Add workflow

.github/workflows/crawl_downloads.yml

@@ -0,0 +1,25 @@
+name: crawl-zenodo-downloads
+
+on: 
+  push:
+  schedule:
+  - cron: '0 12 * * *'
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v4
+      with:
+        ref: zenodo
+    - name: Run
+      run: |
+        pip3 install -r requirements.txt --quiet
+        curl https://zenodo.org/record/8196385 > zenodo_page.txt
+        python3 crawl.py
+        git config --local user.name "${GITHUB_ACTOR}"
+        git config --local user.email "${GITHUB_ACTOR}@users.noreply.github.com"
+        export remote_repo="https://${GITHUB_ACTOR}:${{ secrets.GITHUB_TOKEN }}@github.com/${GITHUB_REPOSITORY}.git"
+        git add *.json
+        git commit -m "Update downloads" --amend --reset-author
+        git push -f "${remote_repo}" zenodo

README.md

@@ -37,11 +37,12 @@ Loghub maintains a collection of system logs, which are freely accessible for AI
 ### Datasets download 
 We host only a small sample (2k lines) of each log dataset on Github. If you are interested in these raw datasets, please download them [via Zenodo](https://doi.org/10.5281/zenodo.1144100).
 
-:bell: We proudly announce that the loghub datasets have attained [**90000+ total downloads**](https://doi.org/10.5281/zenodo.1144100) by more than [**450 organizations**](https://github.com/logpai/loghub/wiki/Loghub-download-list) from both industry and academia.
+:bell: We proudly announce that the loghub datasets have attained total <a href="https://doi.org/10.5281/zenodo.1144100"><img src="https://img.shields.io/endpoint?&url=https://cdn.jsdelivr.net/gh/logpai/loghub@zenodo/downloads.json&labelColor=grey&color=4EB999&style=flat&label=Downloads"></a> by more than [**450 organizations**](https://github.com/logpai/loghub/wiki/Loghub-download-list) from both industry and academia.
 
+### 🌈 Citation
 
-### Citation
 Please cite the following paper if you use the loghub datasets for research.
+
 + Jieming Zhu, Shilin He, Pinjia He, Jinyang Liu, Michael R. Lyu. [Loghub: A Large Collection of System Log Datasets for AI-driven Log Analytics](https://arxiv.org/abs/2008.06448). IEEE International Symposium on Software Reliability Engineering (ISSRE), 2023.