Adjust documentation

Former-commit-id: 7062769

Author: amotl

DATA_GENERATOR.md

@@ -86,7 +86,7 @@ The Data Generator is a tool to generate timeseries data which adheres to a [sta
 
 An easy way to use the Data Generator is to install it via `pip`:
 
-+ Open a terminal and type `pip install tsdb-data-generator`
++ Open a terminal and type `pip install tsdg`
 + Look at the default configuration of the Data Generator by executing `tsdg -h` in a terminal
 + Run the Data Generator with the desired configuration values by executing `tsdg` in a terminal
 

LICENSE

@@ -175,28 +175,3 @@
       of your accepting any such warranty or additional liability.
 
    END OF TERMS AND CONDITIONS
-
-   APPENDIX: How to apply the Apache License to your work.
-
-      To apply the Apache License to your work, attach the following
-      boilerplate notice, with the fields enclosed by brackets "[]"
-      replaced with your own identifying information. (Don't include
-      the brackets!)  The text should be enclosed in the appropriate
-      comment syntax for the file format. We also recommend that a
-      file or class name and description of purpose be included on the
-      same "printed page" as the copyright notice for easier
-      identification within third-party archives.
-
-   Copyright [yyyy] [name of copyright owner]
-
-   Licensed under the Apache License, Version 2.0 (the "License");
-   you may not use this file except in compliance with the License.
-   You may obtain a copy of the License at
-
-       http://www.apache.org/licenses/LICENSE-2.0
-
-   Unless required by applicable law or agreed to in writing, software
-   distributed under the License is distributed on an "AS IS" BASIS,
-   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-   See the License for the specific language governing permissions and
-   limitations under the License.

README.md

@@ -1,4 +1,4 @@
-![tag_build_and_push](https://github.com/crate/ts-data-generator/workflows/tag_build_and_push/badge.svg?branch=master) ![code_quality](https://github.com/crate/ts-data-generator/workflows/code_quality/badge.svg)
+![Tests](https://github.com/crate/tsdg/workflows/Tests/badge.svg)
 
 # Data Generator
 
@@ -9,3 +9,11 @@ data, without the need to set up an ingestion chain (which could be Azure IoTHub
 ## Maximizing Performance
 
 To maximize performance multiple instances of the Data Generator must be run in parallel. One way to achieve this is using kubernetes how to do this is documented [here](KUBERNETES.md).
+
+## Setup sandbox
+```shell
+python3 -m venv .venv
+source .venv/bin/activate
+pip install --editable=.[testing]
+pytest -vvv tests
+```

QUERY_TIMER.md renamed to query_timer/README.md

@@ -12,11 +12,14 @@ The Query Timer is a tool to run queries against different databases and determi
 
 #### Pip install
 
-The Query Timer is part of the tsdb-data-generator package and can be installed using `pip install tsdb-data-generator`.
+The Query Timer is part of the tsdb-data-generator package and can be installed using `pip install tsdg`.
 
-By calling `tsqt -h` the possible configurations are listed. For further details see [Query Timer Configuration](#query-timer-configuration). All configurations can be done with either command line arguments or environment variables but when both are set then command line arguments will be used.
+By calling `tsqt -h` the possible configurations are listed. For further details see
+[Query Timer Configuration](#query-timer-configuration). All configurations can be done with either command line
+arguments or environment variables but when both are set then command line arguments will be used.
 
-When calling `tsqt` with the desired arguments the Query Timer outputs live updated statistics on the query execution. This includes:
+When calling `tsqt` with the desired arguments the Query Timer outputs live updated statistics on the query execution.
+This includes:
 
 + concurrency: how many threads are running, defined by [CONCURRENCY](#concurrency)
 + iterations: how many queries will be done in each thread, defined by [ITERATIONS](#iterations)
@@ -48,7 +51,8 @@ Currently 7 Databases are
 
 ##### Client Library
 
-For CrateDB the [crate](https://pypi.org/project/crate/) library is used. To connect to CrateDB the following environment variables must be set:
+For CrateDB the [crate](https://pypi.org/project/crate/) library is used. To connect to CrateDB the following
+environment variables must be set:
 
 + [HOST](#host): hostname including port e.g. `localhost:4200`
 + [USERNAME](#username): CrateDB username.
@@ -58,7 +62,8 @@ For CrateDB the [crate](https://pypi.org/project/crate/) library is used. To con
 
 ##### Client Library
 
-For InfluxDB the [influx-client](https://pypi.org/project/influxdb-client/) library is used as the Data Generator only supports InfluxDB V2. To connect to InfluxDB the following environment variables must be set:
+For InfluxDB the [influx-client](https://pypi.org/project/influxdb-client/) library is used as the Data Generator only
+supports InfluxDB V2. To connect to InfluxDB the following environment variables must be set:
 
 + [HOST](#host): hostname
 + [TOKEN](#token): InfluxDB Read/Write token
@@ -86,7 +91,8 @@ To connect with TimescaleDB the following environment variables must be set:
 
 ##### Client Library
 
-For MongoDB the [MongoClient](https://mongodb.github.io/node-mongodb-native/api-generated/mongoclient.html) library is used.
+For MongoDB the [MongoClient](https://mongodb.github.io/node-mongodb-native/api-generated/mongoclient.html) library is
+used.
 
 To connect with MongoDB the following environment variables must be set:
 
@@ -97,7 +103,8 @@ To connect with MongoDB the following environment variables must be set:
 
 ##### Specifics
 
-Because `pymongo` does not support queries as string, Support for MongoDB is turned of in the binary. To still use the Query Timer with Mongo DB have a look at the [Using MongoDB](#using-mongodb) section of this documentation. 
+Because `pymongo` does not support queries as string, Support for MongoDB is turned of in the binary. To still use the
+Query Timer with Mongo DB have a look at the [Using MongoDB](#using-mongodb) section of this documentation. 
 
 #### PostgreSQL
 
@@ -128,7 +135,8 @@ To connect with AWS Timestream the following environment variables must be set:
 
 ##### Specifics
 
-+ Tests have shown that queries often fail due to server errors. To accommodate this an automatic retry is implemented that tries to execute the query a second time. If it fails again the query is marked as failure.
++ Tests have shown that queries often fail due to server errors. To accommodate this an automatic retry is implemented
+  that tries to execute the query a second time. If it fails again the query is marked as failure.
 
 #### Microsoft SQL Server
 
@@ -146,21 +154,24 @@ To connect with Microsoft SQL Server the following environment variables must be
 
 ### Using MongoDB
 
-To use the Query Timer with MongoDB the code of the Query Timer needs to be changed. Therefore checkout this [repository](https://www.github.com/crate/ts-data-generator). 
+To use the Query Timer with MongoDB the code of the Query Timer needs to be changed. Therefore checkout this
+[repository](https://www.github.com/crate/tsdg). 
 
 + In [this](query_timer/__main__.py) file uncomment the import statement of the `MongoDBWriter` 
 + Also uncomment the instantiation of the `db_writer` in the `get_db_writer` function 
 + Comment the `ValueError` in the line above
 
 This should let you start the Query Timer using `DATABASE` set to MongoDB.
 
-To add the query you want to measure add a variable containing your query to the script and pass this variable to `db_writer.execute_query()` in the `start_query_run` function, instead of `config.query`.
+To add the query you want to measure add a variable containing your query to the script and pass this variable to
+`db_writer.execute_query()` in the `start_query_run` function, instead of `config.query`.
 
 Now the Query Timer is able to measure query execution times for MongoDB.
 
 ## Query Timer Configuration
 
-The Query Timer is mostly configured by setting Environment Variables (or command line arguments start with `-h` for more information). This chapter lists all available Environment Variables and explains their use in the Query Time.
+The Query Timer is mostly configured by setting Environment Variables (or command line arguments start with `-h` for
+more information). This chapter lists all available Environment Variables and explains their use in the Query Time.
 
 ### Environment variables configuring the behaviour of the Query Time
 
@@ -288,7 +299,8 @@ Default: empty string
 used with TimescaleDB, MongoDB, AWS Timestream, Postgresql, MSSQL.
 
 **TimescaleDB, Postgresql, MSSQL:**
-The value of `DB_NAME` is used when connecting to TimescaleDB. This database must already exist in your TimescaleDB instance and must have already been initialized with `CREATE EXTENSION IF NOT EXISTS timescaledb CASCADE;`.
+The value of `DB_NAME` is used when connecting to TimescaleDB. This database must already exist in your TimescaleDB
+instance and must have already been initialized with `CREATE EXTENSION IF NOT EXISTS timescaledb CASCADE;`.
 
 **MongoDB:**
 The value of `DB_NAME` is used as the database parameter of MongoDB.
@@ -362,11 +374,14 @@ Default: empty string
 
 ## Alternative Query Timers
 
-As the Query Timer is just a by-product of the Data Generator there are other alternatives that offer more features and ways to time queries. The main advantage of the Query Timer is that it supports all Databases that are also supported by the Data Generator and is easy and fast to use.
+As the Query Timer is just a by-product of the Data Generator there are other alternatives that offer more features and
+ways to time queries. The main advantage of the Query Timer is that it supports all Databases that are also supported by
+the Data Generator and is easy and fast to use.
 
 ### cr8
 
-[cr8](https://github.com/mfussenegger/cr8) is a highly sophisticated tool that offers the possibility to measure query execution times for CrateDB and other Databases using the postgres protocol.
+[cr8](https://github.com/mfussenegger/cr8) is a highly sophisticated tool that offers the possibility to measure query
+execution times for CrateDB and other Databases using the postgres protocol.
 
 Pros:
 
@@ -380,7 +395,8 @@ Cons:
 
 ### JMeter
 
-[Jmeter](https://jmeter.apache.org/) is a well known and great tool that offers the possibility to measure query execution times for Databases using JDBC.
+[Jmeter](https://jmeter.apache.org/) is a well known and great tool that offers the possibility to measure query
+execution times for Databases using JDBC.
 
 Pros: 
 

tictrack/README.md

@@ -1,11 +1,11 @@
 # tictrack
 
-`tictrack` is a python library to measure function execution times and apply statistical functions on the results.
+`tictrack` is a Python library to measure function execution times and apply statistical functions on the results.
 
 ## Why using tictrack instead of other libraries
 
 Other libraries that measure function execution times require the same repetitive code for each time you want to use it.
-This reduces readability and code needs to be changed when execution times no longer want to be tracked. Also if an
+This reduces readability and code needs to be changed when execution times no longer want to be tracked. Also, if an
 average (or other statistical value) execution time needs to be calculated time keeping needs to be implemented again.
 
 `tictrack` solves this with the following features: