issue_comments
2 rows where user = 58298410
This data as json, CSV (advanced)
Suggested facets: created_at (date), updated_at (date)
id ▼ | html_url | issue_url | node_id | user | created_at | updated_at | author_association | body | reactions | issue | performed_via_github_app |
---|---|---|---|---|---|---|---|---|---|---|---|
641889565 | https://github.com/simonw/datasette/issues/394#issuecomment-641889565 | https://api.github.com/repos/simonw/datasette/issues/394 | MDEyOklzc3VlQ29tbWVudDY0MTg4OTU2NQ== | LVerneyPEReN 58298410 | 2020-06-10T09:49:34Z | 2020-06-10T09:49:34Z | NONE | Hi, I came across this issue while looking for a way to spawn Datasette as a SQLite files viewer in JupyterLab. I found https://github.com/simonw/jupyterserverproxy-datasette-demo which seems to be the most up to date proof of concept, but it seems to be failing to list the available db (at least in the Binder demo, https://hub.gke.mybinder.org/user/simonw-jupyters--datasette-demo-uw4dmlnn/datasette/, I only have `:memory`). Does anyone tried to improve on this proof of concept to have a Datasette visualization for SQLite files? Thanks! | {"total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0} | base_url configuration setting 396212021 | |
642522285 | https://github.com/simonw/datasette/issues/394#issuecomment-642522285 | https://api.github.com/repos/simonw/datasette/issues/394 | MDEyOklzc3VlQ29tbWVudDY0MjUyMjI4NQ== | LVerneyPEReN 58298410 | 2020-06-11T09:15:19Z | 2020-06-11T09:15:19Z | NONE | Hi @wragge, This looks great, thanks for the share! I refactored it into a self-contained function, binding on a random available TCP port (multi-user context). I am using subprocess API directly since the `%run` magic was leaving defunct process behind :/ ![image](https://user-images.githubusercontent.com/58298410/84367566-b5d0d500-abd4-11ea-96e2-f5c05a28e506.png) ```python import socket from signal import SIGINT from subprocess import Popen, PIPE from IPython.display import display, HTML from notebook.notebookapp import list_running_servers def get_free_tcp_port(): """ Get a free TCP port. """ tcp = socket.socket(socket.AF_INET, socket.SOCK_STREAM) tcp.bind(('', 0)) _, port = tcp.getsockname() tcp.close() return port def datasette(database): """ Run datasette on an SQLite database. """ # Get current running servers servers = list_running_servers() # Get the current base url base_url = next(servers)['base_url'] # Get a free port port = get_free_tcp_port() # Create a base url for Datasette suing the proxy path proxy_url = f'{base_url}proxy/absolute/{port}/' # Display a link to Datasette display(HTML(f'<p><a href="{proxy_url}">View Datasette</a> (Click on the stop button to close the Datasette server)</p>')) # Launch Datasette with Popen( [ 'python', '-m', 'datasette', '--', database, '--port', str(port), '--config', f'base_url:{proxy_url}' ], stdout=PIPE, stderr=PIPE, bufsize=1, universal_newlines=True ) as p: print(p.stdout.readline(), end='') while True: try: line = p.stderr.readline() if not line: break print(line, end='') exit_code = p.poll() except KeyboardInterrupt: p.send_signal(SIGINT) ``` Ideal… | {"total_count": 1, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 1, "rocket": 0, "eyes": 0} | base_url configuration setting 396212021 |
Advanced export
JSON shape: default, array, newline-delimited, object
CREATE TABLE [issue_comments] ( [html_url] TEXT, [issue_url] TEXT, [id] INTEGER PRIMARY KEY, [node_id] TEXT, [user] INTEGER REFERENCES [users]([id]), [created_at] TEXT, [updated_at] TEXT, [author_association] TEXT, [body] TEXT, [reactions] TEXT, [issue] INTEGER REFERENCES [issues]([id]) , [performed_via_github_app] TEXT); CREATE INDEX [idx_issue_comments_issue] ON [issue_comments] ([issue]); CREATE INDEX [idx_issue_comments_user] ON [issue_comments] ([user]);