similar to this:
| Comarca / Serventia Extrajudicial | 2018 | 2019 | 2020 | 2021 | Total Geral |
|---|---|---|---|---|---|
| 8º Serviço de Registro de Imóveis do Foro Central da Comarca da Região Metropolitana de Curitiba | R$ 5.440.730,81 | R$ 12.778.474,63 | R$ 9.861.284,99 | R$ 13.257.083,50 | R$ 41.337.573,93 |
| 1º Serviço de Registro de Imóveis do Foro Central da Comarca da Região Metropolitana de Londrina | R$ 3.837.116,05 | R$ 9.120.386,31 | R$ 8.458.784,80 | R$ 6.567.534,67 | R$ 27.983.821,83 |
| 6º Serviço de Registro de Imóveis do Foro Central da Comarca da Região Metropolitana de Curitiba | R$ 3.253.248,89 | R$ 8.508.878,89 | R$ 6.801.850,23 | R$ 4.325.247,56 | R$ 22.889.225,57 |
| 1º Serviço de Registro de Imóveis do Foro Central da Comarca da Região Metropolitana de Maringá | R$ 2.543.310,21 | R$ 5.260.576,85 | R$ 5.528.040,95 | R$ 5.256.915,15 | R$ 18.588.843,16 |
| 2º Serviço de Registro de Imóveis do Foro Central da Comarca da Região Metropolitana de Curitiba | R$ 1.707.215,29 | R$ 6.224.611,35 | R$ 4.721.166,74 | R$ 5.913.923,44 | R$ 18.566.916,82 |
| *** | *** | *** | *** | *** | *** |
| 1º Serviço de Registro de Imóveis do Foro Regional de São José dos Pinhais da Comarca da Região Metropolitana de Curitiba | R$ 2.200.614,00 | R$ 5.196.023,24 | R$ 4.662.502,86 | R$ 5.850.969,91 | R$ 17.910.110,01 |
| 2º Serviço de Registro de Imóveis do Foro Central da Comarca da Região Metropolitana de Maringá | R$ 2.618.460,03 | R$ 4.887.744,57 | R$ 4.999.803,24 | R$ 4.307.329,32 | R$ 16.813.337,16 |
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TODO
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Extract data from judicial notaries
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Extract data from employees
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Extract revenues and expenses data of the Court
Script: consolidate_email_addresses.py
- Description
This script finds and consolidates all unique email addresses found in CSV files, ensuring to remove duplicates and sorting them.
It's useful when you have a lot of CSV files with email addresses and you want to consolidate them in a single CSV file.
This situation might happen when you export all your contacts from your email client (such as Outlook).
- Usage
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To run it, change the
CSV_DIRvariable to the directory where your CSV files filled with email addresses are located.CSV_DIR = 'path/to/csv/files'
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Then, just run the
consolidate_email_addresses.pyin your terminal.python consolidate_email_addresses.py
Script: extract_contacts_whatsapp.py
This is a really old script that I wrote to extract the contacts from a WhatsApp group. It was written it uses the selenium library to simulate a browser and extract the contacts.
NOTE: This script is not working anymore, because WhatsApp changed the way to access the group's contacts.
- Usage:
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Change the
CHAT_NAMEconstant to the name of the chat you want to extract the contacts from:# Change the name of the chat here CHAT_NAME = "<chat name>"
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Run the script:
python extract_contacts_whatsapp.py