Docs on new signal deployment details

_template_python/INDICATOR_DEV_GUIDE.md

@@ -278,7 +278,7 @@ This example is taken from [`hhs_hosp`](https://github.com/cmu-delphi/covidcast-
 
 The column is described [here](https://cmu-delphi.github.io/delphi-epidata/api/missing_codes.html).
 
-#### Testing
+#### Local testing
 
 As a general rule, it helps to decompose your functions into operations for which you can write unit tests.
 To run the tests, use `make test` in the top-level indicator directory.
@@ -411,29 +411,159 @@ Next, the `acquisition.covidcast` component of the `delphi-epidata` codebase doe
       12. `value_updated_timestamp`: now
    2. Update the `epimetric_latest` table with any new keys or new versions of existing keys.
 
+Consider what settings to use in the `params.json.template` file in accordance with how you want to run the indicator and acquisition.
+Pay attention to the receiving directory, as well as how you can store credentials in vault.
+Refer to [this guide](https://docs.google.com/document/d/1Bbuvtoxowt7x2_8USx_JY-yTo-Av3oAFlhyG-vXGG-c/edit#heading=h.8kkoy8sx3t7f) for more vault info.
+
+### CI/CD
+
+* Add module name to the `build` job in `.github/workflows/python-ci.yml`.
+  This allows github actions to run on this indicator code, which includes unit tests and linting.
+* Add top-level directory name to `indicator_list` in `Jenkinsfile`.
+  This allows your code to be automatically deployed to staging after your branch is merged to main, and deployed to prod after `covidcast-indicators` is released.
+* Create `ansible/templates/{top_level_directory_name}-params-prod.json.j2` based on your `params.json.template` with some adjustment:
+   * "export_dir": "/common/covidcast/receiving/{data-source-name}"
+   * "log_filename": "/var/log/indicators/{top_level_directory_name}.log"
+
+Pay attention to the receiving/export directory, as well as how you can store credentials in vault.
+Refer to [this guide](https://docs.google.com/document/d/1Bbuvtoxowt7x2_8USx_JY-yTo-Av3oAFlhyG-vXGG-c/edit#heading=h.8kkoy8sx3t7f) for more vault info.
+
 ### Staging
 
-After developing the pipeline code, but before deploying in development, the pipeline should be run on staging for at least a week.
-This involves setting up some cronicle jobs as follows:
+After developing the pipeline code, but before deploying in development, the pipeline should be tested on staging.
+Indicator runs should be set up to run automatically daily for at least a week.
 
-first the indicator run
+The indicator run code is automatically deployed on staging after your branch is merged into `main`.
+After merging, make sure you have proper access to Cronicle and staging server `app-mono-dev-01.delphi.cmu.edu` _and_ can see your code on staging at `/home/indicators/runtime/`.
 
-Then the acquisition run
+Then, on Cronicle, create two jobs: one to run the indicator and one to load the output csv files into database. 
 
-See [@korlaxxalrok](https://www.github.com/korlaxxalrok) or [@minhkhul](https://www.github.com/minhkhul) for more information.
+We start by setting up the acquisition job.
 
-https://cronicle-prod-01.delphi.cmu.edu/#Schedule?sub=edit_event&id=elr5clgy6rs
+#### Acquisition job
 
-https://cronicle-prod-01.delphi.cmu.edu/#Schedule?sub=edit_event&id=elr5ctl7art
+The indicator job loads the location of the relevant csv output files into chained data, which this acquisition job then loads into our database.
 
-Note the staging hostname and how the acquisition job is chained to run right after the indicator job.
-Do a few test runs.
+Example script:
 
-If everything goes well (check staging db if data is ingested properly), make a prod version of the indicator run job and use that to run indicator on a daily basis.
+```
+#!/usr/bin/python3
 
-Another thing to do is setting up the params.json template file in accordance with how you want to run the indicator and acquisition.
-Pay attention to the receiving directory, as well as how you can store credentials in vault.
-Refer to [this guide](https://docs.google.com/document/d/1Bbuvtoxowt7x2_8USx_JY-yTo-Av3oAFlhyG-vXGG-c/edit#heading=h.8kkoy8sx3t7f) for more vault info.
+import subprocess
+import json
+
+str_data = input()
+print(str_data)
+
+data = json.loads(str_data, strict=False)
+chain_data = data["chain_data"]
+user = chain_data["user"]
+host = chain_data["host"]
+acq_ind_name = chain_data["acq_ind_name"]
+
+cmd = f'''ssh -T -l {user} {host} "cd ~/driver && python3 -m delphi.epidata.acquisition.covidcast.csv_to_database --data_dir=/common/covidcast --indicator_name={acq_ind_name} --log_file=/var/log/epidata/csv_upload_{acq_ind_name}.log"'''
+
+std_err, std_out = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE).communicate()
+
+print(std_err.decode('UTF-8'))
+print(std_out.decode('UTF-8'))
+```
+
+#### Indicator run job
+
+This job signs into our staging server via ssh, runs the indicator, producing csv files as output.
+
+Example script:
+
+```
+#!/bin/sh
+
+# vars
+user='automation'
+host='app-mono-dev-01.delphi.cmu.edu'
+ind_name='nchs_mortality'
+acq_ind_name='nchs-mortality'
+
+# chain_data to be sent to acquisition job
+chain_data=$(jo chain_data=$(jo acq_ind_name=${acq_ind_name} ind_name=${ind_name} user=${user} host=${host}));
+echo "${chain_data}";
+
+ssh -T -l ${user} ${host} "sudo -u indicators -s bash -c 'cd /home/indicators/runtime/${ind_name} && env/bin/python -m delphi_${ind_name}'";
+```
+
+Note the staging hostname in `host` and how the acquisition job is chained to run right after the indicator job.
+
+Note that `ind_name` variable here refer to the top-level directory name where code is located, while `acq_ind_name` refer to the directory name where output csv files are located, which corresponds to the name of `source` column in our database, as mentioned in step 3.
+
+To automatically run acquisition job right after indicator job finishes successfully:
+
+1. In `Plugin` section, select `Interpret JSON in Output`.
+2. In `Chain Reaction` section, select your acquisition run job below to `Run Event on Success`
+
+You can read more about how the `chain_data` json object in the script above can be used in our subsequent acquisition job [here](https://github.com/jhuckaby/Cronicle/blob/master/docs/Plugins.md#chain-reaction-control).
+
+#### Staging database checks
+
+Apart from checking the logs of staging indicator run and acquisition jobs to identify potential issues with the pipeline, one can also check the contents of staging database for abnormalities.
+
+At this point, acquisition job should have loaded data onto staging mysql db, specifically the `covid` database.
+
+From staging:
+```
+[user@app-mono-dev-01 ~]$ mysql -u user -p
+Enter password: 
+Welcome to the MySQL monitor.  Commands end with ; or \g.
+Your MySQL connection id is 00000
+Server version: 8.0.36-28 Percona Server (GPL), Release 28, Revision 47601f19
+
+Copyright (c) 2009-2024 Percona LLC and/or its affiliates
+Copyright (c) 2000, 2024, Oracle and/or its affiliates.
+
+Oracle is a registered trademark of Oracle Corporation and/or its
+affiliates. Other names may be trademarks of their respective
+owners.
+
+Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.
+
+mysql> use covid;
+Database changed
+```
+Check `signal_dim` table to see if new source and signal names are all present and reasonable. For example:
+```
+mysql> select * from signal_dim where source='nssp';
++---------------+--------+----------------------------------+
+| signal_key_id | source | signal                           |
++---------------+--------+----------------------------------+
+|           817 | nssp   | pct_ed_visits_combined           |
+|           818 | nssp   | pct_ed_visits_covid              |
+|           819 | nssp   | pct_ed_visits_influenza          |
+|           820 | nssp   | pct_ed_visits_rsv                |
+|           821 | nssp   | smoothed_pct_ed_visits_combined  |
+|           822 | nssp   | smoothed_pct_ed_visits_covid     |
+|           823 | nssp   | smoothed_pct_ed_visits_influenza |
+|           824 | nssp   | smoothed_pct_ed_visits_rsv       |
++---------------+--------+----------------------------------+
+```
+
+Then, check if the number of records ingested in db matches with the number of rows in csv when running locally.
+For example, the below query sets the `issue` date being the day acquisition job was run, and `signal_key_id` correspond with signals from our new source.
+Check if this count matches with local run result.
+
+```
+mysql> SELECT count(*) FROM epimetric_full WHERE issue=202425 AND signal_key_id > 816 AND signal_key_id < 825;
++----------+
+| count(*) |
++----------+
+|  2620872 |
++----------+
+1 row in set (0.80 sec)
+```
+
+You can also check how data looks more specifically at each geo level or among different signal names depending on the quirks of the source.
+
+See [@korlaxxalrok](https://www.github.com/korlaxxalrok) or [@minhkhul](https://www.github.com/minhkhul) for more information.
+
+If everything goes well make a prod version of the indicator run job and use that to run indicator on a daily basis.
 
 ### Signal Documentation