diff --git a/README.md b/README.md
index e387459..de9572c 100644
--- a/README.md
+++ b/README.md
@@ -31,6 +31,7 @@ conda update --all
 conda install -c conda-forge heudiconv git-annex=*=alldep* datalad
 ```
 ## Usage
+
 ## How to download Shanoir datasets ?
 
 There are three scripts to download datasets from a Shanoir instance: 
@@ -58,9 +59,11 @@ See `python shanoir_downloader_check.py --help` for more information.
 
 You might want to skip the anonymization process and the encryption process with the `--skip_anonymization` and `--skip_encryption` arguments respectively (or `-sa` and `-se`).
 
+
 ### `shanoir2bids.py`
 
 A `.json` configuration file must be provided to transform a Shanoir dataset into a BIDS dataset.
+
 ```
 -----------------------------[.json configuration file information]-------------------------------
 This file will tell the script what Shanoir datasets should be downloaded and how the data will be organised.
@@ -71,23 +74,29 @@ The dictionary in the json file must have four keys :
 "data_to_bids": list of dict, each dictionary specifies datasets to download and BIDS format with the following keys :
     -> "datasetName": str, Shanoir name for the sequence to search
     -> "bidsDir"    : str, BIDS subdirectory sequence name (eg : "anat", "func" or "dwi", ...)
+
     -> "bidsName"   : str, BIDS sequence name (eg: "t1w", "acq-b0_dir-AP", ...)
 ```
 Please refer to the [BIDS starter kit](https://bids-standard.github.io/bids-starter-kit/folders_and_files/files.html) 
 for exhaustive templates of filenames. A BIDS compatible example is provided in the file `s2b_example_config.json`.
 
+
 To download longitudinal data, a key `session` and a new entry `bidsSession` in `data_to_bids` dictionaries should be defined in the JSON configuration files. Of note, only one session can be downloaded at once. Then, the key `session` is just a string, not a list as for subjects.
 
 
+
 ### Download Examples 
 #### Raw download 
+
 To download datasets, verify the content of them, anonymize them and / or encrypt them you can use a command like:
 
 `python shanoir_downloader_check.py -u username -d shanoir.irisa.fr -ids path/to/datasets_to_download.csv -of path/to/output/folder/ -se -lf path/to/downloads.log`
 
 The `example_input_check.csv` file in this repository is an example input file (the format of the `datasets_to_download.csv` file should be the same).
 
+
 #### Solr search download
+
 You can also download datasets from a [SolR search](https://shanoir.irisa.fr/shanoir-ng/solr-search) as on the website:
 
 `python shanoir_downloader.py -u amasson -d shanoir.irisa.fr -of /data/amasson/test/shanoir_test4 --search_text "FLAIR" -p 1 -s 2 `
@@ -99,6 +108,7 @@ where `--search_text` is the string you would use on [the SolR search page](http
 
 ## About Solr Search 
 
+
 The `--search_text` and `--expert_mode` arguments work as on the [Shanoir search page](https://shanoir.irisa.fr/shanoir-ng/solr-search).
 
 Without expert mode, shanoir will return all datasets containing one of the search term in one of their field.
diff --git a/pyproject.toml b/pyproject.toml
index fde5251..514f2ca 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -23,11 +23,13 @@ readme = "README.md"
 license = {file = "LICENSE"}
 keywords = ["Shanoir", "DICOM", "NIFTI", "BIDS"]
 classifiers = [
+
   "Programming Language :: Python",
   "Programming Language :: Python :: 3",
   "Programming Language :: Python :: 3.8",
   "Programming Language :: Python :: 3.9",
   "Programming Language :: Python :: 3.10"
+
 ]
 
 [project.urls]