From 6d21506eb6eaec7be9b17b04da109753bedfcea1 Mon Sep 17 00:00:00 2001 From: lum4chi Date: Fri, 21 Jul 2023 16:25:26 +0200 Subject: [PATCH] Improved readme and user manual detection --- Home.py | 3 ++- README.md | 18 +++++++++++------- 2 files changed, 13 insertions(+), 8 deletions(-) diff --git a/Home.py b/Home.py index 9076313..fc160e3 100644 --- a/Home.py +++ b/Home.py @@ -8,6 +8,7 @@ if __name__ == "__main__": with open("README.md", "r") as readme: - app_description = "".join([next(readme) for _ in range(18)]) + app_description = "".join(readme).split("# Installation")[0] + st.markdown(app_description) session_console() diff --git a/README.md b/README.md index ff30375..6cc73f9 100644 --- a/README.md +++ b/README.md @@ -1,24 +1,25 @@ # 🇪🇺 Eurostat Data Wizard -A straightforward webapp to export easily multiple Eurostat datasets. +A webapp to export easily multiple Eurostat datasets. -## Lookup +## User manual +### 1. Lookup 1. Search and select all variables that you find interesting: dataset containing them will be available in the `Data` page. -## Data +### 2. Data 1. Choose an Eurostat dataset of interest (or start typing dataset code or title). 2. After loading, you can inspect the dataset and filter indexes, flags and time-span with the controls provided in the sidebar. 3. Every dataset that you inspect, along with your filtering choice, is saved and can be shown in the `Stash` page by ticking the dedicated checkbox. 4. You can repeat the process starting from _1_ for as many dataset as you like. -## Stash +### 3. Stash Stash it's where you can find every dataset that you inspected. The current stash will be reported here and you can _download_ it in a convenient gzipped csv. -## Timeseries +### 4. Timeseries Stash can also be inspected visually here as separated time series. In order to prevent long loading time, a message will inform you if the amount of variables to be plot are too high. -## Correlations +### 5. Correlations Stash time series how strong is the correlation across countries. In order to prevent long loading time, a message will inform you if the amount of variables to be plot are too high. -# Instruction +# Installation ## Run the app on localhost This is a [streamlit](https://streamlit.io/)-based app. Requirements are managed with [pipenv](https://pipenv.pypa.io/) (and it is highly suggested to use [pyenv](https://github.com/pyenv/pyenv) to manage python versions). Clone the repo and you should be able to run this command: @@ -27,6 +28,9 @@ pipenv run streamlit run Home.py ``` Based on your environment configuration, you may required to satisfy some system dependencies in order to execute the app smoothly. Please refer to the [FAQ](#FAQ) section to solve common issues. +## Live demo +This is a memory intensive webapp, so the cloud use is discouraged. Anyway, a best-effort live demo can be found [here](https://eurostat-datawizard-lum4chi.streamlit.app). + # Development App was developed with [vscode](https://code.visualstudio.com/). Use it to benefit from the `.vscode/settings.json` to configure testing environment. Install the full dev toolbox with the command: