Skip to content

dataforgoodfr/quotaclimat

Repository files navigation

QuotaClimat x Data For Good - badge

The aim of this work is to deliver a tool to a consortium around QuotaClimat, Climat Medias allowing them to quantify the media coverage of the climate crisis.

Radio and TV data are collected thanks to Mediatree API.

And webpress is currently at work in progress (as for 04/2024)

Index

🤱 I want to contribute! Where do I start?

  1. Learn about the project by watching the introduction videos mentioned above.
  2. Create an issue or/and join https://dataforgood.fr/join and the Slack #offseason_quotaclimat.
  3. Introduce yourself on Slack #offseason_quotaclimat

🔧 Development

Contributing

🔩 Setting up the environment

Doing the following step will enable your local environement to be aligned with the one of any other collaborator.

First install pyenv:

OS Command
MacOS
cd -
brew install pyenv # pyenv itself
brew install pyenv-virtualenv # integration with Python virtualenvsec
Ubuntu
sudo apt-get update; sudo apt-get install make build-essential libssl-dev zlib1g-dev \
libbz2-dev libreadline-dev libsqlite3-dev wget curl llvm \
libncursesw5-dev xz-utils tk-dev libxml2-dev libxmlsec1-dev libffi-dev liblzma-dev

curl https://pyenv.run | bash
Windows An installation using miniconda is generally simpler than a pyenv one on Windows.

Make the shell pyenv aware:

OS Command
MacOS
eval "$(pyenv init --path)"
eval "$(pyenv init -)"
eval "$(pyenv virtualenv-init -)"
Ubuntu
export PYENV_ROOT="$HOME/.pyenv"
command -v pyenv >/dev/null || export PATH="$PYENV_ROOT/bin:$PATH"
eval "$(pyenv init -)"
eval "$(pyenv virtualenv-init -)"
Windows

🇫🇷 Dans Propriétés systèmes > Paramètres système avancés > Variables d'environnement... Choisissez la variable "Path" > Modifier... et ajoutez le chemin de votre installation python, où se trouve le python.exe. (par défaut, C:\Users\username\AppData\Roaming\Python\Scripts\ )

🇬🇧 In System Properties > Advanced > Environment Variables... Choose the variable "Path" > Edit... et add the path to your python's installation, where is located the pyhton.exe (by default, this should be at C:\Users\username\AppData\Roaming\Python\Scripts\ )

In the console, you can now try :

poetry --version

Let's install a python version (for windows, this step have been done with miniconda):

pyenv install 3.11.6 # this will take time

Check if it works properly, this command:

pyenv versions

should return:

  system
  3.11.6

Then you are ready to create a virtual environment. Go in the project folder, and run:

  pyenv virtualenv 3.11.6 quotaclimat
  pyenv local quotaclimat

In case of a version upgrade you can perform this command to switch

eval "$(pyenv init --path)"
pyenv activate 3.11.6/envs/quotaclimat

You now need a tool to manage dependencies. Let's use poetry. On windows, if not already installed, you will need a VS installation.

Link : https://wiki.python.org/moin/WindowsCompilers#Microsoft_Visual_C.2B-.2B-_14.x_with_Visual_Studio_2022_.28x86.2C_x64.2C_ARM.2C_ARM64.29

pip install poetry
poetry update

NLDA : I have not been able to work with wordcloud on windows.

When you need to install a new dependency (use a new package, e.g. nltk), run

poetry add ntlk

Update dependencies

poetry self update

After commiting to the repo, other team members will be able to use the exact same environment you are using.

Docker

First, have docker and compose installed on your computer

Then to start the different services

## To run only one service, have a look to docker-compose.yml and pick one service :
docker compose up metabase
docker compose up ingest_to_db
docker compose up mediatree
docker compose up test

If you add a new dependency, don't forget to rebuild

docker compose build test # or ingest_to_db, mediatree etc

Explore postgres data using Metabase - a BI tool

docker compose up metabase -d

Will give you access to Metabase to explore the SQL table sitemap table or keywords here : http://localhost:3000/

To connect to it you have use the variables used inside docker-compose.yml :

  • password: password
  • username: user
  • db: barometre
  • host : postgres_db

Production metabase

If we encounter a OOM error, we can set this env variable : JAVA_OPTS=-Xmx2g

Web Press - How to scrap

The scrapping of sitemap.xml is done using the library advertools.

A great way to discover sitemap.xml is to check robots.txt page of websites : https://www.midilibre.fr/robots.txt

What medias to parse ? This document is a good start.

Learn more about site maps here.

Scrap every sitemaps

By default, we use a env variable ENV to only parse from localhost. If you set this value to another thing that docker or dev, it will parse everything.

Test

Thanks to the nginx container, we can have a local server for sitemap :

docker compose up -d nginx # used to scrap sitemap locally - a figaro like website with only 3 news
# docker compose up test with entrypoint modified to sleep
# docker exec test bash
pytest -vv --log-level DEBUG test # "test" is the folder containing tests
# Only one test
pytest -vv --log-level DEBUG -k detect
# OR
docker compose up test # test is the container name running pytest test

Deploy

Every commit on the main branch will build an deploy to the Scaleway container registry a new image that will be deployed. Have a look to .github/deploy-main.yml.

Learn more here.

Monitoring

With Sentry, with env variable SENTRY_DSN.

Learn more here : https://docs.sentry.io/platforms/python/configuration/options/

Mediatree - Import data

Mediatree Documentation API : https://keywords.mediatree.fr/docs/

You must contact QuotaClimat team to 2 files with the API's username and password inside :

  • secrets/pwd_api.txt
  • secrets/username_api.txt

Otherwise, a mock api response is available at https://github.com/dataforgoodfr/quotaclimat/blob/main/test/sitemap/mediatree.json

Run

docker compose up mediatree

Configuration - Batch import

Based on time

If our media perimeter evolves, we have to reimport it all using env variable START_DATE like in docker compose (epoch second format : 1705409797).

Otherwise, default is yesterday midnight date (default cron job)

Based on channel

Use env variable CHANNEL like in docker compose (string: tf1)

Otherwise, default is all channels

Update without querying Mediatre API

In case we have a new word detection logic - and already saved data from Mediatree inside our DB (otherwise see Batch import based on time or channel) - we can re-apply it to all saved keywords inside our database.

⚠️ in this case, as we won't requery Mediatree API so we can miss some chunks, but it's faster. Choose wisely between importing/updating.

We should use env variable UPDATE like in docker compose (should be set to "true")

In order to see actual change in the local DB, run the test first docker compose up test and then these commands :

docker exec -ti quotaclimat-postgres_db-1 bash
psql -h localhost --port 5432 -d barometre -U user
--> enter password : password
UPDATE keywords set number_of_keywords=1000 WHERE id = '71b8126a50c1ed2e5cb1eab00e4481c33587db478472c2c0e74325abb872bef6';
UPDATE keywords set number_of_keywords=1000 WHERE id = '975b41e76d298711cf55113a282e7f11c28157d761233838bb700253d47be262';

After having updated UPDATE env variable to true inside docker-compose.yml and running docker compose up mediatree you should see these logs :

 update_pg_keywords.py:20 | Difference old 1000 - new_number_of_keywords 0

Batch program data

UPDATE_PROGRAM_ONLY to true will only update program metadata, otherwise, it will update program metadata and all theme/keywords calculations.

Batch update from an offset

With +1 millions rows, we can update from an offset to fix a custom logic by using START_OFFSET to batch update PG from a offset.

~55 minutes to update 50K rows on a mVCPU 2240 - 4Gb RAM on Scaleway.

Example inside the docker-compose.yml mediatree service -> START_OFFSET: 100

We can use a Github actions to start multiple update operations with different offsets

SQL Tables evolution

Using Alembic Auto Generating Migrations¶ we can add a new column inside models.py and it will automatically make the schema evolution :

# If changes have already been applied and you want to recreate your alembic file:
# 1. change to you main branch
# 2. start test container and run "pytest -vv -k api" to rebuild the state of the DB (or drop table the table you want)
# 3. rechange to your WIP branch 
# 4. connect to the test container : docker compose up test -d / docker compose exec test bash
# 5. reapply the latest saved state : poetry run alembic upgrade head
# 6. Save the new columns
poetry run alembic revision --autogenerate -m "Add new column test for table keywords"
# this should generate a file to commit inside "alembic/versions"
# 7. to apply it we need to run, from our container
poetry run alembic upgrade head

Inside our Dockerfile_api_import, we call this line

# to migrate SQL tables schema if needed
RUN alembic upgrade head

Channel metadata

In order to maintain channel perimeter (weekday, hours) up to date, we save the current version inside postgres/channel_metadata.json, if we modify this file the next deploy will update every lines of inside Postgresql table channel_metadata.

Keywords

Produce keywords list from Excel files

How to update quotaclimat/data_processing/mediatree/keyword/keyword.py from shared excel files ? Download files locally then :

poetry run python3 quotaclimat/transform_excel_to_json.py > cc-bio.json
# then update quotaclimat/data_processing/mediatree/keyword/keyword.py list

Program Metadata table

The media perimeter is defined here : "quotaclimat/data_processing/mediatree/channel_program.json"

To calculate the right total duration for each channel, after updating "quotaclimat/data_processing/mediatree/channel_program.json" you need to execute this command to update postgres/program_metadata.json

poetry run python3 transform_program.py

The SQL queries are based on this file that generate the Program Metadata table.

With the docker-entrypoint.sh this command is done automatically, so for production uses, you will not have to run this command.

Production monitoring

  • Use scaleway
  • Use [Ray dashboard] on port 8265

Fix linting

Before committing, make sure that the line of codes you wrote are conform to PEP8 standard by running:

poetry run black .
poetry run isort .
poetry run flake8 .

There is a debt regarding the cleanest of the code right now. Let's just not make it worth for now.

Thanks

About

Observatoire Ecologique Mediatique

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages